Eprints.soton.ac.uk



Single-cell transcriptomic analysis of tissue-resident memory T cells in human lung cancer.James Clarke1,2, Bharat Panwar1, Ariel Madrigal1, Divya Singh1, Ravindra Gujar1, Oliver Wood2, Serena J Chee2,3, Simon Eschweiler1, Emma King2,4, Amiera S Awad3,5, Christopher J Hanley2, Katy J McCann2, Sourya Bhattacharyya1, Edwin Woo3, Aiman Alzetani3, Grégory Seumois1, Gareth J Thomas2, Anusha-Preethi Ganesan1, Peter S Friedmann5, Tilman Sanchez-Elsner5, Ferhat Ay1, Christian H Ottensmeier2,7, Pandurangan Vijayanand1,5,6,7*.1La Jolla Institute for Allergy and Immunology, La Jolla, CA, USA.2NIHR and CRUK Southampton Experimental Cancer Medicine Center & NIHR Southampton Biomedical Research Center & Cancer Sciences Unit, Faculty of Medicine, University of Southampton, Southampton, UK.3Southampton University Hospitals NHS Foundation Trust, Southampton, UK.4Department of Otolaryngology, Poole Hospital NHS Foundation Trust, Poole, Dorset, United Kingdom.5Clinical and Experimental Sciences, National Institute for Health Research Southampton. Respiratory Biomedical Research Unit, University of Southampton, Faculty of Medicine, Southampton UK.6Department of Medicine, University of California San Diego, La Jolla, CA, USA. 7These authors jointly directed the work*Corresponding authorCorrespondence should be addressed to P.V. (vijay@); La Jolla Institute for Immunology, 9420 Athena Circle?La Jolla,?CA?92037. ORCID identifier is 0000-0001-7067-9723.Non-standard abbreviation listATAC-seq: Assay for Transposase-Accessible Chromatin using sequencingCTL: CD8+ cytotoxic T lymphocytesGSEA: Gene set enrichment analysisTCR; T cell receptorTRM: Tissue-Resident MemorySummaryClarke et al. interrogate human TRM cells from cancer and non-malignant tissue. These analyses highlight that PD-1 expression in tumor-infiltrating TRM cells was positively correlated with features suggestive of active proliferation and superior functionality rather than dysfunction.ABSTRACT High numbers of tissue-resident memory T (TRM) cells are associated with better clinical outcomes in cancer patients. However, the molecular characteristics that drive their efficient immune response to tumors are poorly understood. Here, single-cell and bulk transcriptomic analysis of TRM and non-TRM cells present in tumor and normal lung tissue from patients with lung cancer, revealed that PD-1 expressing TRM cells in tumors were clonally expanded and enriched for transcripts linked to cell proliferation and cytotoxicity when compared to PD-1 expressing non-TRM cells. This feature was more prominent in the TRM subset co-expressing PD-1 and TIM-3, and it was validated by functional assays ex-vivo and also reflected in their chromatin accessibility profile. This PD-1+TIM-3+ TRM subset was enriched in responders to PD-1 inhibitors and in tumors with a greater magnitude of CTL responses. These data highlight that not all CTLs expressing PD-1 are dysfunctional, on the contrary, TRM cells with PD-1 expression were enriched for features suggestive of superior functionality. INTRODUCTIONIn lung cancer and many other solid tumors, patient survival is positively correlated with an effective adaptive anti-tumor immune response ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/science.1129139","ISBN":"0036-8075","ISSN":"0036-8075","PMID":"17008531","abstract":"The role of the adaptive immune response in controlling the growth and recurrence of human tumors has been controversial. We characterized the tumor-infiltrating immune cells in large cohorts of human colorectal cancers by gene expression profiling and in situ immunohistochemical staining. Collectively, the immunological data (the type, density, and location of immune cells within the tumor samples) were found to be a better predictor of patient survival than the histopathological methods currently used to stage colorectal cancer. The results were validated in two additional patient populations. These data support the hypothesis that the adaptive immune response influences the behavior of human tumors. In situ analysis of tumor-infiltrating immune cells may therefore be a valuable prognostic tool in the treatment of colorectal cancer and possibly other malignancies.","author":[{"dropping-particle":"","family":"Galon","given":"Jér?me","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science","id":"ITEM-1","issue":"5795","issued":{"date-parts":[["2006","9","29"]]},"page":"1960-1964","title":"Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome","type":"article-journal","volume":"313"},"uris":[""]}],"mendeley":{"formattedCitation":"(Galon, 2006)","plainTextFormattedCitation":"(Galon, 2006)","previouslyFormattedCitation":"(Galon, 2006)"},"properties":{"noteIndex":0},"schema":""}(Galon, 2006). This response is mediated primarily by CD8+ cytotoxic T lymphocytes (CTLs). Because CTLs in tumors are chronically activated, they can become “exhausted,” a hyporesponsive state that, in the setting of infection, prevents inflammatory damage to healthy tissue ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.2035","ISBN":"1529-2916 (Electronic)\\n1529-2908 (Linking)","ISSN":"1529-2908","PMID":"21739672","abstract":"T cell exhaustion is a state of T cell dysfunction that arises during many chronic infections and cancer. It is defined by poor effector function, sustained expression of inhibitory receptors and a transcriptional state distinct from that of functional effector or memory T cells. Exhaustion prevents optimal control of infection and tumors. Recently, a clearer picture of the functional and phenotypic profile of exhausted T cells has emerged and T cell exhaustion has been defined in many experimental and clinical settings. Although the pathways involved remain to be fully defined, advances in the molecular delineation of T cell exhaustion are clarifying the underlying causes of this state of differentiation and also suggest promising therapeutic opportunities.","author":[{"dropping-particle":"","family":"Wherry","given":"E John","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature immunology","id":"ITEM-1","issue":"6","issued":{"date-parts":[["2011"]]},"page":"492-499","publisher":"Nature Publishing Group","title":"T cell exhaustion.","type":"article-journal","volume":"12"},"uris":[""]}],"mendeley":{"formattedCitation":"(Wherry, 2011)","plainTextFormattedCitation":"(Wherry, 2011)","previouslyFormattedCitation":"(Wherry, 2011)"},"properties":{"noteIndex":0},"schema":""}(Wherry, 2011). Exhaustion involves up-regulation of surface molecules such as PD-1 and TIM-3, alongside a gradual diminution of functional and proliferative potential ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nrc3239","ISBN":"1474-1768 (Electronic)\\r1474-175X (Linking)","ISSN":"1474-1768","PMID":"22437870","abstract":"Among the most promising approaches to activating therapeutic antitumour immunity is the blockade of immune checkpoints. Immune checkpoints refer to a plethora of inhibitory pathways hardwired into the immune system that are crucial for maintaining self-tolerance and modulating the duration and amplitude of physiological immune responses in peripheral tissues in order to minimize collateral tissue damage. It is now clear that tumours co-opt certain immune-checkpoint pathways as a major mechanism of immune resistance, particularly against T cells that are specific for tumour antigens. Because many of the immune checkpoints are initiated by ligand-receptor interactions, they can be readily blocked by antibodies or modulated by recombinant forms of ligands or receptors. Cytotoxic T-lymphocyte-associated antigen 4 (CTLA4) antibodies were the first of this class of immunotherapeutics to achieve US Food and Drug Administration (FDA) approval. Preliminary clinical findings with blockers of additional immune-checkpoint proteins, such as programmed cell death protein 1 (PD1), indicate broad and diverse opportunities to enhance antitumour immunity with the potential to produce durable clinical responses.","author":[{"dropping-particle":"","family":"Pardoll","given":"Drew M.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature reviews. Cancer","id":"ITEM-1","issue":"4","issued":{"date-parts":[["2012","4","1"]]},"page":"252-264","publisher":"Nature Publishing Group","title":"The blockade of immune checkpoints in cancer immunotherapy.","type":"article-journal","volume":"12"},"uris":[""]}],"mendeley":{"formattedCitation":"(Pardoll, 2012)","plainTextFormattedCitation":"(Pardoll, 2012)","previouslyFormattedCitation":"(Pardoll, 2012)"},"properties":{"noteIndex":0},"schema":""}(Pardoll, 2012). Anti-PD-1 therapies have revolutionized cancer treatment by inducing durable responses in some patients ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1056/NEJMoa1503093","ISBN":"1533-4406 (Electronic)\\r0028-4793 (Linking)","ISSN":"0028-4793","PMID":"25891173","abstract":"BackgroundThe immune checkpoint inhibitor ipilimumab is the standard-of-care treatment for patients with advanced melanoma. Pembrolizumab inhibits the programmed cell death 1 (PD-1) immune checkpoint and has antitumor activity in patients with advanced melanoma. MethodsIn this randomized, controlled, phase 3 study, we assigned 834 patients with advanced melanoma in a 1:1:1 ratio to receive pembrolizumab (at a dose of 10 mg per kilogram of body weight) every 2 weeks or every 3 weeks or four doses of ipilimumab (at 3 mg per kilogram) every 3 weeks. Primary end points were progression-free and overall survival. ResultsThe estimated 6-month progression-free-survival rates were 47.3% for pembrolizumab every 2 weeks, 46.4% for pembrolizumab every 3 weeks, and 26.5% for ipilimumab (hazard ratio for disease progression, 0.58; P<0.001 for both pembrolizumab regimens versus ipilimumab; 95% confidence intervals [CIs], 0.46 to 0.72 and 0.47 to 0.72, respectively). Estimated 12-month survival rates were 74.1%, 68.4%, ...","author":[{"dropping-particle":"","family":"Robert","given":"Caroline","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schachter","given":"Jacob","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V.","family":"Long","given":"Georgina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Arance","given":"Ana","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Grob","given":"Jean Jacques","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mortier","given":"Laurent","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Daud","given":"Adil","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Carlino","given":"Matteo S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"McNeil","given":"Catriona","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lotem","given":"Michal","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Larkin","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lorigan","given":"Paul","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Neyns","given":"Bart","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Blank","given":"Christian U.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hamid","given":"Omid","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mateus","given":"Christine","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Shapira-Frommer","given":"Ronnie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kosh","given":"Michele","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhou","given":"Honghong","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ibrahim","given":"Nageatte","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ebbinghaus","given":"Scot","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ribas","given":"Antoni","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"New England Journal of Medicine","id":"ITEM-1","issue":"26","issued":{"date-parts":[["2015","4","19"]]},"page":"2521-2532","title":"Pembrolizumab versus Ipilimumab in Advanced Melanoma","type":"article-journal","volume":"372"},"uris":[""]}],"mendeley":{"formattedCitation":"(Robert et al., 2015)","plainTextFormattedCitation":"(Robert et al., 2015)","previouslyFormattedCitation":"(Robert et al., 2015)"},"properties":{"noteIndex":0},"schema":""}(Robert et al., 2015). Given the association of PD-1 with exhaustion and the description of CTLs expressing PD-1 in human cancers, “exhausted” CTLs are generally assumed to be the cells reactivated by anti-PD-1 therapy, though definitive evidence for this is lacking in humans ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1080/2162402X.2017.1364828","ISSN":"2162-402X","PMID":"29296515","abstract":"Inhibitory properties of PD-1 receptor engagement on activated T cells are well established in physiologic and pathological contexts. In cancer, the use of checkpoint blockade, such as anti-PD-1 antibodies, becomes progressively a reference treatment of a growing number of tumors. Nonetheless, it is also established that PD-1 expression on antigen-specific T cells reflects the functional avidity and anti-tumor reactivity of these T cells. We will discuss this dual significance of PD-1 expression on tumor-specific T cells, due to a complex regulation and the opportunity to exploit this expression to define, monitor and exploit tumor-reactive T cells for immunotherapy purposes.","author":[{"dropping-particle":"","family":"Simon","given":"Sylvain","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Labarriere","given":"Nathalie","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"OncoImmunology","id":"ITEM-1","issue":"1","issued":{"date-parts":[["2018","1","2"]]},"page":"e1364828","publisher":"Taylor & Francis","title":"PD-1 expression on tumor-specific T cells: Friend or foe for immunotherapy?","type":"article-journal","volume":"7"},"uris":[""]}],"mendeley":{"formattedCitation":"(Simon and Labarriere, 2018)","plainTextFormattedCitation":"(Simon and Labarriere, 2018)","previouslyFormattedCitation":"(Simon and Labarriere, 2018)"},"properties":{"noteIndex":0},"schema":""}(Simon and Labarriere, 2018).Though anti-PD-1 therapies can eradicate tumors in some patients, they also lead to serious “off-target” immune-mediated adverse reactions ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nm.4321","ISBN":"1520-6890 (Electronic) 0009-2665 (Linking)","ISSN":"1078-8956","PMID":"28475571","abstract":"In this Perspective, June, Bluestone and Warshauer discuss potential cellular and molecular explanations for the autoimmunity often associated with immunotherapy, and propose additional research and changes to reporting practices to aid efforts to understand and minimize these toxic side effects.","author":[{"dropping-particle":"","family":"June","given":"Carl H","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Warshauer","given":"Jeremy T","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bluestone","given":"Jeffrey A","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Medicine","id":"ITEM-1","issue":"5","issued":{"date-parts":[["2017","5","5"]]},"page":"540-547","publisher":"Nature Publishing Group","title":"Is autoimmunity the Achilles' heel of cancer immunotherapy?","type":"article-journal","volume":"23"},"uris":[""]}],"mendeley":{"formattedCitation":"(June et al., 2017)","plainTextFormattedCitation":"(June et al., 2017)","previouslyFormattedCitation":"(June et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(June et al., 2017), calling for research to identify features unique to tumor-reactive CTLs. One subset of CTLs that may harbor such distinctive properties are tissue-resident memory T cells (TRM) which mediate the response to anti-tumor vaccines ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ncomms15221","ISBN":"1078-0432 (Electronic)\\r1078-0432 (Linking)","ISSN":"2041-1723","PMID":"28537262","abstract":"Resident memory T cells (Trm) are memory T cells that remain in tissue. Here, the authors show that induction of Trm cells is required for control of tumour growth following mucosal vaccination in mice bearing head and neck cancer and that Trm cells in human lung cancer correlates with a better survival.","author":[{"dropping-particle":"","family":"Nizard","given":"Mevyn","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Roussel","given":"Hélène","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Diniz","given":"Mariana O","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Karaki","given":"Soumaya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tran","given":"Thi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Voron","given":"Thibault","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Dransart","given":"Estelle","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sandoval","given":"Federico","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Riquet","given":"Marc","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Rance","given":"Bastien","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Marcheteau","given":"Elie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Fabre","given":"Elizabeth","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mandavit","given":"Marion","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Terme","given":"Magali","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Blanc","given":"Charlotte","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Escudie","given":"Jean-Baptiste","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gibault","given":"Laure","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Barthes","given":"Fran?oise Le Pimpec","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Granier","given":"Clemence","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ferreira","given":"Luis C. 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We report that skin-resident memory T cell responses to melanoma are generated naturally as a result of autoimmune vitiligo. Melanoma antigen-specific TRMcells resided predominantly in melanocyte-depleted hair follicles and were maintained without recirculation or replenishment from the lymphoid compartment. These cells expressed CD103, CD69, and CLA (cutaneous lymphocyte antigen), but lacked PD-1 (programmed cell death protein-1) or LAG-3 (lymphocyte activation gene-3), and were capable of making IFN-γ (interferon-γ). CD103 expression on CD8 T cells was required for the establishment of TRMcells in the skin but was dispensable for vitiligo development. CD103+CD8 TRMcells were critical for protection against melanoma rechallenge. This work establishes that CD103-dependent TRMcells play a key role in perpetuating antitumor immunity.","author":[{"dropping-particle":"","family":"Malik","given":"Brian T.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Byrne","given":"Katelyn T.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vella","given":"Jennifer L.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Peisheng","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Shabaneh","given":"Tamer B.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Steinberg","given":"Shannon M.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Molodtsov","given":"Aleksey K.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bowers","given":"Jacob S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V.","family":"Angeles","given":"Christina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Paulos","given":"Chrystal M.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Huang","given":"Yina H.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Turk","given":"Mary Jo","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science immunology","id":"ITEM-1","issue":"10","issued":{"date-parts":[["2017","4","14"]]},"page":"6346","title":"Resident memory T cells in the skin mediate durable immunity to melanoma.","type":"article-journal","volume":"2"},"uris":[""]}],"mendeley":{"formattedCitation":"(Malik et al., 2017)","plainTextFormattedCitation":"(Malik et al., 2017)","previouslyFormattedCitation":"(Malik et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Malik et al., 2017). TRM responses have also recently been shown by our group ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3775","ISSN":"1529-2908","PMID":"28628092","abstract":"Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.","author":[{"dropping-particle":"","family":"Ganesan","given":"Anusha-Preethi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garrido-Martin","given":"Eva M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alzetani","given":"Aiman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friedmann","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2017","6","19"]]},"page":"940-950","title":"Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer","type":"article-journal","volume":"18"},"uris":[""]}],"mendeley":{"formattedCitation":"(Ganesan et al., 2017)","plainTextFormattedCitation":"(Ganesan et al., 2017)","previouslyFormattedCitation":"(Ganesan et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Ganesan et al., 2017) and others ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.4049/jimmunol.1402711","ISBN":"1550-6606 (Electronic)\\r0022-1767 (Linking)","ISSN":"0022-1767","PMID":"25725111","abstract":"We had previously demonstrated the role of CD103 integrin on lung tumor-infiltrating lymphocyte (TIL) clones in promoting specific TCR-mediated epithelial tumor cell cytotoxicity. However, the contribution of CD103 on intratumoral T cell distribution and functions and the prognosis significance of TIL subpopulations in non-small cell lung carcinoma (NSCLC) have thus far not been systematically addressed. In this study, we show that an enhanced CD103(+) TIL subset correlates with improved early stage NSCLC patient survival and increased intraepithelial lymphocyte infiltration. Moreover, our results indicate that CD8(+)CD103(+) TIL, freshly isolated from NSCLC specimens, display transcriptomic and phenotypic signatures characteristic of tissue-resident memory T cells and frequently express PD-1 and Tim-3 checkpoint receptors. This TIL subset also displays increased activation-induced cell death and mediates specific cytolytic activity toward autologous tumor cells upon blockade of the PD-1-PD-L1 interaction. These findings emphasize the role of CD8(+)CD103(+) tissue-resident memory T cells in promoting intratumoral CTL responses and support the rationale for using anti-PD-1 blocking Ab to reverse tumor-induced T cell exhaustion in NSCLC patients.","author":[{"dropping-particle":"","family":"Djenidi","given":"Fay?al","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Adam","given":"Julien","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Goubar","given":"A?cha","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Durgeau","given":"Aurélie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Meurice","given":"Guillaume","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Montpréville","given":"Vincent","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Validire","given":"Pierre","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Besse","given":"Benjamin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mami-Chouaib","given":"Fathia","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"The Journal of Immunology","id":"ITEM-1","issue":"7","issued":{"date-parts":[["2015","4","1"]]},"page":"3475-3486","title":"CD8 + CD103 + Tumor–Infiltrating Lymphocytes Are Tumor-Specific Tissue-Resident Memory T Cells and a Prognostic Factor for Survival in Lung Cancer Patients","type":"article-journal","volume":"194"},"uris":[""]}],"mendeley":{"formattedCitation":"(Djenidi et al., 2015)","plainTextFormattedCitation":"(Djenidi et al., 2015)","previouslyFormattedCitation":"(Djenidi et al., 2015)"},"properties":{"noteIndex":0},"schema":""}(Djenidi et al., 2015) to be associated with better survival in patients with solid tumors. The molecular features of TRM cells’ responses have been characterized in infection models, and involve rapid clonal expansion and upregulation of molecules aiding recruitment and activation of additional immune cells alongside the conventional effector functions of CTLs ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.immuni.2014.12.007","ISSN":"1097-4180","PMID":"25526304","abstract":"Tissue-resident memory T (Trm) cells constitute a recently identified lymphocyte lineage that occupies tissues without recirculating. They provide a first response against infections reencountered at body surfaces, where they accelerate pathogen clearance. Because Trm cells are not present within peripheral blood, they have not yet been well characterized, but are transcriptionally, phenotypically, and functionally distinct from recirculating central and effector memory T cells. In this review, we will summarize current knowledge of Trm cell ontogeny, regulation, maintenance, and function and will highlight technical considerations for studying this population.","author":[{"dropping-particle":"","family":"Schenkel","given":"Jason M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Masopust","given":"David","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Immunity","id":"ITEM-1","issue":"6","issued":{"date-parts":[["2014","12","18"]]},"page":"886-97","title":"Tissue-resident memory T cells.","type":"article-journal","volume":"41"},"uris":[""]}],"mendeley":{"formattedCitation":"(Schenkel and Masopust, 2014)","plainTextFormattedCitation":"(Schenkel and Masopust, 2014)","previouslyFormattedCitation":"(Schenkel and Masopust, 2014)"},"properties":{"noteIndex":0},"schema":""}(Schenkel and Masopust, 2014). To date, the properties of TRM cells found in the background lung, compared to those in the tumor are not fully elucidated. Furthermore, the properties of these cell subsets in the context of immunotherapy are still poorly understood. To address this question, we compared the transcriptome of TRM and non-TRM CTLs present in tumor and normal lung tissue samples from treatment na?ve patients with lung cancer. Furthermore, we investigated the same tissue-resident populations in head and neck squamous cell carcinoma and during immunotherapy regimes. RESULTSTRM cells in human lungs are transcriptionally distinct from previously characterized TRM cellsWe analyzed the transcriptome of CTLs isolated from lung tumor and adjacent uninvolved lung tissue samples obtained from patients (n = 30) with treatment-na?ve lung cancer (Table S1), sorted according to CD103 expression to separate TRM from non-TRM cells, as previously described ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3775","ISSN":"1529-2908","PMID":"28628092","abstract":"Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.","author":[{"dropping-particle":"","family":"Ganesan","given":"Anusha-Preethi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garrido-Martin","given":"Eva M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alzetani","given":"Aiman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friedmann","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2017","6","19"]]},"page":"940-950","title":"Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer","type":"article-journal","volume":"18"},"uris":[""]}],"mendeley":{"formattedCitation":"(Ganesan et al., 2017)","plainTextFormattedCitation":"(Ganesan et al., 2017)","previouslyFormattedCitation":"(Ganesan et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Ganesan et al., 2017). Lung CD103+ and CD103– CTLs clustered separately and showed differential expression of nearly 700 transcripts including several previously linked to TRM phenotypes; we validated CD49A and KLRG1 at the protein level, as described previously (Figs. 1 A, S1 A-C and Table S2) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3589","ISBN":"1529-2916 (Electronic)\n1529-2908 (Linking)","ISSN":"15292916","PMID":"28102212","abstract":"Tissue-resident memory T cells (TRM cells) in the airways mediate protection against respiratory infection. We characterized TRM cells expressing integrin [alpha]E (CD103) that reside within the epithelial barrier of human lungs. These cells had specialized profiles of chemokine receptors and adhesion molecules, consistent with their unique localization. Lung TRM cells were poised for rapid responsiveness by constitutive expression of deployment-ready mRNA encoding effector molecules, but they also expressed many inhibitory regulators, suggestive of programmed restraint. A distinct set of transcription factors was active in CD103+ TRM cells, including Notch. Genetic and pharmacological experiments with mice revealed that Notch activity was required for the maintenance of CD103+ TRM cells. We have thus identified specialized programs underlying the residence, persistence, vigilance and tight control of human lung TRM cells.","author":[{"dropping-particle":"","family":"Hombrink","given":"Pleun","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Helbig","given":"Christina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Backer","given":"Ronald A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Piet","given":"Berber","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Oja","given":"Anna E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Stark","given":"Regina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Brasser","given":"Giso","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jongejan","given":"Aldo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jonkers","given":"René E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nota","given":"Benjamin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Basak","given":"Onur","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clevers","given":"Hans C.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Moerland","given":"Perry D.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Amsen","given":"Derk","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lier","given":"René A.W.","non-dropping-particle":"Van","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"12","issued":{"date-parts":[["2016","10","24"]]},"page":"1467-1478","publisher":"Nature Research","title":"Programs for the persistence, vigilance and control of human CD8 + lung-resident memory T cells","type":"article-journal","volume":"17"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1038/ni.3775","ISSN":"1529-2908","PMID":"28628092","abstract":"Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.","author":[{"dropping-particle":"","family":"Ganesan","given":"Anusha-Preethi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garrido-Martin","given":"Eva M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alzetani","given":"Aiman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friedmann","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-2","issue":"8","issued":{"date-parts":[["2017","6","19"]]},"page":"940-950","title":"Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer","type":"article-journal","volume":"18"},"uris":[""]}],"mendeley":{"formattedCitation":"(Hombrink et al., 2016; Ganesan et al., 2017)","plainTextFormattedCitation":"(Hombrink et al., 2016; Ganesan et al., 2017)","previouslyFormattedCitation":"(Hombrink et al., 2016; Ganesan et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Hombrink et al., 2016; Ganesan et al., 2017). Gene set enrichment analysis (GSEA) showed that the pattern of expression of these transcripts correlated with a murine core tissue residency signature in CTLs isolated from both lung and tumor samples (Fig. S2 D and Table S3) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nature24993","ISSN":"0028-0836","author":[{"dropping-particle":"","family":"Milner","given":"J Justin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Toma","given":"Clara","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yu","given":"Bingfei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Kai","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Omilusik","given":"Kyla","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Phan","given":"Anthony T","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wang","given":"Dapeng","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Getzler","given":"Adam J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nguyen","given":"Toan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Crotty","given":"Shane","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wang","given":"Wei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pipkin","given":"Matthew E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Goldrath","given":"Ananda W.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature","id":"ITEM-1","issued":{"date-parts":[["2017","12","6"]]},"page":"253–257","publisher":"Nature Publishing Group","title":"Runx3 programs CD8+ T cell residency in non-lymphoid tissues and tumours","type":"article-journal","volume":"552"},"uris":[""]}],"mendeley":{"formattedCitation":"(Milner et al., 2017)","plainTextFormattedCitation":"(Milner et al., 2017)","previouslyFormattedCitation":"(Milner et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Milner et al., 2017). Together, these data confirm that CD103+ CTLs in human lungs and tumors are highly enriched for TRM cells; for simplicity, hereafter we refer to CD103+ CTLs as TRM cells and CD103– CTLs as non-TRM cells. We next compared differentially expressed transcripts between lung TRM and non-TRM with those reported for other TRM cells. The comparison with gene signatures of human skin TRM cells ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.immuni.2017.01.009","ISSN":"1097-4180","PMID":"28214226","abstract":"Tissue-resident memory T (Trm) cells form a heterogeneous population that provides localized protection against pathogens. Here, we identify CD49a as a marker that differentiates CD8(+) Trm cells on a compartmental and functional basis. In human skin epithelia, CD8(+)CD49a(+) Trm cells produced interferon-γ, whereas CD8(+)CD49a(-) Trm cells produced interleukin-17 (IL-17). In addition, CD8(+)CD49a(+) Trm cells from healthy skin rapidly induced the expression of the effector molecules perforin and granzyme B when stimulated with IL-15, thereby promoting a strong cytotoxic response. In skin from patients with vitiligo, where melanocytes are eradicated locally, CD8(+)CD49a(+) Trm cells that constitutively expressed perforin and granzyme B accumulated both in the epidermis and dermis. Conversely, CD8(+)CD49a(-) Trm cells from psoriasis lesions predominantly generated IL-17 responses that promote local inflammation in this skin disease. Overall, CD49a expression delineates CD8(+) Trm cell specialization in human epithelial barriers and correlates with the effector cell balance found in distinct inflammatory skin diseases.","author":[{"dropping-particle":"","family":"Cheuk","given":"Stanley","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schlums","given":"Heinrich","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gallais Sérézal","given":"Irène","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Martini","given":"Elisa","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chiang","given":"Samuel C.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Marquardt","given":"Nicole","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gibbs","given":"Anna","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Detlofsson","given":"Ebba","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Introini","given":"Andrea","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Forkel","given":"Marianne","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"H??g","given":"Charlotte","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tjernlund","given":"Annelie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Micha?lsson","given":"Jakob","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Folkersen","given":"Lasse","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mj?sberg","given":"Jenny","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Blomqvist","given":"Lennart","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ehrstr?m","given":"Marcus","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"St?hle","given":"Mona","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bryceson","given":"Yenan T.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Eidsmo","given":"Liv","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Immunity","id":"ITEM-1","issue":"2","issued":{"date-parts":[["2017","2","21"]]},"page":"287-300","title":"CD49a Expression Defines Tissue-Resident CD8(+) T Cells Poised for Cytotoxic Function in Human Skin.","type":"article-journal","volume":"46"},"uris":[""]}],"mendeley":{"formattedCitation":"(Cheuk et al., 2017)","plainTextFormattedCitation":"(Cheuk et al., 2017)","previouslyFormattedCitation":"(Cheuk et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Cheuk et al., 2017) and that of murine TRM cells isolated from multiple organs ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nature24993","ISSN":"0028-0836","author":[{"dropping-particle":"","family":"Milner","given":"J Justin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Toma","given":"Clara","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yu","given":"Bingfei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Kai","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Omilusik","given":"Kyla","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Phan","given":"Anthony T","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wang","given":"Dapeng","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Getzler","given":"Adam J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nguyen","given":"Toan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Crotty","given":"Shane","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wang","given":"Wei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pipkin","given":"Matthew E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Goldrath","given":"Ananda W.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature","id":"ITEM-1","issued":{"date-parts":[["2017","12","6"]]},"page":"253–257","publisher":"Nature Publishing Group","title":"Runx3 programs CD8+ T cell residency in non-lymphoid tissues and tumours","type":"article-journal","volume":"552"},"uris":[""]}],"mendeley":{"formattedCitation":"(Milner et al., 2017)","plainTextFormattedCitation":"(Milner et al., 2017)","previouslyFormattedCitation":"(Milner et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Milner et al., 2017) revealed only limited overlap (≤ 5%, Fig. 1 B and C), though statistically significant, which suggested that core tissue-residency features were well preserved. However, those differentially expressed transcripts that were not preserved across organs, or species, were not significantly enriched (Fig. S1 E). Thus, the transcriptional program, outside of a core tissue residency program of human lung TRM cells is distinct from that of human skin TRM cells and murine TRM cells present in several organs Importantly, many of the features observed in human lung TRM cells have not been previously reported (Table S2) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3589","ISBN":"1529-2916 (Electronic)\n1529-2908 (Linking)","ISSN":"15292916","PMID":"28102212","abstract":"Tissue-resident memory T cells (TRM cells) in the airways mediate protection against respiratory infection. We characterized TRM cells expressing integrin [alpha]E (CD103) that reside within the epithelial barrier of human lungs. These cells had specialized profiles of chemokine receptors and adhesion molecules, consistent with their unique localization. Lung TRM cells were poised for rapid responsiveness by constitutive expression of deployment-ready mRNA encoding effector molecules, but they also expressed many inhibitory regulators, suggestive of programmed restraint. A distinct set of transcription factors was active in CD103+ TRM cells, including Notch. Genetic and pharmacological experiments with mice revealed that Notch activity was required for the maintenance of CD103+ TRM cells. We have thus identified specialized programs underlying the residence, persistence, vigilance and tight control of human lung TRM cells.","author":[{"dropping-particle":"","family":"Hombrink","given":"Pleun","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Helbig","given":"Christina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Backer","given":"Ronald A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Piet","given":"Berber","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Oja","given":"Anna E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Stark","given":"Regina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Brasser","given":"Giso","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jongejan","given":"Aldo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jonkers","given":"René E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nota","given":"Benjamin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Basak","given":"Onur","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clevers","given":"Hans C.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Moerland","given":"Perry D.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Amsen","given":"Derk","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lier","given":"René A.W.","non-dropping-particle":"Van","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"12","issued":{"date-parts":[["2016","10","24"]]},"page":"1467-1478","publisher":"Nature Research","title":"Programs for the persistence, vigilance and control of human CD8 + lung-resident memory T cells","type":"article-journal","volume":"17"},"uris":[""]}],"mendeley":{"formattedCitation":"(Hombrink et al., 2016)","plainTextFormattedCitation":"(Hombrink et al., 2016)","previouslyFormattedCitation":"(Hombrink et al., 2016)"},"properties":{"noteIndex":0},"schema":""}(Hombrink et al., 2016). PD-1 expression is a feature of lung and tumor TRM cellsWe next asked if TRM cells in lung tumors share tissue residency features (Methods) with TRM cells in adjacent normal lung tissue. Nearly one-third (89/306) of the TRM properties, i.e., transcripts differentially expressed between CD103+ and CD103– CTLs in tumors were shared with those of normal lung TRM cells (Fig. 1 D,E and Table S4). Co-expression analysis (Fig. 1 F) and weighted?gene co-expression network?analysis?(WGCNA) (Fig. 1 G) (Methods) of the 89 ‘shared tissue residency’ transcripts revealed a number of novel genes whose expression was highly correlated with known tissue residency genes (S1PR1, S1PR5, ITGA1 (CD49A), ZNF693 (HOBIT), RBPJ) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3589","ISBN":"1529-2916 (Electronic)\n1529-2908 (Linking)","ISSN":"15292916","PMID":"28102212","abstract":"Tissue-resident memory T cells (TRM cells) in the airways mediate protection against respiratory infection. We characterized TRM cells expressing integrin [alpha]E (CD103) that reside within the epithelial barrier of human lungs. These cells had specialized profiles of chemokine receptors and adhesion molecules, consistent with their unique localization. Lung TRM cells were poised for rapid responsiveness by constitutive expression of deployment-ready mRNA encoding effector molecules, but they also expressed many inhibitory regulators, suggestive of programmed restraint. A distinct set of transcription factors was active in CD103+ TRM cells, including Notch. Genetic and pharmacological experiments with mice revealed that Notch activity was required for the maintenance of CD103+ TRM cells. We have thus identified specialized programs underlying the residence, persistence, vigilance and tight control of human lung TRM cells.","author":[{"dropping-particle":"","family":"Hombrink","given":"Pleun","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Helbig","given":"Christina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Backer","given":"Ronald A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Piet","given":"Berber","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Oja","given":"Anna E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Stark","given":"Regina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Brasser","given":"Giso","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jongejan","given":"Aldo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jonkers","given":"René E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nota","given":"Benjamin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Basak","given":"Onur","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clevers","given":"Hans C.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Moerland","given":"Perry D.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Amsen","given":"Derk","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lier","given":"René A.W.","non-dropping-particle":"Van","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"12","issued":{"date-parts":[["2016","10","24"]]},"page":"1467-1478","publisher":"Nature Research","title":"Programs for the persistence, vigilance and control of human CD8 + lung-resident memory T cells","type":"article-journal","volume":"17"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1038/ni.2744","ISBN":"1529-2916 (Electronic)\\r1529-2908 (Linking)","ISSN":"1529-2908","PMID":"24162776","abstract":"Tissue-resident memory T cells (T(RM) cells) provide superior protection against infection in extralymphoid tissues. Here we found that CD103(+)CD8(+) T(RM) cells developed in the skin from epithelium-infiltrating precursor cells that lacked expression of the effector-cell marker KLRG1. A combination of entry into the epithelium plus local signaling by interleukin 15 (IL-15) and transforming growth factor-β (TGF-β) was required for the formation of these long-lived memory cells. Notably, differentiation into T(RM) cells resulted in the progressive acquisition of a unique transcriptional profile that differed from that of circulating memory cells and other types of T cells that permanently reside in skin epithelium. We provide a comprehensive molecular framework for the local differentiation of a distinct peripheral population of memory cells that forms a first-line immunological defense system in barrier tissues.","author":[{"dropping-particle":"","family":"Mackay","given":"Laura K","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Rahimpour","given":"Azad","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ma","given":"Joel Z","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Collins","given":"Nicholas","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Stock","given":"Angus T","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hafon","given":"Ming-Li","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vega-Ramos","given":"Javier","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lauzurica","given":"Pilar","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mueller","given":"Scott N","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Stefanovic","given":"Tijana","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tscharke","given":"David C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Heath","given":"William R","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Inouye","given":"Michael","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Carbone","given":"Francis R","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gebhardt","given":"Thomas","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature immunology","id":"ITEM-2","issue":"12","issued":{"date-parts":[["2013","10","27"]]},"page":"1294-1301","publisher":"Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.","title":"The developmental pathway for CD103+CD8+ tissue-resident memory T cells of skin","title-short":"Nat Immunol","type":"article-journal","volume":"14"},"uris":[""]},{"id":"ITEM-3","itemData":{"DOI":"10.1126/science.aad2035","ISSN":"0036-8075","PMID":"27102484","abstract":"Tissue-resident memory T (Trm) cells permanently localize to portals of pathogen entry, where they provide immediate protection against reinfection. To enforce tissue retention, Trm cells up-regulate CD69 and down-regulate molecules associated with tissue egress; however, a Trm-specific transcriptional regulator has not been identified. Here, we show that the transcription factor Hobit is specifically up-regulated in Trm cells and, together with related Blimp1, mediates the development of Trm cells in skin, gut, liver, and kidney in mice. The Hobit-Blimp1 transcriptional module is also required for other populations of tissue-resident lymphocytes, including natural killer T (NKT) cells and liver-resident NK cells, all of which share a common transcriptional program. Our results identify Hobit and Blimp1 as central regulators of this universal program that instructs tissue retention in diverse tissue-resident lymphocyte populations.","author":[{"dropping-particle":"","family":"Mackay","given":"L. K.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Minnich","given":"M.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kragten","given":"N. A. 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Notable examples encoding products likely to be involved in TRM functionality, migration or retention include GPR25 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/science.1237013","ISSN":"0036-8075","PMID":"23661644","abstract":"Lymphocyte homing, which contributes to inflammation, has been studied extensively in the small intestine, but there is little known about homing to the large intestine, the site most commonly affected in inflammatory bowel disease. GPR15, an orphan heterotrimeric guanine nucleotide-binding protein (G protein)-coupled receptor, controlled the specific homing of T cells, particularly FOXP3(+) regulatory T cells (Tregs), to the large intestine lamina propria (LILP). GPR15 expression was modulated by gut microbiota and transforming growth factor-β1, but not by retinoic acid. GPR15-deficient mice were prone to develop more severe large intestine inflammation, which was rescued by the transfer of GPR15-sufficient Tregs. Our findings thus describe a T cell-homing receptor for LILP and indicate that GPR15 plays a role in mucosal immune tolerance largely by regulating the influx of Tregs.","author":[{"dropping-particle":"V.","family":"Kim","given":"S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V.","family":"Xiang","given":"W.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kwak","given":"C.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yang","given":"Y.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lin","given":"X. 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SrGAP3-mediated reorganisation of the actin cytoskeleton is crucial for the normal development of dendritic spines and loss of srGAP3 leads to abnormal synaptic activity and impaired cognitive behaviours in mice, which is reminiscent of an association between disrupted srGAP3 and intellectual disability in humans. Additionally, srGAP3 has been implicated to act downstream of Slit-Robo signalling in commissural axons of the spinal cord. Thus, srGAP3-mediated cytoskeletal reorganisation has an important influence on a variety of neurodevelopmental processes, which may be required for normal cognitive function. ?2012 Elsevier Ireland Ltd.","author":[{"dropping-particle":"","family":"Bacon","given":"Claire","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Endris","given":"Volker","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Rappold","given":"Gudrun A.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Mechanisms of Development","id":"ITEM-1","issue":"6","issued":{"date-parts":[["2013","6","1"]]},"page":"391-395","publisher":"Elsevier","title":"The cellular function of srGAP3 and its role in neuronal morphogenesis","type":"article-journal","volume":"130"},"uris":[""]}],"mendeley":{"formattedCitation":"(Bacon et al., 2013)","plainTextFormattedCitation":"(Bacon et al., 2013)","previouslyFormattedCitation":"(Bacon et al., 2013)"},"properties":{"noteIndex":0},"schema":""}(Bacon et al., 2013), AMICA1 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/science.1192698","ISBN":"2007353191810","ISSN":"10959203","PMID":"23287718","abstract":"γδ T cells present in epithelial tissues provide a crucial first line of defense against environmental insults, including infection, trauma, and malignancy, yet the molecular events surrounding their activation remain poorly defined. Here we identify an epithelial γδ T cell–specific costimulatory molecule, junctional adhesion molecule–like protein (JAML). Binding of JAML to its ligand Coxsackie and adenovirus receptor (CAR) provides costimulation leading to cellular proliferation and cytokine and growth factor production. Inhibition of JAML costimulation leads to diminished γδ T cell activation and delayed wound closure akin to that seen in the absence of γδ T cells. Our results identify JAML as a crucial component of epithelial γδ T cell biology and have broader implications for CAR and JAML in tissue homeostasis and repair.","author":[{"dropping-particle":"","family":"Witherden","given":"Deborah A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Verdino","given":"Petra","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Rieder","given":"Stephanie E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garijo","given":"Olivia","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mills","given":"Robyn E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Teyton","given":"Luc","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Fischer","given":"Wolfgang H.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wilson","given":"Ian A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Havran","given":"Wendy L.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science","id":"ITEM-1","issue":"5996","issued":{"date-parts":[["2010","9","3"]]},"page":"1205-1210","title":"The junctional adhesion molecule JAML is a costimulatory receptor for epithelial γδ T cell activation","type":"article-journal","volume":"329"},"uris":[""]}],"mendeley":{"formattedCitation":"(Witherden et al., 2010)","plainTextFormattedCitation":"(Witherden et al., 2010)","previouslyFormattedCitation":"(Witherden et al., 2010)"},"properties":{"noteIndex":0},"schema":""}(Witherden et al., 2010), CAPG ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1128/IAI.71.11.6582-6590.2003","ISBN":"0019-9567 (Print)\\r0019-9567 (Linking)","ISSN":"00199567","PMID":"14573680","abstract":"Loss of the actin filament capping protein CapG has no apparent effect on the phenotype of mice maintained under sterile conditions; however, bone marrow-derived macrophages from CapG(-/-) mice exhibited distinct motility defects. We examined the ability of CapG(-/-) mice to clear two intracellular bacteria, Listeria monocytogenes and Salmonella enterica serovar Typhimurium. The 50% lethal dose of Listeria was 10-fold lower for CapG(-/-) mice than for CapG(+/+) mice (6 x 10(3) CFU for CapG(-/-) mice and 6 x 10(4) CFU for CapG(+/+) mice), while no difference was observed for Salmonella: The numbers of Listeria cells in the spleens and livers were significantly higher in CapG(-/-) mice than in CapG(+/+) mice at days 5 to 9, while the bacterial counts were identical on day 5 for Salmonella-infected mice. Microscopic analysis revealed qualitatively similar inflammatory responses in the spleens and livers of the two types of mice. Specific immunofluorescence staining analyzed by fluorescence-activated cell sorting revealed similar numbers of macrophages and dendritic cells in infected CapG(-/-) and CapG(+/+) spleens. However, analysis of bone marrow-derived macrophages revealed a 50% reduction in the rate of phagocytosis of Listeria in CapG(-/-) cells but a normal rate of phagocytosis of Salmonella: Stimulation of bone marrow-derived dendritic cells with granulocyte-macrophage colony-stimulating factor resulted in a reduction in the ruffling response of CapG(-/-) cells compared to the response of CapG(+/+) cells, and CapG(-/-) bone-marrowed derived neutrophils migrated at a mean speed that was nearly 50% lower than the mean speed of CapG(+/+) neutrophils. Our findings suggest that specific motility deficits in macrophages, dendritic cells, and neutrophils render CapG(-/-) mice more susceptible than CapG(+/+) mice to Listeria infection.","author":[{"dropping-particle":"","family":"Parikh","given":"Shefal S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Litherland","given":"Sally A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clare-Salzler","given":"Michael J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Li","given":"Wei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gulig","given":"Paul A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Southwick","given":"Frederick S","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Infection and Immunity","id":"ITEM-1","issue":"11","issued":{"date-parts":[["2003","11","1"]]},"page":"6582-6590","publisher":"American Society for Microbiology","title":"CapG-/- Mice Have Specific Host Defense Defects that Render Them More Susceptible than CapG+/+ Mice to Listeria monocytogenes Infection but Not to Salmonella enterica Serovar Typhimurium Infection","type":"article-journal","volume":"71"},"uris":[""]}],"mendeley":{"formattedCitation":"(Parikh et al., 2003)","plainTextFormattedCitation":"(Parikh et al., 2003)","previouslyFormattedCitation":"(Parikh et al., 2003)"},"properties":{"noteIndex":0},"schema":""}(Parikh et al., 2003), ADAM19 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1091/mbc.E05-03-0258","ISBN":"1059-1524 (Print)","ISSN":"1059-1524","PMID":"16339080","abstract":"A disintegrin and a metalloprotease (ADAM) family members have been implicated in many biological processes. Although it is recognized that recombinant ADAM disintegrin domains can interact with integrins, little is known about ADAM-integrin interactions in cellular context. Here, we tested whether ADAMs can selectively regulate integrin-mediated cell migration. ADAMs were expressed in Chinese hamster ovary cells that express defined integrins (alpha4beta1, alpha5beta1, or both), and cell migration on full-length fibronectin or on its alpha4beta1 or alpha5beta1 binding fragments was studied. We found that ADAMs inhibit integrin-mediated cell migration in patterns dictated by the integrin binding profiles of their isolated disintegrin domains. ADAM12 inhibited cell migration mediated by the alpha4beta1 but not the alpha5beta1 integrin. ADAM17 had the reciprocal effect; it inhibited alpha5beta1- but not alpha4beta1-mediated cell migration. ADAM19 and ADAM33 inhibited migration mediated by both alpha4beta1 and alpha5beta1 integrins. A point mutation in the ADAM12 disintegrin loop partially reduced the inhibitory effect of ADAM12 on cell migration on the alpha4beta1 binding fragment of fibronectin, whereas mutations that block metalloprotease activity had no effect. Our results indicate that distinct ADAMs can modulate cell migration mediated by specific integrins in a pattern dictated, at least in part, by their disintegrin domains.","author":[{"dropping-particle":"","family":"Huang","given":"Jing","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Molecular Biology of the Cell","id":"ITEM-1","issue":"10","issued":{"date-parts":[["2005","10"]]},"page":"4982-4991","publisher":"American Society for Cell Biology","title":"Selective Modulation of Integrin-mediated Cell Migration by Distinct ADAM Family Members","type":"article-journal","volume":"16"},"uris":[""]}],"mendeley":{"formattedCitation":"(Huang, 2005)","plainTextFormattedCitation":"(Huang, 2005)","previouslyFormattedCitation":"(Huang, 2005)"},"properties":{"noteIndex":0},"schema":""}(Huang, 2005), and NUAK2 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1073/pnas.1007694108","ISBN":"1091-6490 (Electronic)\\r0027-8424 (Linking)","ISSN":"0027-8424","PMID":"21460252","abstract":"The identification of genes that participate in melanomagenesis should suggest strategies for developing therapeutic modalities. We used a public array comparative genomic hybridization (CGH) database and real-time quantitative PCR (qPCR) analyses to identify the AMP kinase (AMPK)-related kinase NUAK2 as a candidate gene for melanomagenesis, and we analyzed its functions in melanoma cells. Our analyses had identified a locus at 1q32 where genomic gain is strongly associated with tumor thickness, and we used real-time qPCR analyses and regression analyses to identify NUAK2 as a candidate gene at that locus. Associations of relapse-free survival and overall survival of 92 primary melanoma patients with NUAK2 expression measured using immunohistochemistry were investigated using Kaplan-Meier curves, log rank tests, and Cox regression models. Knockdown of NUAK2 induces senescence and reduces S-phase, decreases migration, and down-regulates expression of mammalian target of rapamycin (mTOR). In vivo analysis demonstrated that knockdown of NUAK2 suppresses melanoma tumor growth in mice. Survival analysis showed that the risk of relapse is greater in acral melanoma patients with high levels of NUAK2 expression than in acral melanoma patients with low levels of NUAK2 expression (hazard ratio = 3.88; 95% confidence interval = 1.44-10.50; P = 0.0075). These data demonstrate that NUAK2 expression is significantly associated with the oncogenic features of melanoma cells and with the survival of acral melanoma patients. NUAK2 may provide a drug target to suppress melanoma progression. This study further supports the importance of NUAK2 in cancer development and tumor progression, while AMPK has antioncogenic properties.","author":[{"dropping-particle":"","family":"Namiki","given":"Takeshi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tanemura","given":"Atsushi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Valencia","given":"Julio C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Coelho","given":"Sergio G","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Passeron","given":"Thierry","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kawaguchi","given":"Masakazu","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vieira","given":"Wilfred D","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ishikawa","given":"Masashi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nishijima","given":"Wataru","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Izumo","given":"Toshiyuki","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kaneko","given":"Yasuhiko","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Katayama","given":"Ichiro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yamaguchi","given":"Yuji","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yin","given":"Lanlan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Polley","given":"Eric C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Liu","given":"Hongfang","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kawakami","given":"Yutaka","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Eishi","given":"Yoshinobu","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Takahashi","given":"Eishi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yokozeki","given":"Hiroo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hearing","given":"Vincent J","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Proceedings of the National Academy of Sciences","id":"ITEM-1","issue":"16","issued":{"date-parts":[["2011","4","19"]]},"page":"6597-6602","publisher":"National Academy of Sciences","title":"AMP kinase-related kinase NUAK2 affects tumor growth, migration, and clinical outcome of human melanoma","type":"article-journal","volume":"108"},"uris":[""]}],"mendeley":{"formattedCitation":"(Namiki et al., 2011)","plainTextFormattedCitation":"(Namiki et al., 2011)","previouslyFormattedCitation":"(Namiki et al., 2011)"},"properties":{"noteIndex":0},"schema":""}(Namiki et al., 2011) (Fig. 1 F-G and Fig. 1 H, upper panel). Another important ‘shared tissue residency’ transcript was PDCD1, encoding PD-1 (Fig. 1 H, lower panel). We confirmed at the protein level that PD-1 is expressed at higher levels in both tumor and lung TRM cells compared to non-TRM cells (Fig. 1 I). Although PD-1 expression is considered typical of exhausted T cells, as well as activated cells ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nrc3239","ISBN":"1474-1768 (Electronic)\\r1474-175X (Linking)","ISSN":"1474-1768","PMID":"22437870","abstract":"Among the most promising approaches to activating therapeutic antitumour immunity is the blockade of immune checkpoints. Immune checkpoints refer to a plethora of inhibitory pathways hardwired into the immune system that are crucial for maintaining self-tolerance and modulating the duration and amplitude of physiological immune responses in peripheral tissues in order to minimize collateral tissue damage. It is now clear that tumours co-opt certain immune-checkpoint pathways as a major mechanism of immune resistance, particularly against T cells that are specific for tumour antigens. Because many of the immune checkpoints are initiated by ligand-receptor interactions, they can be readily blocked by antibodies or modulated by recombinant forms of ligands or receptors. Cytotoxic T-lymphocyte-associated antigen 4 (CTLA4) antibodies were the first of this class of immunotherapeutics to achieve US Food and Drug Administration (FDA) approval. Preliminary clinical findings with blockers of additional immune-checkpoint proteins, such as programmed cell death protein 1 (PD1), indicate broad and diverse opportunities to enhance antitumour immunity with the potential to produce durable clinical responses.","author":[{"dropping-particle":"","family":"Pardoll","given":"Drew M.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature reviews. Cancer","id":"ITEM-1","issue":"4","issued":{"date-parts":[["2012","4","1"]]},"page":"252-264","publisher":"Nature Publishing Group","title":"The blockade of immune checkpoints in cancer immunotherapy.","type":"article-journal","volume":"12"},"uris":[""]}],"mendeley":{"formattedCitation":"(Pardoll, 2012)","plainTextFormattedCitation":"(Pardoll, 2012)","previouslyFormattedCitation":"(Pardoll, 2012)"},"properties":{"noteIndex":0},"schema":""}(Pardoll, 2012), recent reports have suggested that high PD-1 expression is a tissue residency feature of murine brain TRM cells independent of antigen stimulation ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/icb.2017.62","ISSN":"0818-9641","PMID":"28829048","author":[{"dropping-particle":"","family":"Shwetank","given":"","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Abdelsamed","given":"Hossam A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Frost","given":"Elizabeth L","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmitz","given":"Heather M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mockus","given":"Taryn E","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Youngblood","given":"Ben A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lukacher","given":"Aron E","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Immunology and Cell Biology","id":"ITEM-1","issue":"10","issued":{"date-parts":[["2017"]]},"page":"953-959","publisher":"Nature Publishing Group","title":"Maintenance of PD-1 on brain-resident memory CD8 T cells is antigen independent","type":"article-journal","volume":"95"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1186/s12974-017-0860-3","ISSN":"1742-2094","PMID":"28407741","abstract":"BACKGROUND Previous work from our laboratory has demonstrated that during acute viral brain infection, glial cells modulate antiviral T cell effector responses through the PD-1: PD-L1 pathway, thereby limiting the deleterious consequences of unrestrained neuroinflammation. Here, we evaluated the PD-1: PD-L1 pathway in development of brain-resident memory T cells (bTRM) following murine cytomegalovirus (MCMV) infection. METHODS Flow cytometric analysis of immune cells was performed at 7, 14, and 30?days post-infection (dpi) to assess the shift of brain-infiltrating CD8(+) T cell populations from short-lived effector cells (SLEC) to memory precursor effector cells (MPEC), as well as generation of bTRMs. RESULTS In wild-type (WT) animals, we observed a switch in the phenotype of brain-infiltrating CD8(+) T cell populations from KLRG1(+) CD127(-) (SLEC) to KLRG1(-) CD127(+) (MPEC) during transition from acute through chronic phases of infection. At 14 and 30 dpi, the majority of CD8(+) T cells expressed CD127, a marker of memory cells. In contrast, fewer CD8(+) T cells expressed CD127 within brains of infected, PD-L1 knockout (KO) animals. Notably, in WT mice, a large population of CD8(+) T cells was phenotyped as CD103(+) CD69(+), markers of bTRM, and differences were observed in the numbers of these cells when compared to PD-L1 KOs. Immunohistochemical studies revealed that brain-resident CD103(+) bTRM cells were localized to the parenchyma. Higher frequencies of CXCR3 were also observed among WT animals in contrast to PD-L1 KOs. CONCLUSIONS Taken together, our results indicate that bTRMs are present within the CNS following viral infection and the PD-1: PD-L1 pathway plays a role in the generation of this brain-resident population.","author":[{"dropping-particle":"","family":"Prasad","given":"Sujata","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hu","given":"Shuxian","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sheng","given":"Wen S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chauhan","given":"Priyanka","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Amar","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lokensgard","given":"James R","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Journal of neuroinflammation","id":"ITEM-2","issue":"1","issued":{"date-parts":[["2017","4","13"]]},"page":"82","publisher":"BioMed Central","title":"The PD-1: PD-L1 pathway promotes development of brain-resident memory T cells following acute viral encephalitis.","type":"article-journal","volume":"14"},"uris":[""]}],"mendeley":{"formattedCitation":"(Shwetank et al., 2017; Prasad et al., 2017)","plainTextFormattedCitation":"(Shwetank et al., 2017; Prasad et al., 2017)","previouslyFormattedCitation":"(Shwetank et al., 2017; Prasad et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Shwetank et al., 2017; Prasad et al., 2017), and of murine TRM cells from multiple organ systems ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nature24993","ISSN":"0028-0836","author":[{"dropping-particle":"","family":"Milner","given":"J Justin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Toma","given":"Clara","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yu","given":"Bingfei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Kai","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Omilusik","given":"Kyla","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Phan","given":"Anthony T","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wang","given":"Dapeng","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Getzler","given":"Adam J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nguyen","given":"Toan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Crotty","given":"Shane","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wang","given":"Wei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pipkin","given":"Matthew E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Goldrath","given":"Ananda W.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature","id":"ITEM-1","issued":{"date-parts":[["2017","12","6"]]},"page":"253–257","publisher":"Nature Publishing Group","title":"Runx3 programs CD8+ T cell residency in non-lymphoid tissues and tumours","type":"article-journal","volume":"552"},"uris":[""]}],"mendeley":{"formattedCitation":"(Milner et al., 2017)","plainTextFormattedCitation":"(Milner et al., 2017)","previouslyFormattedCitation":"(Milner et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Milner et al., 2017). In support of the conclusion that high expression of PD-1 reflects tissue residency, rather than exhaustion, we found that when TRM and non-TRM cells isolated from both lung and tumor tissue were stimulated ex-vivo (Methods), they showed robust up-regulation of TCR-activation-induced genes (NR4A1, CD69, TNFRSF9 (4-1BB), EGR2) and cytokines (TNF, IFNG) (Fig. 1 J,K, Table S1 and S5). In addition to PDCD1, ‘shared tissue-residency’ transcripts included several (SPRY1 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1371/journal.pone.0049801","ISSN":"1932-6203","author":[{"dropping-particle":"","family":"Collins","given":"Sam","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Waickman","given":"Adam","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Basson","given":"Albert","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kupfer","given":"Abraham","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Licht","given":"Jonathan D.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Horton","given":"Maureen R.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Powell","given":"Jonathan D.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"PLoS ONE","editor":[{"dropping-particle":"","family":"Teague","given":"Ryan M.","non-dropping-particle":"","parse-names":false,"suffix":""}],"id":"ITEM-1","issue":"11","issued":{"date-parts":[["2012","11","15"]]},"page":"e49801","publisher":"Public Library of Science","title":"Regulation of CD4+ and CD8+ Effector Responses by Sprouty-1","type":"article-journal","volume":"7"},"uris":[""]}],"mendeley":{"formattedCitation":"(Collins et al., 2012)","plainTextFormattedCitation":"(Collins et al., 2012)","previouslyFormattedCitation":"(Collins et al., 2012)"},"properties":{"noteIndex":0},"schema":""}(Collins et al., 2012), TMIGD2 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1080/2162402X.2015.1026534","ISSN":"2162402X","PMID":"26405587","abstract":"We and others recently discovered HHLA2 as a new B7 family member and transmembrane and immunoglobulin domain containing 2 (TMIGD2) as one of its receptors. Based on a new study we propose that HHLA2 may represent a novel immunosuppressive mechanism within the tumor microenvironment and hence could be a target for cancer therapy. TMIGD2 may be another therapeutic target.","author":[{"dropping-particle":"","family":"Janakiram","given":"Murali","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chinai","given":"Jordan M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhao","given":"Aimin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sparano","given":"Joseph A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zang","given":"Xingxing","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"OncoImmunology","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2015"]]},"page":"e1026534","title":"HHLA2 and TMIGD2: new immunotherapeutic targets of the B7 and CD28 families","type":"article-journal","volume":"4"},"uris":[""]}],"mendeley":{"formattedCitation":"(Janakiram et al., 2015)","plainTextFormattedCitation":"(Janakiram et al., 2015)","previouslyFormattedCitation":"(Janakiram et al., 2015)"},"properties":{"noteIndex":0},"schema":""}(Janakiram et al., 2015), CLNK ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1128/MCB.24.13.6067-6075.2004","ISSN":"0270-7306","PMID":"15199160","abstract":"The SLP-76 family of immune cell-specific adaptors is composed of three distinct members named SLP-76, Blnk, and Clnk. They have been implicated in the signaling pathways coupled to immunoreceptors such as the antigen receptors and Fc receptors. Previous studies using gene-targeted mice and deficient cell lines showed that SLP-76 plays a central role in T-cell development and activation. Moreover, it is essential for normal mast cell and platelet activation. In contrast, Blnk is necessary for B-cell development and activation. While the precise function of Clnk is not known, it was reported that Clnk is selectively expressed in mast cells, natural killer (NK) cells, and previously activated T-cells. Moreover, ectopic expression of Clnk was shown to rescue T-cell receptor-mediated signal transduction in an SLP-76-deficient T-cell line, suggesting that, like its relatives, Clnk is involved in the positive regulation of immunoreceptor signaling. Stimulatory effects of Clnk on immunoreceptor signaling were also reported to occur in transfected B-cell and basophil leukemia cell lines. Herein, we attempted to address the physiological role of Clnk in immune cells by the generation of Clnk-deficient mice. The results of our studies demonstrated that Clnk is dispensable for normal differentiation and function of T cells, mast cells, and NK cells. Hence, unlike its relatives, Clnk is not essential for normal immune functions.","author":[{"dropping-particle":"","family":"Utting","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sedgmen","given":"Bradley J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Watts","given":"Tania H.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Shi","given":"Xiaoshu","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Rottapel","given":"Robert","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Iulianella","given":"Angelo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lohnes","given":"David","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Veillette","given":"André","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Molecular and Cellular Biology","id":"ITEM-1","issue":"13","issued":{"date-parts":[["2004","7","1"]]},"page":"6067-6075","title":"Immune Functions in Mice Lacking Clnk, an SLP-76-Related Adaptor Expressed in a Subset of Immune Cells","type":"article-journal","volume":"24"},"uris":[""]}],"mendeley":{"formattedCitation":"(Utting et al., 2004)","plainTextFormattedCitation":"(Utting et al., 2004)","previouslyFormattedCitation":"(Utting et al., 2004)"},"properties":{"noteIndex":0},"schema":""}(Utting et al., 2004), KLRC1 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.immuni.2015.11.005","ISSN":"10974180","PMID":"26680205","abstract":"CD8+T cells and NK cells protect from viral infections by killing virally infected cells and secreting interferon-γ. Several inhibitory receptors limit the magnitude and duration of these anti-viral responses. NKG2A, which is encoded by Klrc1, is a lectin-like inhibitory receptor that is expressed as a heterodimer with CD94 on NK cells and activated CD8+T cells. Previous studies on the impact of CD94/NKG2A heterodimers on anti-viral responses have yielded contrasting results and the in vivo function of NKG2A remains unclear. Here, we generated Klrc1-/-mice and found that NKG2A is selectively required for resistance to ectromelia virus (ECTV). NKG2A functions intrinsically within ECTV-specific CD8+T cells to limit excessive activation, prevent apoptosis, and preserve the specific CD8+T cell response. Thus, although inhibitory receptors often cause T cell exhaustion and viral spreading during chronic viral infections, NKG2A optimizes CD8+T cell responses during an acute poxvirus infection.","author":[{"dropping-particle":"","family":"Rapaport","given":"Aaron S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schriewer","given":"Jill","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gilfillan","given":"Susan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hembrador","given":"Ed","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Crump","given":"Ryan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Plougastel","given":"Beatrice F.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wang","given":"Yaming","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friec","given":"Gaelle","non-dropping-particle":"Le","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gao","given":"Jian","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Cella","given":"Marina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pircher","given":"Hanspeter","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yokoyama","given":"Wayne M.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Buller","given":"R. 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We speculate that the expression of these inhibitory molecules may restrain the functional activity of tumor TRM cells and may represent targets for future immunotherapies. Overall, our transcriptomic analysis of TRM cells has identified molecules that are potentially important for the function of TRM cells and thus serves as an important resource for investigating the biology of human TRM cells. Tumor TRM cells display greater clonal expansion To identify features unique to tumor TRM cells, we compared the transcriptome of TRM cells and non-TRM cells from both normal lung and tumors, and detected 92 differentially expressed transcripts (Fig. 2 A and Table S4) specifically in this subset, hence termed ‘tumor TRM-enriched transcripts’. Reactome pathway analysis of these ‘tumor TRM-enriched’ transcripts showed significant enrichment for transcripts encoding components of the canonical cell cycle, mitosis and DNA replication machinery (Fig. 2 B and Table S4). The tumor TRM subset thus appears to be highly enriched for proliferating CTLs, presumably responding to tumor-associated antigens (TAA), despite PD-1 expression. Unique molecular identifier (UMI)-based T cell receptor (TCR) sequencing assays (Methods) revealed that TRM cells in tumors expressed a significantly more restricted TCR repertoire than non-TRM cells in tumors, as shown by significantly lower Shannon-Wiener and Inverse Simpson diversity indices (Fig. 2 C and Table S6). Furthermore, the tumor TRM population contained a higher mean percentage of expanded clonotypes (73% versus. 52%, in tumor TRM versus. non-TRM populations) (Fig. 2 D). The most expanded clonotype in each patient comprised, on average, 19% of all TRM cells with sequenced TCRs (three examples, Fig. 2 D, right and Table S6), suggesting marked expansion of a single TAA-specific T cell clone in the tumor TRM population, in keeping with recent publications ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/s41591-018-0045-3","ISSN":"1078-8956","author":[{"dropping-particle":"","family":"Guo","given":"Xinyi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Yuanyuan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zheng","given":"Liangtao","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zheng","given":"Chunhong","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Song","given":"Jintao","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Qiming","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kang","given":"Boxi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Liu","given":"Zhouzerui","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jin","given":"Liang","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Xing","given":"Rui","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gao","given":"Ranran","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Lei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Dong","given":"Minghui","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hu","given":"Xueda","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ren","given":"Xianwen","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kirchhoff","given":"Dennis","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Roider","given":"Helge Gottfried","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yan","given":"Tiansheng","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Zemin","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Medicine","id":"ITEM-1","issue":"7","issued":{"date-parts":[["2018","7","25"]]},"page":"978-985","publisher":"Springer US","title":"Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing","type":"article-journal","volume":"24"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1038/s41591-018-0078-7","ISSN":"1078-8956","abstract":"The quantity of tumor-infiltrating lymphocytes (TILs) in breast cancer (BC) is a robust prognostic factor for improved patient survival, particularly in triple-negative and HER2-overexpressing BC subtypes 1 . Although T cells are the predominant TIL population 2 , the relationship between quantitative and qualitative differences in T cell subpopulations and patient prognosis remains unknown. We performed single-cell RNA sequencing (scRNA-seq) of 6,311 T cells isolated from human BCs and show that significant heterogeneity exists in the infiltrating T cell population. We demonstrate that BCs with a high number of TILs contained CD8+ T cells with features of tissue-resident memory T (TRM) cell differentiation and that these CD8+ TRM cells expressed high levels of immune checkpoint molecules and effector proteins. A CD8+ TRM gene signature developed from the scRNA-seq data was significantly associated with improved patient survival in early-stage triple-negative breast cancer (TNBC) and provided better prognostication than CD8 expression alone. Our data suggest that CD8+ TRM cells contribute to BC immunosurveillance and are the key targets of modulation by immune checkpoint inhibition. Further understanding of the development, maintenance and regulation of TRM cells will be crucial for successful immunotherapeutic development in BC.","author":[{"dropping-particle":"","family":"Savas","given":"Peter","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Virassamy","given":"Balaji","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ye","given":"Chengzhong","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Salim","given":"Agus","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mintoff","given":"Christopher P.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Caramia","given":"Franco","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Salgado","given":"Roberto","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Byrne","given":"David J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Teo","given":"Zhi L.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Dushyanthen","given":"Sathana","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Byrne","given":"Ann","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wein","given":"Lironne","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Luen","given":"Stephen J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Poliness","given":"Catherine","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nightingale","given":"Sophie S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Skandarajah","given":"Anita S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gyorki","given":"David E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thornton","given":"Chantel M.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Beavis","given":"Paul A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Fox","given":"Stephen B.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Darcy","given":"Phillip K.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Speed","given":"Terence P.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mackay","given":"Laura K.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Neeson","given":"Paul J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Loi","given":"Sherene","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Medicine","id":"ITEM-2","issue":"7","issued":{"date-parts":[["2018","7","25"]]},"page":"986-993","publisher":"Springer US","title":"Single-cell profiling of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis","type":"article-journal","volume":"24"},"uris":[""]}],"mendeley":{"formattedCitation":"(Guo et al., 2018; Savas et al., 2018)","plainTextFormattedCitation":"(Guo et al., 2018; Savas et al., 2018)","previouslyFormattedCitation":"(Guo et al., 2018; Savas et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Guo et al., 2018; Savas et al., 2018). ‘Tumor TRM-enriched’ transcripts that were highly correlated with cell cycle genes may encode products with important functions, as they are likely to reflect the molecular features of TRM cells that are actively expanding in response to TAA (Table S4). HAVCR2, encoding the co-inhibitory checkpoint molecule TIM-3, was most correlated and connected with cell cycle genes (Fig. 2 E-G). Thus, TIM-3 expression may be a feature of lung tumor TRM cells that is not linked to exhaustion, but rather reflects a state of functionality, as the other transcripts that correlated with expression of TIM-3 and cell cycle genes encode molecules that likely confer additional functionality, such as CD39 (encoded by ENTPD1) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1084/jem.20162115","ISSN":"1540-9538","PMID":"28526759","abstract":"The liver provides a tolerogenic immune niche exploited by several highly prevalent pathogens as well as by primary and metastatic tumors. We have sampled healthy and hepatitis B virus (HBV)-infected human livers to probe for a subset of T cells specialized to overcome local constraints and mediate immunity. We characterize a population of T-bet(lo)Eomes(lo)Blimp-1(hi)Hobit(lo) T cells found within the intrahepatic but not the circulating memory CD8 T cell pool expressing liver-homing/retention markers (CD69(+)CD103(+) CXCR6(+)CXCR3(+)). These tissue-resident memory T cells (TRM) are preferentially expanded in patients with partial immune control of HBV infection and can remain in the liver after the resolution of infection, including compartmentalized responses against epitopes within all major HBV proteins. Sequential IL-15 or antigen exposure followed by TGFβ induces liver-adapted TRM, including their signature high expression of exhaustion markers PD-1 and CD39. We suggest that these inhibitory molecules, together with paradoxically robust, rapid, cell-autonomous IL-2 and IFNγ production, equip liver CD8 TRM to survive while exerting local noncytolytic hepatic immunosurveillance.","author":[{"dropping-particle":"","family":"Pallett","given":"Laura J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Davies","given":"Jessica","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Colbeck","given":"Emily J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Robertson","given":"Francis","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hansi","given":"Navjyot","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Easom","given":"Nicholas J W","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Burton","given":"Alice R.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Stegmann","given":"Kerstin A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schurich","given":"Anna","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Swadling","given":"Leo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gill","given":"Upkar S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Male","given":"Victoria","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Luong","given":"TuVinh","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gander","given":"Amir","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Davidson","given":"Brian R.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kennedy","given":"Patrick T F","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Maini","given":"Mala K.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"The Journal of Experimental Medicine","id":"ITEM-1","issue":"6","issued":{"date-parts":[["2017","5","19"]]},"page":"1567-1580","title":"IL-2(high) tissue-resident T cells in the human liver: Sentinels for hepatotropic infection.","type":"article-journal","volume":"214"},"uris":[""]}],"mendeley":{"formattedCitation":"(Pallett et al., 2017)","plainTextFormattedCitation":"(Pallett et al., 2017)","previouslyFormattedCitation":"(Pallett et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Pallett et al., 2017), CXCL13 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.immuni.2013.10.003","ISSN":"10747613","PMID":"24138885","abstract":"The complex interactions between tumors and their microenvironment remain to be elucidated. Combining large-scale approaches, we examined the spatio-temporal dynamics of 28 different immune cell types (immunome) infiltrating tumors. We found that the immune infiltrate composition changed at each tumor stage and that particular cells had a major impact on survival. Densities of T follicular helper (Tfh) cells and innate cells increased, whereas most T cell densities decreased along with tumor progression. The number of B cells, which are key players in the core immune network and are associated with prolonged survival, increased at a late stage and showed a dual effect on recurrence and tumor progression. The immune control relevance was demonstrated in three endoscopic orthotopic colon-cancer mouse models. Genomic instability of the chemokine CXCL13 was a mechanism associated with Tfh and B cell infiltration. CXCL13 and IL21 were pivotal factors for the Tfh/B cell axis correlating with survival. 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Cooperation between these lymphocyte subsets involves recognition of antigens co-presented by the same dendritic cell, but the frequencies of such antigen-bearing cells early in an infection and of the relevant naive T cells are both low. This suggests that an active mechanism facilitates the necessary cell-cell associations. Here we demonstrate that after immunization but before antigen recognition, naive CD8+ T cells in immunogen-draining lymph nodes upregulate the chemokine receptor CCR5, permitting these cells to be attracted to sites of antigen-specific dendritic cell-CD4+ T cell interaction where the cognate chemokines CCL3 and CCL4 (also known as MIP-1alpha and MIP-1beta) are produced. Interference with this actively guided recruitment markedly reduces the ability of CD4+ T cells to promote memory CD8+ T-cell generation, indicating that an orchestrated series of differentiation events drives nonrandom cell-cell interactions within lymph nodes, optimizing CD8+ T-cell immune responses involving the few antigen-specific precursors present in the naive repertoire.","author":[{"dropping-particle":"","family":"Castellino","given":"Flora","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Huang","given":"Alex Y.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Altan-Bonnet","given":"Grégoire","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Stoll","given":"Sabine","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Scheinecker","given":"Clemens","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Germain","given":"Ronald N.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature","id":"ITEM-1","issue":"7086","issued":{"date-parts":[["2006","4","13"]]},"page":"890-895","title":"Chemokines enhance immunity by guiding naive CD8+T cells to sites of CD4+T cell-dendritic cell interaction","type":"article-journal","volume":"440"},"uris":[""]}],"mendeley":{"formattedCitation":"(Castellino et al., 2006)","plainTextFormattedCitation":"(Castellino et al., 2006)","previouslyFormattedCitation":"(Castellino et al., 2006)"},"properties":{"noteIndex":0},"schema":""}(Castellino et al., 2006), TNFSF4 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1111/j.1600-065X.2009.00766.x","ISSN":"1600-065X","PMID":"19426222","abstract":"SUMMARY OX40 (CD134) and its binding partner, OX40L (CD252), are members of the tumor necrosis factor receptor/tumor necrosis factor superfamily and are expressed on activated CD4(+) and CD8(+) T cells as well as on a number of other lymphoid and non-lymphoid cells. Costimulatory signals from OX40 to a conventional T cell promote division and survival, augmenting the clonal expansion of effector and memory populations as they are being generated to antigen. OX40 additionally suppresses the differentiation and activity of T-regulatory cells, further amplifying this process. OX40 and OX40L also regulate cytokine production from T cells, antigen-presenting cells, natural killer cells, and natural killer T cells, and modulate cytokine receptor signaling. In line with these important modulatory functions, OX40-OX40L interactions have been found to play a central role in the development of multiple inflammatory and autoimmune diseases, making them attractive candidates for intervention in the clinic. Conversely, stimulating OX40 has shown it to be a candidate for therapeutic immunization strategies for cancer and infectious disease. This review provides a broad overview of the biology of OX40 including the intracellular signals from OX40 that impact many aspects of immune function and have promoted OX40 as one of the most prominent costimulatory molecules known to control T cells.","author":[{"dropping-particle":"","family":"Croft","given":"Michael","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"So","given":"Takanori","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Duan","given":"Wei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Soroosh","given":"Pejman","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Immunological reviews","id":"ITEM-1","issue":"1","issued":{"date-parts":[["2009","5"]]},"page":"173-91","publisher":"NIH Public Access","title":"The significance of OX40 and OX40L to T-cell biology and immune disease.","type":"article-journal","volume":"229"},"uris":[""]}],"mendeley":{"formattedCitation":"(Croft et al., 2009)","plainTextFormattedCitation":"(Croft et al., 2009)","previouslyFormattedCitation":"(Croft et al., 2009)"},"properties":{"noteIndex":0},"schema":""}(Croft et al., 2009) (OX-40 ligand), as well as a marker of antigen-specific engagement (4-1BB) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.cell.2016.09.050","ISBN":"1097-4172 (Electronic)\\r0092-8674 (Linking)","ISSN":"00928674","PMID":"27773482","abstract":"FOXP3+ regulatory T cells (Tregs) maintain tolerance against self-antigens and innocuous environmental antigens. However, it is still unknown whether Treg-mediated tolerance is antigen specific and how Treg specificity contributes to the selective loss of tolerance, as observed in human immunopathologies such as allergies. Here, we used antigen-reactive T cell enrichment to identify antigen-specific human Tregs. We demonstrate dominant Treg-mediated tolerance against particulate aeroallergens, such as pollen, house dust mites, and fungal spores. Surprisingly, we found no evidence of functional impairment of Treg responses in allergic donors. Rather, major allergenic proteins, known to rapidly dissociate from inhaled allergenic particles, have a generally reduced capability to generate Treg responses. Most strikingly, in individual allergic donors, Th2 cells and Tregs always target disparate proteins. 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The Hobit-Blimp1 transcriptional module is also required for other populations of tissue-resident lymphocytes, including natural killer T (NKT) cells and liver-resident NK cells, all of which share a common transcriptional program. Our results identify Hobit and Blimp1 as central regulators of this universal program that instructs tissue retention in diverse tissue-resident lymphocyte populations.","author":[{"dropping-particle":"","family":"Mackay","given":"L. K.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Minnich","given":"M.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kragten","given":"N. A. 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Lung TRM cells were poised for rapid responsiveness by constitutive expression of deployment-ready mRNA encoding effector molecules, but they also expressed many inhibitory regulators, suggestive of programmed restraint. A distinct set of transcription factors was active in CD103+ TRM cells, including Notch. Genetic and pharmacological experiments with mice revealed that Notch activity was required for the maintenance of CD103+ TRM cells. 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Analysis of the ~12,000 single-cell transcriptomes revealed 5 clusters (Methods) of TRM cells and 4 clusters of non-TRM cells with varying frequency per donor, highlighting the importance of studying multiple patient samples (Figs. 3 A,B and S2 A-C). Among the 5 TRM clusters, clusters 1-3 (light purple, purple and blue, respectively) contained a greater proportion of the tumor TRM population while clusters 4 and 5 (green and red) contained more lung TRM cells (Fig. 3 C). Most strikingly, clusters 1-3 contained very few lung TRM cells (Fig. 3 C). We infer that the ‘tumor TRM-enriched’ transcripts detected in our analysis of bulk populations (Fig. 2 A) were likely to be contributed by cells in these subsets. 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We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. 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Cooperation between these lymphocyte subsets involves recognition of antigens co-presented by the same dendritic cell, but the frequencies of such antigen-bearing cells early in an infection and of the relevant naive T cells are both low. This suggests that an active mechanism facilitates the necessary cell-cell associations. Here we demonstrate that after immunization but before antigen recognition, naive CD8+ T cells in immunogen-draining lymph nodes upregulate the chemokine receptor CCR5, permitting these cells to be attracted to sites of antigen-specific dendritic cell-CD4+ T cell interaction where the cognate chemokines CCL3 and CCL4 (also known as MIP-1alpha and MIP-1beta) are produced. Interference with this actively guided recruitment markedly reduces the ability of CD4+ T cells to promote memory CD8+ T-cell generation, indicating that an orchestrated series of differentiation events drives nonrandom cell-cell interactions within lymph nodes, optimizing CD8+ T-cell immune responses involving the few antigen-specific precursors present in the naive repertoire.","author":[{"dropping-particle":"","family":"Castellino","given":"Flora","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Huang","given":"Alex Y.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Altan-Bonnet","given":"Grégoire","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Stoll","given":"Sabine","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Scheinecker","given":"Clemens","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Germain","given":"Ronald N.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature","id":"ITEM-1","issue":"7086","issued":{"date-parts":[["2006","4","13"]]},"page":"890-895","title":"Chemokines enhance immunity by guiding naive CD8+T cells to sites of CD4+T cell-dendritic cell interaction","type":"article-journal","volume":"440"},"uris":[""]}],"mendeley":{"formattedCitation":"(Castellino et al., 2006)","plainTextFormattedCitation":"(Castellino et al., 2006)","previouslyFormattedCitation":"(Castellino et al., 2006)"},"properties":{"noteIndex":0},"schema":""}(Castellino et al., 2006); Fig. 3 F), consistent with recent reports ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/s41591-018-0045-3","ISSN":"1078-8956","author":[{"dropping-particle":"","family":"Guo","given":"Xinyi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Yuanyuan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zheng","given":"Liangtao","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zheng","given":"Chunhong","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Song","given":"Jintao","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Qiming","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kang","given":"Boxi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Liu","given":"Zhouzerui","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jin","given":"Liang","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Xing","given":"Rui","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gao","given":"Ranran","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Lei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Dong","given":"Minghui","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hu","given":"Xueda","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ren","given":"Xianwen","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kirchhoff","given":"Dennis","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Roider","given":"Helge Gottfried","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yan","given":"Tiansheng","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Zemin","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Medicine","id":"ITEM-1","issue":"7","issued":{"date-parts":[["2018","7","25"]]},"page":"978-985","publisher":"Springer US","title":"Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing","type":"article-journal","volume":"24"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1038/s41591-018-0078-7","ISSN":"1078-8956","abstract":"The quantity of tumor-infiltrating lymphocytes (TILs) in breast cancer (BC) is a robust prognostic factor for improved patient survival, particularly in triple-negative and HER2-overexpressing BC subtypes 1 . Although T cells are the predominant TIL population 2 , the relationship between quantitative and qualitative differences in T cell subpopulations and patient prognosis remains unknown. We performed single-cell RNA sequencing (scRNA-seq) of 6,311 T cells isolated from human BCs and show that significant heterogeneity exists in the infiltrating T cell population. We demonstrate that BCs with a high number of TILs contained CD8+ T cells with features of tissue-resident memory T (TRM) cell differentiation and that these CD8+ TRM cells expressed high levels of immune checkpoint molecules and effector proteins. A CD8+ TRM gene signature developed from the scRNA-seq data was significantly associated with improved patient survival in early-stage triple-negative breast cancer (TNBC) and provided better prognostication than CD8 expression alone. Our data suggest that CD8+ TRM cells contribute to BC immunosurveillance and are the key targets of modulation by immune checkpoint inhibition. Further understanding of the development, maintenance and regulation of TRM cells will be crucial for successful immunotherapeutic development in BC.","author":[{"dropping-particle":"","family":"Savas","given":"Peter","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Virassamy","given":"Balaji","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ye","given":"Chengzhong","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Salim","given":"Agus","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mintoff","given":"Christopher P.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Caramia","given":"Franco","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Salgado","given":"Roberto","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Byrne","given":"David J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Teo","given":"Zhi L.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Dushyanthen","given":"Sathana","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Byrne","given":"Ann","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wein","given":"Lironne","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Luen","given":"Stephen J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Poliness","given":"Catherine","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nightingale","given":"Sophie S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Skandarajah","given":"Anita S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gyorki","given":"David E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thornton","given":"Chantel M.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Beavis","given":"Paul A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Fox","given":"Stephen B.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Darcy","given":"Phillip K.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Speed","given":"Terence P.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mackay","given":"Laura K.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Neeson","given":"Paul J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Loi","given":"Sherene","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Medicine","id":"ITEM-2","issue":"7","issued":{"date-parts":[["2018","7","25"]]},"page":"986-993","publisher":"Springer US","title":"Single-cell profiling of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis","type":"article-journal","volume":"24"},"uris":[""]}],"mendeley":{"formattedCitation":"(Guo et al., 2018; Savas et al., 2018)","plainTextFormattedCitation":"(Guo et al., 2018; Savas et al., 2018)","previouslyFormattedCitation":"(Guo et al., 2018; Savas et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Guo et al., 2018; Savas et al., 2018), but with a noteworthy caveat that transcript expression does not necessarily reflect functionality. This shared expression pattern suggests that the cycling cluster (cluster 1, light purple) may represent cells in cluster 2 that are entering the cell cycle. Confirming this idea, cell-state hierarchy maps of all TRM cells, constructed using Monocle2 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nbt.2859","ISSN":"1087-0156","PMID":"24658644","abstract":"Defining the transcriptional dynamics of a temporal process such as cell differentiation is challenging owing to the high variability in gene expression between individual cells. Time-series gene expression analyses of bulk cells have difficulty distinguishing early and late phases of a transcriptional cascade or identifying rare subpopulations of cells, and single-cell proteomic methods rely on a priori knowledge of key distinguishing markers. Here we describe Monocle, an unsupervised algorithm that increases the temporal resolution of transcriptome dynamics using single-cell RNA-Seq data collected at multiple time points. Applied to the differentiation of primary human myoblasts, Monocle revealed switch-like changes in expression of key regulatory factors, sequential waves of gene regulation, and expression of regulators that were not known to act in differentiation. We validated some of these predicted regulators in a loss-of function screen. Monocle can in principle be used to recover single-cell gene expression kinetics from a wide array of cellular processes, including differentiation, proliferation and oncogenic transformation.","author":[{"dropping-particle":"","family":"Trapnell","given":"Cole","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Cacchiarelli","given":"Davide","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Grimsby","given":"Jonna","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pokharel","given":"Prapti","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Li","given":"Shuqiang","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Morse","given":"Michael","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lennon","given":"Niall J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Livak","given":"Kenneth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mikkelsen","given":"Tarjei S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Rinn","given":"John L","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Biotechnology","id":"ITEM-1","issue":"4","issued":{"date-parts":[["2014","4","23"]]},"page":"381-386","title":"The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells","type":"article-journal","volume":"32"},"uris":[""]}],"mendeley":{"formattedCitation":"(Trapnell et al., 2014)","plainTextFormattedCitation":"(Trapnell et al., 2014)","previouslyFormattedCitation":"(Trapnell et al., 2014)"},"properties":{"noteIndex":0},"schema":""}(Trapnell et al., 2014) (Methods), revealed that cells in cluster 2 were most similar to the cycling TRM cells (cluster 1, Fig. 3 G). Additionally, when we performed hierarchical clustering (Methods) of these cells, we noted that the proliferating cluster 1 clustered more with cells assigned to cluster 2, than the other TRM clusters (Fig. 3 H). This finding was corroborated when we calculated the average distance in principle component space (Methods) between each cell in cluster 1 to the other TRM clusters (Fig. S2 D). T cells expressing TCF7, encoding the transcription factor TCF-1 are linked to ‘stemness’, and have been shown to sustain T cell expansion and responses following anti-PD-1 therapy during chronic infections and in tumor models in mice ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nature19330","ISSN":"1476-4687","PMID":"27501248","abstract":"Chronic viral infections are characterized by a state of CD8(+) T-cell dysfunction that is associated with expression of the programmed cell death 1 (PD-1) inhibitory receptor. A better understanding of the mechanisms that regulate CD8(+) T-cell responses during chronic infection is required to improve immunotherapies that restore function in exhausted CD8(+) T cells. Here we identify a population of virus-specific CD8(+) T cells that proliferate after blockade of the PD-1 inhibitory pathway in mice chronically infected with lymphocytic choriomeningitis virus (LCMV). These LCMV-specific CD8(+) T cells expressed the PD-1 inhibitory receptor, but also expressed several costimulatory molecules such as ICOS and CD28. This CD8(+) T-cell subset was characterized by a unique gene signature that was related to that of CD4(+) T follicular helper (TFH) cells, CD8(+) T cell memory precursors and haematopoietic stem cell progenitors, but that was distinct from that of CD4(+) TH1 cells and CD8(+) terminal effectors. This CD8(+) T-cell population was found only in lymphoid tissues and resided predominantly in the T-cell zones along with naive CD8(+) T cells. These PD-1(+)CD8(+) T cells resembled stem cells during chronic LCMV infection, undergoing self-renewal and also differentiating into the terminally exhausted CD8(+) T cells that were present in both lymphoid and non-lymphoid tissues. The proliferative burst after PD-1 blockade came almost exclusively from this CD8(+) T-cell subset. Notably, the transcription factor TCF1 had a cell-intrinsic and essential role in the generation of this CD8(+) T-cell subset. These findings provide a better understanding of T-cell exhaustion and have implications in the optimization of PD-1-directed immunotherapy in chronic infections and cancer.","author":[{"dropping-particle":"","family":"Im","given":"Se Jin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hashimoto","given":"Masao","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gerner","given":"Michael Y","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lee","given":"Junghwa","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kissick","given":"Haydn T","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Burger","given":"Matheus C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Shan","given":"Qiang","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hale","given":"J Scott","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lee","given":"Judong","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nasti","given":"Tahseen H","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sharpe","given":"Arlene H","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Freeman","given":"Gordon J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Germain","given":"Ronald N","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nakaya","given":"Helder I","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Xue","given":"Hai-Hui","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ahmed","given":"Rafi","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature","id":"ITEM-1","issue":"7620","issued":{"date-parts":[["2016","8","15"]]},"page":"417-421","title":"Defining CD8+ T cells that provide the proliferative burst after PD-1 therapy.","type":"article-journal","volume":"537"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1016/j.immuni.2016.07.021","ISSN":"10974180","PMID":"27533016","abstract":"Chronic infections promote the terminal differentiation (or “exhaustion”) of T?cells and are thought to?preclude the formation of memory T?cells. In contrast, we discovered a small subpopulation of virus-specific CD8+ T?cells that sustained the T?cell response during chronic infections. These cells were defined by, and depended on, the expression of the transcription factor Tcf1. Transcriptome analysis revealed that this population shared key characteristics of central memory cells but lacked an effector signature. Unlike conventional memory cells, Tcf1-expressing T?cells displayed hallmarks of an “exhausted” phenotype, including the expression of inhibitory receptors such as PD-1 and Lag-3. This population was crucial for the T?cell expansion that occurred in response to inhibitory receptor blockade during chronic infection. These findings identify a memory-like T?cell population that sustains T?cell responses and is a prime target for therapeutic interventions to improve the immune response in chronic infections.","author":[{"dropping-particle":"","family":"Utzschneider","given":"Daniel T.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Charmoy","given":"Mélanie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chennupati","given":"Vijaykumar","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pousse","given":"Laurène","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ferreira","given":"Daniela Pais","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Calderon-Copete","given":"Sandra","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Danilo","given":"Maxime","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alfei","given":"Francesca","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hofmann","given":"Maike","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wieland","given":"Dominik","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pradervand","given":"Sylvain","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thimme","given":"Robert","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zehn","given":"Dietmar","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Held","given":"Werner","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Immunity","id":"ITEM-2","issue":"2","issued":{"date-parts":[["2016"]]},"page":"415-427","title":"T Cell Factor 1-Expressing Memory-like CD8+ T Cells Sustain the Immune Response to Chronic Viral Infections","type":"article-journal","volume":"45"},"uris":[""]}],"mendeley":{"formattedCitation":"(Im et al., 2016; Utzschneider et al., 2016)","plainTextFormattedCitation":"(Im et al., 2016; Utzschneider et al., 2016)","previouslyFormattedCitation":"(Im et al., 2016; Utzschneider et al., 2016)"},"properties":{"noteIndex":0},"schema":""}(Im et al., 2016; Utzschneider et al., 2016). Applying unbiased differential expression analysis (MAST), we found that among the tumor-infiltrating CTLs TCF7 expression was enriched in the CCR7 (CD197) and SELL (CD62L) expressing non-TRM subset, likely to reflect central memory cells (Figs. 3 B and S2 E; light orange), with no significant enrichment observed in any of the TRM clusters (1 and 2) linked to cell proliferation (Fig. S2 E and Table S7) compared to other TRM clusters. This finding is consistent with recent reports which showed that in mouse tumor models Tcf7+ tumor-infiltrating T cells were enriched for central memory but not TRM cell features ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.immuni.2018.12.021","ISSN":"1074-7613","author":[{"dropping-particle":"","family":"Siddiqui","given":"Imran","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schaeuble","given":"Karin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chennupati","given":"Vijaykumar","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Marraco","given":"Silvia A Fuertes","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Calderon-copete","given":"Sandra","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ferreira","given":"Daniela 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Overall, our single-cell transcriptome uncovered additional phenotypically distinct subsets of lung and tumor TRM cells that have not previously been described, and which are likely to play an important role in anti-tumor immune responses. TIM-3+IL7R– TRM subset was enriched for transcripts linked to cytotoxicityTo dissect the molecular properties unique to tumor-infiltrating TRM cells in each of the 4 larger TRM clusters (clusters 2-5), we performed multiple pair-wise single-cell differential gene expression analyses (Methods). Over 250 differentially expressed genes showed higher expression in any one of the four clusters (Fig. 4 A and Table S7), indicating that cells in different clusters had divergent gene expression programs. For example, cells in cluster 3 were highly enriched for transcripts encoding heat shock proteins (e.g., HSPA1A, HSPA1B and HSP90AA1), whereas cells in cluster 5, comprising TRM cells from both normal lung and tumor tissue, expressed high levels of IL7R, which encodes the IL-7 receptor, a marker of memory precursor cells ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-1","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]}],"mendeley":{"formattedCitation":"(Patil et al., 2018)","plainTextFormattedCitation":"(Patil et al., 2018)","previouslyFormattedCitation":"(Patil et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Patil et al., 2018), and transcripts such as GPR183 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.immuni.2017.11.020","ISSN":"10747613","PMID":"29343433","abstract":"Group 3 innate lymphoid cells (ILC3s) sense environmental signals and are critical for tissue integrity in the intestine. Yet, which signals are sensed and what receptors control ILC3 function remain poorly understood. Here, we show that ILC3s with a lymphoid-tissue-inducer (LTi) phenotype expressed G-protein-coupled receptor 183 (GPR183) and migrated to its oxysterol ligand 7α,25-hydroxycholesterol (7α,25-OHC). In mice lacking Gpr183 or 7α,25-OHC, ILC3s failed to localize to cryptopatches (CPs) and isolated lymphoid follicles (ILFs). Gpr183 deficiency in ILC3s caused a defect in CP and ILF formation in the colon, but not in the small intestine. Localized oxysterol production by fibroblastic stromal cells provided an essential signal for colonic lymphoid tissue development, and inflammation-induced increased oxysterol production caused colitis through GPR183-mediated cell recruitment. Our findings show that GPR183 promotes lymphoid organ development and indicate that oxysterol-GPR183-dependent positioning within tissues controls ILC3 activity and intestinal homeostasis.","author":[{"dropping-particle":"","family":"Emg?rd","given":"Johanna","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kammoun","given":"Hana","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"García-Cassani","given":"Bethania","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chesné","given":"Julie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Parigi","given":"Sara M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jacob","given":"Jean-Marie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Cheng","given":"Hung-Wei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Evren","given":"Elza","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Das","given":"Srustidhar","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Czarnewski","given":"Paulo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sleiers","given":"Natalie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Melo-Gonzalez","given":"Felipe","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kvedaraite","given":"Egle","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Svensson","given":"Mattias","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Scandella","given":"Elke","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hepworth","given":"Matthew R","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Huber","given":"Samuel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ludewig","given":"Burkhard","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peduto","given":"Lucie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Villablanca","given":"Eduardo J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Veiga-Fernandes","given":"Henrique","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pereira","given":"Jo?o P","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Flavell","given":"Richard A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Willinger","given":"Tim","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Immunity","id":"ITEM-1","issue":"1","issued":{"date-parts":[["2018","1","16"]]},"page":"120-132.e8","publisher":"Elsevier","title":"Oxysterol Sensing through the Receptor GPR183 Promotes the Lymphoid-Tissue-Inducing Function of Innate Lymphoid Cells and Colonic Inflammation","type":"article-journal","volume":"48"},"uris":[""]}],"mendeley":{"formattedCitation":"(Emg?rd et al., 2018)","plainTextFormattedCitation":"(Emg?rd et al., 2018)","previouslyFormattedCitation":"(Emg?rd et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Emg?rd et al., 2018), MYADM ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1091/mbc.E10-11-0910","ISBN":"1059-1524","ISSN":"1059-1524","PMID":"21325632","abstract":"Membrane organization into condensed domains or rafts provides molecular platforms for selective recruitment of proteins. Cell migration is a general process that requires spatiotemporal targeting of Rac1 to membrane rafts. The protein machinery responsible for making rafts competent to recruit Rac1 remains elusive. Some members of the MAL family of proteins are involved in specialized processes dependent on this type of membrane. Because condensed membrane domains are a general feature of the plasma membrane of all mammalian cells, we hypothesized that MAL family members with ubiquitous expression and plasma membrane distribution could be involved in the organization of membranes for cell migration. We show that myeloid-associated differentiation marker (MYADM), a protein with unique features within the MAL family, colocalizes with Rac1 in membrane protrusions at the cell surface and distributes in condensed membranes. MYADM knockdown (KD) cells had altered membrane condensation and showed deficient incorporation of Rac1 to membrane raft fractions and, similar to Rac1 KD cells, exhibited reduced cell spreading and migration. Results of rescue-of-function experiments by expression of MYADM or active Rac1L61 in cells knocked down for Rac1 or MYADM, respectively, are consistent with the idea that MYADM and Rac1 act on parallel pathways that lead to similar functional outcomes.","author":[{"dropping-particle":"","family":"Aranda","given":"Juan F","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Reglero-Real","given":"Natalia","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kremer","given":"Leonor","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Marcos-Ramiro","given":"Beatriz","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ruiz-Saenz","given":"A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Calvo","given":"María","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Enrich","given":"Carlos","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Correas","given":"Isabel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Millan","given":"J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alonso","given":"Miguel A","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Molecular Biology of the Cell","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2011","4","15"]]},"page":"1252-1262","publisher":"American Society for Cell Biology","title":"MYADM regulates Rac1 targeting to ordered membranes required for cell spreading and migration","type":"article-journal","volume":"22"},"uris":[""]}],"mendeley":{"formattedCitation":"(Aranda et al., 2011)","plainTextFormattedCitation":"(Aranda et al., 2011)","previouslyFormattedCitation":"(Aranda et al., 2011)"},"properties":{"noteIndex":0},"schema":""}(Aranda et al., 2011), VIM ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ncb1355","ISSN":"1465-7392","PMID":"16429129","abstract":"Although the adhesive interactions of leukocytes with endothelial cells are well understood, little is known about the detailed mechanisms underlying the actual migration of leukocytes across the endothelium (diapedesis). Leukocytes have been shown to use both paracellular and transcellular routes for transendothelial migration. Here we show that peripheral blood mononuclear cells (PBMCs; T- and B-lymphocytes) preferentially use the transcellular route. The intermediate filaments of both endothelial cells and lymphocytes formed a highly dynamic anchoring structure at the site of contact between these two cell types. The initiation of this process was markedly reduced in vimentin-deficient (vim(-/-)) PBMCs and endothelial cells. When compared with wild-type PBMCs, vim(-/-) PBMCs showed a markedly reduced capacity to home to mesenteric lymph nodes and spleen. Furthermore, endothelial integrity was compromised in vim(-/-) mice, demonstrating that intermediate filaments also regulate the barrier that governs leukocyte extravasation. Absence of vimentin resulted in highly aberrant expression and distribution of surface molecules critical for homing (ICAM-1 and VCAM-1 on endothelial cells and integrin-beta1 on PBMCs). These data show that intermediate filaments are active in lymphocyte adhesion and transmigration.","author":[{"dropping-particle":"","family":"Nieminen","given":"Mikko","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Henttinen","given":"Tiina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Merinen","given":"Marika","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Marttila–Ichihara","given":"Fumiko","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Eriksson","given":"John E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jalkanen","given":"Sirpa","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Cell Biology","id":"ITEM-1","issue":"2","issued":{"date-parts":[["2006","2","22"]]},"page":"156-162","title":"Vimentin function in lymphocyte adhesion and transcellular migration","type":"article-journal","volume":"8"},"uris":[""]}],"mendeley":{"formattedCitation":"(Nieminen et al., 2006)","plainTextFormattedCitation":"(Nieminen et al., 2006)","previouslyFormattedCitation":"(Nieminen et al., 2006)"},"properties":{"noteIndex":0},"schema":""}(Nieminen et al., 2006) and ANKRD28 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.yexcr.2008.12.005","ISBN":"1090-2422 (Electronic)\\n0014-4827 (Linking)","ISSN":"10902422","PMID":"19118547","abstract":"DOCK180 is a guanine exchange factor of Rac1 originally identified as a protein bound to an SH3 domain of the Crk adaptor protein. DOCK180 induces tyrosine phosphorylation of p130Cas, and recruits the Crk-p130Cascomplex to focal adhesions. To understand the role of DOCK180 in cell adhesion and migration, we searched for DOCK180-binding proteins with a nano-LC/MS/MS system, and identified ANKRD28, a protein that contains twenty-six ankyrin domain repeats. Knockdown of ANKRD28 by RNA interference reduced the velocity of migration of HeLa cells, suggesting that this protein plays a physiologic role in the DOCK180-Rac1 signaling pathway. Furthermore, knockdown of ANKRD28 was found to alter the distribution of focal adhesion proteins such as Crk, paxillin, and p130Cas. On the other hand, expression of ANKRD28, p130Cas, Crk, and DOCK180 induced hyper-phosphorylation of p130Cas, and impaired detachment of the cell membrane during migration. Consequently, cells expressing ANKRD28 exhibited multiple long cellular processes. ANKRD28 associated with DOCK180 in an SH3-dependent manner and competed with ELMO, another protein bound to the SH3 domain of DOCK180. In striking contrast to ANKRD28, overexpression of ELMO induced extensive lamellipodial protrusion around the entire circumference. These data suggest that ANKRD28 specifies the localization and the activity of the DOCK180-Rac1 pathway. ? 2008 Elsevier Inc. All rights reserved.","author":[{"dropping-particle":"","family":"Tachibana","given":"Mitsuhiro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kiyokawa","given":"Etsuko","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hara","given":"Shigeo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Iemura","given":"Shun ichiro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Natsume","given":"Tohru","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Manabe","given":"Toshiaki","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Matsuda","given":"Michiyuki","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Experimental Cell Research","id":"ITEM-1","issue":"5","issued":{"date-parts":[["2009","3","10"]]},"page":"863-876","title":"Ankyrin repeat domain 28 (ANKRD28), a novel binding partner of DOCK180, promotes cell migration by regulating focal adhesion formation","type":"article-journal","volume":"315"},"uris":[""]}],"mendeley":{"formattedCitation":"(Tachibana et al., 2009)","plainTextFormattedCitation":"(Tachibana et al., 2009)","previouslyFormattedCitation":"(Tachibana et al., 2009)"},"properties":{"noteIndex":0},"schema":""}(Tachibana et al., 2009), which encode proteins involved in cell migration and tissue homing (Fig. 4 A,B).Because of their close relationship with cycling TRM cells (Fig. 3 D,G and H), we focused our analysis on the TRM cells in cluster 2. The 91 transcripts enriched in cluster 2 compared to the other TRM clusters (Fig. 4 A) included several which encoded products linked to cytotoxic activity such as PRF1, GZMB, GZMA, CTSW ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-1","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]}],"mendeley":{"formattedCitation":"(Patil et al., 2018)","plainTextFormattedCitation":"(Patil et al., 2018)","previouslyFormattedCitation":"(Patil et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Patil et al., 2018), RAB27A ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1083/jcb.152.4.825","ISBN":"0021-9525 (Print)\\r0021-9525 (Linking)","ISSN":"00219525","PMID":"11266472","abstract":"Rab27a activity is affected in several mouse models of human disease including Griscelli (ashen mice) and Hermansky-Pudlak (gunmetal mice) syndromes. A loss of function mutation occurs in the Rab27a gene in ashen (ash), whereas in gunmetal (gm) Rab27a dysfunction is secondary to a mutation in the alpha subunit of Rab geranylgeranyl transferase, an enzyme required for prenylation and activation of Rabs. We show here that Rab27a is normally expressed in cytotoxic T lymphocytes (CTLs), but absent in ashen homozygotes (ash/ash). Cytotoxicity and secretion assays show that ash/ash CTLs are unable to kill target cells or to secrete granzyme A and hexosaminidase. By immunofluorescence and electron microscopy, we show polarization but no membrane docking of ash/ash lytic granules at the immunological synapse. In gunmetal CTLs, we show underprenylation and redistribution of Rab27a to the cytosol, implying reduced activity. Gunmetal CTLs show a reduced ability to kill target cells but retain the ability to secrete hexosaminidase and granzyme A. However, only some of the granules polarize to the immunological synapse, and many remain dispersed around the periphery of the CTLs. These results demonstrate that Rab27a is required in a final secretory step and that other Rab proteins also affected in gunmetal are likely to be involved in polarization of the granules to the immunological synapse.","author":[{"dropping-particle":"","family":"Stinchcombe","given":"Jane C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Barral","given":"Duarte C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mules","given":"Emilie H","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Booth","given":"Sarah","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hume","given":"Alistair N","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Machesky","given":"Laura M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seabra","given":"Miguel C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Griffiths","given":"Gillian M","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Journal of Cell Biology","id":"ITEM-1","issue":"4","issued":{"date-parts":[["2001","2","19"]]},"page":"825-833","publisher":"The Rockefeller University Press","title":"Rab27a is required for regulated secretion in cytotoxic T lymphocytes","type":"article-journal","volume":"152"},"uris":[""]}],"mendeley":{"formattedCitation":"(Stinchcombe et al., 2001)","plainTextFormattedCitation":"(Stinchcombe et al., 2001)","previouslyFormattedCitation":"(Stinchcombe et al., 2001)"},"properties":{"noteIndex":0},"schema":""}(Stinchcombe et al., 2001), ITGAE ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1158/0008-5472.CAN-12-2569","ISBN":"1538-7445 (Electronic)\\r0008-5472 (Linking)","ISSN":"00085472","PMID":"23188505","abstract":"T-cell adhesion/costimulatory molecules and their cognate receptors on target cells play a major role in T-cell receptor (TCR)-mediated activities. Here, we compared the involvement of CD103 and LFA-1, and their respective ligands, in the maturation of the cytotoxic immune synapse (cIS) and in the activation of CTL effector functions. Our results indicate that cytotoxicity toward cancer cells and, to a lesser extent, cytokine production by specific CTL require, together with TCR engagement, the interaction of either CD103 with E-cadherin or LFA-1 with ICAM-1. Flow-based adhesion assay showed that engagement of CD103 or LFA-1, together with TCR, enhances the strength of the T-cell/target cell interaction. Moreover, electron microscopic analyses showed that integrin-dependent mature cIS (mcIS) displays a cohesive ultrastructure, with tight membrane contacts separated by extensive clefts. In contrast, immature cIS (icIS), which is unable to trigger target cell lysis, is loose, with multiple protrusions in the effector cell membrane. Experiments using confocal microscopy revealed polarized cytokine release and degranulation at the mcIS associated with target cell killing, whereas icIS is characterized by failure of IFN-γ and granzyme B relocalization. Thus, interactive forces between CTL and epithelial tumor cells, mainly regulated by integrin engagement, correlate with maturity and the ultrastructure of the cIS and influence CTL effector functions. These results provide new insights into molecular mechanisms regulating antitumor CTL responses and may lead to the development of more efficient cancer immunotherapy strategies.","author":[{"dropping-particle":"","family":"Franciszkiewicz","given":"Katarzyna","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Floc'H","given":"Audrey","non-dropping-particle":"Le","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Boutet","given":"Marie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vergnon","given":"Isabelle","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmitt","given":"Alain","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mami-Chouaib","given":"Fathia","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Cancer Research","id":"ITEM-1","issue":"2","issued":{"date-parts":[["2013"]]},"page":"617-628","title":"CD103 or LFA-1 engagement at the immune synapse between cytotoxic T cells and tumor cells promotes maturation and regulates T-cell effector functions","type":"article-journal","volume":"73"},"uris":[""]}],"mendeley":{"formattedCitation":"(Franciszkiewicz et al., 2013)","plainTextFormattedCitation":"(Franciszkiewicz et al., 2013)","previouslyFormattedCitation":"(Franciszkiewicz et al., 2013)"},"properties":{"noteIndex":0},"schema":""}(Franciszkiewicz et al., 2013) and CRTAM ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-1","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]}],"mendeley":{"formattedCitation":"(Patil et al., 2018)","plainTextFormattedCitation":"(Patil et al., 2018)","previouslyFormattedCitation":"(Patil et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Patil et al., 2018) (Figs. 4 C and S3 A), as well as transcripts encoding effector cytokines and chemokines such as IFN-?? CCL3, CXCL13, IL17A and IL26. Cluster 2 also expressed high levels of transcripts encoding transcription factors known to promote the survival of memory or effector CTLs (ID2 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.2158","ISBN":"1529-2916 (Electronic)\\r1529-2908 (Linking)","ISSN":"15292908","PMID":"22057289","abstract":"During infection, naive CD8 + T cells differentiate into effector cells, which are armed to eliminate pathogens, and memory cells, which are poised to protect against reinfection. The transcriptional program that regulates terminal differentiation into short-lived effector-memory versus long-lived memory cells is not clearly defined. Through the use of mice expressing reporters for the DNA-binding inhibitors Id2 and Id3, we identified Id3 hi precursors of long-lived memory cells before the peak of T cell population expansion or upregulation of cell-surface receptors that indicate memory potential. Deficiency in Id2 or Id3 resulted in loss of distinct CD8 + effector and memory populations, which demonstrated unique roles for these inhibitors of E-protein transcription factors. Furthermore, cytokines altered the expression of Id2 and Id3 differently, which provides insight into how external cues influence gene expression.","author":[{"dropping-particle":"","family":"Yang","given":"Cliff Y.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Best","given":"J Adam","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Knell","given":"Jamie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yang","given":"Edward","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sheridan","given":"Alison D","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jesionek","given":"Adam K","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Li","given":"Haiyan S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Rivera","given":"Richard R","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lind","given":"Kristin Camfield","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"D'Cruz","given":"Louise M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Watowich","given":"Stephanie S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Murre","given":"Cornelis","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Goldrath","given":"Ananda W","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"12","issued":{"date-parts":[["2011","11","6"]]},"page":"1221-1229","title":"The transcriptional regulators Id2 and Id3 control the formation of distinct memory CD8 + T cell subsets","type":"article-journal","volume":"12"},"uris":[""]}],"mendeley":{"formattedCitation":"(Yang et al., 2011)","plainTextFormattedCitation":"(Yang et al., 2011)","previouslyFormattedCitation":"(Yang et al., 2011)"},"properties":{"noteIndex":0},"schema":""}(Yang et al., 2011), STAT3 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.immuni.2011.09.017","ISSN":"1097-4180","PMID":"22118527","abstract":"Memory CD8(+) T cells are critical for long-term immunity, but the genetic pathways governing their formation remain poorly defined. This study shows that the IL-10-IL-21-STAT3 pathway is critical for memory CD8(+) T cell development after acute LCMV infection. In the absence of either interleukin-10 (IL-10) and IL-21 or STAT3, virus-specific CD8(+) T cells retain terminal effector (TE) differentiation states and fail to mature into protective memory T cells that contain self-renewing central memory T cells. Expression of Eomes, BCL-6, Blimp-1, and SOCS3 was considerably reduced in STAT3-deficient memory CD8(+) T cells, and BCL-6- or SOCS3-deficient CD8(+) T cells also had perturbed memory cell development. Reduced SOCS3 expression rendered STAT3-deficient CD8(+) T cells hyperresponsive to IL-12, suggesting that the STAT3-SOCS3 pathway helps to insulate memory precursor cells from inflammatory cytokines that drive TE differentiation. Thus, memory CD8(+) T cell precursor maturation is an active process dependent on IL-10-IL-21-STAT3 signaling.","author":[{"dropping-particle":"","family":"Cui","given":"Weiguo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Liu","given":"Ying","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weinstein","given":"Jason S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Craft","given":"Joseph","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kaech","given":"Susan M","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Immunity","id":"ITEM-1","issue":"5","issued":{"date-parts":[["2011","11","23"]]},"page":"792-805","publisher":"NIH Public Access","title":"An interleukin-21-interleukin-10-STAT3 pathway is critical for functional maturation of memory CD8+ T cells.","type":"article-journal","volume":"35"},"uris":[""]}],"mendeley":{"formattedCitation":"(Cui et al., 2011)","plainTextFormattedCitation":"(Cui et al., 2011)","previouslyFormattedCitation":"(Cui et al., 2011)"},"properties":{"noteIndex":0},"schema":""}(Cui et al., 2011), ZEB2 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1084/jem.20150186","ISSN":"0022-1007","PMID":"26503446","abstract":"The transcription factor T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during viral infection. We find that, at high concentrations, T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin immunoprecipitation sequencing showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.","author":[{"dropping-particle":"","family":"Dominguez","given":"Claudia X.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Amezquita","given":"Robert A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Guan","given":"Tianxia","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Marshall","given":"Heather D.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Joshi","given":"Nikhil S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kleinstein","given":"Steven H.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kaech","given":"Susan M.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"The Journal of Experimental Medicine","id":"ITEM-1","issue":"12","issued":{"date-parts":[["2015"]]},"page":"2041-2056","title":"The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation in response to LCMV viral infection","type":"article-journal","volume":"212"},"uris":[""]}],"mendeley":{"formattedCitation":"(Dominguez et al., 2015)","plainTextFormattedCitation":"(Dominguez et al., 2015)","previouslyFormattedCitation":"(Dominguez et al., 2015)"},"properties":{"noteIndex":0},"schema":""}(Dominguez et al., 2015) and ETS-1 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/377639a0","ISBN":"0028-0836 (Print)\\r0028-0836 (Linking)","ISSN":"0028-0836","PMID":"7566177","abstract":"The Ets-1 proto-oncogene is a member of the Ets family of eukaryotic transcription factors. Members of this family play important roles in regulating gene expression in response to multiple developmental and mitogenic signals. Ets-1 is preferentially expressed at high levels in B and T cells of adult mice and is regulated during both thymocyte development and T-cell activation. To study the role of Ets-1 in T-cell development and function we have used the RAG-2-/- complementation system and murine embryonic stem (ES) cells containing homozygous deletions in the Ets-1 gene (Ets-1-/-). Ets-1-/(-)-RAG-2-/- chimaeric mice displayed markedly decreased numbers of mature thymocytes and peripheral T cells. Ets-1-/- T cells expressed normal levels of CD3 and T-cell antigen receptor (TCR)-alpha/beta. However, they displayed a severe proliferative defect in response to multiple activational signals and demonstrated increased rates of spontaneous apoptosis in vitro. These findings demonstrate that Ets-1 is required for the normal survival and activation of murine T cells.","author":[{"dropping-particle":"","family":"Muthusamy","given":"Natarajan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Barton","given":"Kevin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Leiden","given":"Jeffrey","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"M.","given":"","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature","id":"ITEM-1","issue":"6550","issued":{"date-parts":[["1995","10","19"]]},"page":"639-642","publisher":"Nature Publishing Group","title":"Defective activation and survival of T cells lacking the Ets-1 transcription factor","type":"article-journal","volume":"377"},"uris":[""]}],"mendeley":{"formattedCitation":"(Muthusamy et al., 1995)","plainTextFormattedCitation":"(Muthusamy et al., 1995)","previouslyFormattedCitation":"(Muthusamy et al., 1995)"},"properties":{"noteIndex":0},"schema":""}(Muthusamy et al., 1995)) or those that are involved in establishing and maintaining tissue residency (RBPJ, a key player in Notch signaling ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3589","ISBN":"1529-2916 (Electronic)\n1529-2908 (Linking)","ISSN":"15292916","PMID":"28102212","abstract":"Tissue-resident memory T cells (TRM cells) in the airways mediate protection against respiratory infection. We characterized TRM cells expressing integrin [alpha]E (CD103) that reside within the epithelial barrier of human lungs. These cells had specialized profiles of chemokine receptors and adhesion molecules, consistent with their unique localization. Lung TRM cells were poised for rapid responsiveness by constitutive expression of deployment-ready mRNA encoding effector molecules, but they also expressed many inhibitory regulators, suggestive of programmed restraint. A distinct set of transcription factors was active in CD103+ TRM cells, including Notch. Genetic and pharmacological experiments with mice revealed that Notch activity was required for the maintenance of CD103+ TRM cells. We have thus identified specialized programs underlying the residence, persistence, vigilance and tight control of human lung TRM cells.","author":[{"dropping-particle":"","family":"Hombrink","given":"Pleun","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Helbig","given":"Christina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Backer","given":"Ronald A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Piet","given":"Berber","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Oja","given":"Anna E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Stark","given":"Regina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Brasser","given":"Giso","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jongejan","given":"Aldo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jonkers","given":"René E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nota","given":"Benjamin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Basak","given":"Onur","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clevers","given":"Hans C.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Moerland","given":"Perry D.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Amsen","given":"Derk","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lier","given":"René A.W.","non-dropping-particle":"Van","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"12","issued":{"date-parts":[["2016","10","24"]]},"page":"1467-1478","publisher":"Nature Research","title":"Programs for the persistence, vigilance and control of human CD8 + lung-resident memory T cells","type":"article-journal","volume":"17"},"uris":[""]}],"mendeley":{"formattedCitation":"(Hombrink et al., 2016)","plainTextFormattedCitation":"(Hombrink et al., 2016)","previouslyFormattedCitation":"(Hombrink et al., 2016)"},"properties":{"noteIndex":0},"schema":""}(Hombrink et al., 2016), and BLIMP1 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/science.aad2035","ISSN":"0036-8075","PMID":"27102484","abstract":"Tissue-resident memory T (Trm) cells permanently localize to portals of pathogen entry, where they provide immediate protection against reinfection. To enforce tissue retention, Trm cells up-regulate CD69 and down-regulate molecules associated with tissue egress; however, a Trm-specific transcriptional regulator has not been identified. Here, we show that the transcription factor Hobit is specifically up-regulated in Trm cells and, together with related Blimp1, mediates the development of Trm cells in skin, gut, liver, and kidney in mice. The Hobit-Blimp1 transcriptional module is also required for other populations of tissue-resident lymphocytes, including natural killer T (NKT) cells and liver-resident NK cells, all of which share a common transcriptional program. Our results identify Hobit and Blimp1 as central regulators of this universal program that instructs tissue retention in diverse tissue-resident lymphocyte populations.","author":[{"dropping-particle":"","family":"Mackay","given":"L. 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TRM cells in cluster 2 also strongly expressed ENTPD1 (Fig. 4 A,B), which encodes CD39, an ectonucleotidase that cleaves ATP, which may protect this TRM subset from ATP-induced cell death in the ATP-rich tumor microenvironment ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1084/jem.20162115","ISSN":"1540-9538","PMID":"28526759","abstract":"The liver provides a tolerogenic immune niche exploited by several highly prevalent pathogens as well as by primary and metastatic tumors. We have sampled healthy and hepatitis B virus (HBV)-infected human livers to probe for a subset of T cells specialized to overcome local constraints and mediate immunity. We characterize a population of T-bet(lo)Eomes(lo)Blimp-1(hi)Hobit(lo) T cells found within the intrahepatic but not the circulating memory CD8 T cell pool expressing liver-homing/retention markers (CD69(+)CD103(+) CXCR6(+)CXCR3(+)). These tissue-resident memory T cells (TRM) are preferentially expanded in patients with partial immune control of HBV infection and can remain in the liver after the resolution of infection, including compartmentalized responses against epitopes within all major HBV proteins. Sequential IL-15 or antigen exposure followed by TGFβ induces liver-adapted TRM, including their signature high expression of exhaustion markers PD-1 and CD39. 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Sentinels for hepatotropic infection.","type":"article-journal","volume":"214"},"uris":[""]}],"mendeley":{"formattedCitation":"(Pallett et al., 2017)","plainTextFormattedCitation":"(Pallett et al., 2017)","previouslyFormattedCitation":"(Pallett et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Pallett et al., 2017) and has recently been shown to be enriched for tumor neo-antigen-specific CTLs ADDIN CSL_CITATION 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Patients and tumours may respond unpredictably to immunotherapy partly owing to heterogeneity of the immune composition and phenotypic profiles of tumour-infiltrating lymphocytes (TILs) within individual tumours and between patients5,6. Although there is evidence that tumour-mutation-derived neoantigen-specific T cells play a role in tumour control2,4,7–10, in most cases the antigen specificities of phenotypically diverse tumour-infiltrating T cells are largely unknown. Here we show that human lung and colorectal cancer CD8+ TILs can?not only be specific for tumour antigens (for example, neoantigens), but also recognize a wide range of epitopes unrelated to cancer (such as those from Epstein–Barr virus, human cytomegalovirus or influenza virus). We found that these bystander CD8+ TILs have diverse phenotypes that overlap with tumour-specific cells, but lack CD39 expression. In colorectal and lung tumours, the absence of CD39 in CD8+ TILs defines populations that lack hallmarks of chronic antigen stimulation at the tumour site, supporting their classification as bystanders. Expression of CD39 varied markedly between patients, with some patients having predominantly CD39? CD8+ TILs. Furthermore, frequencies of CD39 expression among CD8+ TILs correlated with several important clinical parameters, such as the mutation status of?lung tumour epidermal growth factor receptors. Our results demonstrate that not all tumour-infiltrating T cells are specific for tumour antigens, and suggest that measuring CD39 expression could be a straightforward way to quantify or isolate bystander T cells.","author":[{"dropping-particle":"","family":"Simoni","given":"Yannick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Becht","given":"Etienne","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Fehlings","given":"Michael","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Loh","given":"Chiew Yee","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Koo","given":"Si-Lin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Teng","given":"Karen Wei Weng","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yeong","given":"Joe Poh Sheng","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nahar","given":"Rahul","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Tong","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kared","given":"Hassen","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Duan","given":"Kaibo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ang","given":"Nicholas","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Poidinger","given":"Michael","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lee","given":"Yin Yeng","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Larbi","given":"Anis","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Khng","given":"Alexis J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tan","given":"Emile","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Fu","given":"Cherylin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mathew","given":"Ronnie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Teo","given":"Melissa","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lim","given":"Wan Teck","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Toh","given":"Chee Keong","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ong","given":"Boon-Hean","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Koh","given":"Tina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hillmer","given":"Axel M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Takano","given":"Angela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lim","given":"Tony Kiat Hon","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tan","given":"Eng Huat","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhai","given":"Weiwei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tan","given":"Daniel S W","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tan","given":"Iain Beehuat","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Newell","given":"Evan W","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature","id":"ITEM-2","issue":"7706","issued":{"date-parts":[["2018"]]},"page":"575-579","title":"Bystander CD8+ T cells are abundant and phenotypically distinct in human tumour infiltrates","type":"article-journal","volume":"557"},"uris":[""]}],"mendeley":{"formattedCitation":"(Duhen et al., 2018; Simoni et al., 2018)","plainTextFormattedCitation":"(Duhen et al., 2018; Simoni et al., 2018)","previouslyFormattedCitation":"(Duhen et al., 2018; Simoni et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Duhen et al., 2018; Simoni et al., 2018). This expression pattern likely confers highly effective and sustained anti-tumor immune function; in combination with earlier results, we conclude that this TIM-3+IL7R– TRM subset likely represents TAA-specific cells that were enriched for transcripts linked to cytotoxicity.Intriguingly, TRM cells in cluster 2 (TIM-3+IL7R– subset) expressed the highest levels of PDCD1 transcripts (Fig. 4 A) and were enriched for transcripts encoding other molecules linked to inhibitory functions such as TIM-3, TIGIT ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.2850","ISBN":"1529-2916 (Electronic)\\r1529-2908 (Linking)","ISSN":"15292916","PMID":"24658051","abstract":"CD96, CD226 (DNAM-1) and TIGIT belong to an emerging family of receptors that interact with nectin and nectin-like proteins. CD226 activates natural killer (NK) cell-mediated cytotoxicity, whereas TIGIT reportedly counterbalances CD226. In contrast, the role of CD96, which shares the ligand CD155 with CD226 and TIGIT, has remained unclear. In this study we found that CD96 competed with CD226 for CD155 binding and limited NK cell function by direct inhibition. As a result, Cd96(-/-) mice displayed hyperinflammatory responses to the bacterial product lipopolysaccharide (LPS) and resistance to carcinogenesis and experimental lung metastases. Our data provide the first description, to our knowledge, of the ability of CD96 to negatively control cytokine responses by NK cells. Blocking CD96 may have applications in pathologies in which NK cells are important.","author":[{"dropping-particle":"","family":"Chan","given":"Christopher J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Martinet","given":"Ludovic","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gilfillan","given":"Susan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Souza-Fonseca-Guimaraes","given":"Fernando","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chow","given":"Melvyn T","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Town","given":"Liam","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ritchie","given":"David S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Colonna","given":"Marco","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Andrews","given":"Daniel M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Smyth","given":"Mark J","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"5","issued":{"date-parts":[["2014","3","23"]]},"page":"431-438","publisher":"Nature Publishing Group","title":"The receptors CD96 and CD226 oppose each other in the regulation of natural killer cell functions","type":"article-journal","volume":"15"},"uris":[""]}],"mendeley":{"formattedCitation":"(Chan et al., 2014)","plainTextFormattedCitation":"(Chan et al., 2014)","previouslyFormattedCitation":"(Chan et al., 2014)"},"properties":{"noteIndex":0},"schema":""}(Chan et al., 2014), and CTLA4 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nrc3239","ISBN":"1474-1768 (Electronic)\\r1474-175X (Linking)","ISSN":"1474-1768","PMID":"22437870","abstract":"Among the most promising approaches to activating therapeutic antitumour immunity is the blockade of immune checkpoints. Immune checkpoints refer to a plethora of inhibitory pathways hardwired into the immune system that are crucial for maintaining self-tolerance and modulating the duration and amplitude of physiological immune responses in peripheral tissues in order to minimize collateral tissue damage. It is now clear that tumours co-opt certain immune-checkpoint pathways as a major mechanism of immune resistance, particularly against T cells that are specific for tumour antigens. Because many of the immune checkpoints are initiated by ligand-receptor interactions, they can be readily blocked by antibodies or modulated by recombinant forms of ligands or receptors. Cytotoxic T-lymphocyte-associated antigen 4 (CTLA4) antibodies were the first of this class of immunotherapeutics to achieve US Food and Drug Administration (FDA) approval. Preliminary clinical findings with blockers of additional immune-checkpoint proteins, such as programmed cell death protein 1 (PD1), indicate broad and diverse opportunities to enhance antitumour immunity with the potential to produce durable clinical responses.","author":[{"dropping-particle":"","family":"Pardoll","given":"Drew M.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature reviews. Cancer","id":"ITEM-1","issue":"4","issued":{"date-parts":[["2012","4","1"]]},"page":"252-264","publisher":"Nature Publishing Group","title":"The blockade of immune checkpoints in cancer immunotherapy.","type":"article-journal","volume":"12"},"uris":[""]}],"mendeley":{"formattedCitation":"(Pardoll, 2012)","plainTextFormattedCitation":"(Pardoll, 2012)","previouslyFormattedCitation":"(Pardoll, 2012)"},"properties":{"noteIndex":0},"schema":""}(Pardoll, 2012), and inhibitors of TCR-induced signaling and activation, like CBLB, SLAP, DUSP4, PTPN22 and NR3C1 (glucocorticoid receptor) (Figs. 4 A-C and S3 A)ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.4049/jimmunol.1501200","ISSN":"0022-1767","PMID":"26416283","abstract":"Previously, we demonstrated that CD28 and CTLA-4 signaling control Casitas-B-lineage lymphoma (Cbl)-b protein expression, which is critical for T cell activation and tolerance induction. However, the molecular mechanism(s) of this regulation remains to be elucidated. In this study, we found that Cbl-b fails to undergo tyrosine phosphorylation upon CD3 stimulation because SHP-1 is recruited to and dephosphorylates Cbl-b, whereas CD28 costimulation abrogates this interaction. In support of this finding, T cells lacking SHP-1 display heightened tyrosine phosphorylation and ubiquitination of Cbl-b upon TCR stimulation, which correlates with decreased levels of Cbl-b protein. The aberrant Th2 phenotype observed in T cell-specific Shp1(-/-) mice is reminiscent of heightened Th2 response in Cblb(-/-) mice. Indeed, overexpressing Cbl-b in T cell-specific Shp1(-/-) T cells not only inhibits heightened Th2 differentiation in vitro, but also Th2 responses and allergic airway inflammation in vivo. Therefore, SHP-1 regulates Cbl-b-mediated T cell responses by controlling its tyrosine phosphorylation and ubiquitination.","author":[{"dropping-particle":"","family":"Xiao","given":"Yun","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Qiao","given":"Guilin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tang","given":"Juan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tang","given":"Rong","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Guo","given":"Hui","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Warwar","given":"Samantha","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Langdon","given":"Wallace Y","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tao","given":"Lijian","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Jian","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"The Journal of Immunology","id":"ITEM-1","issue":"9","issued":{"date-parts":[["2015","11","1"]]},"page":"4218-4227","publisher":"NIH Public Access","title":"Protein Tyrosine Phosphatase SHP-1 Modulates T Cell Responses by Controlling Cbl-b Degradation","type":"article-journal","volume":"195"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1002/eji.201041295","ISSN":"00142980","PMID":"22101742","abstract":"The differentiation and activation of T cells are critically modulated by MAP kinases, which are in turn feed-back regulated by dual-specificity phosphatases (DUSPs) to determine the duration and magnitude of MAP kinase activation. DUSP4 (also known as MKP2) is a MAP kinase-induced DUSP member that is dynamically expressed during thymocyte differentiation. We generated DUSP4-deficient mice to study the function of DUSP4 in T-cell development and activation. Our results show that thymocyte differentiation and activation-induced MAP kinase phosphorylation were comparable between DUSP4-deficient and WT mice. Interestingly, activated DUSP4(-/-) CD4(+) T cells were hyperproliferative while DUSP4(-/-) CD8(+) T cells proliferated normally. Further mechanistic studies suggested that the hyperproliferation of DUSP4(-/-) CD4(+) T cells resulted from enhanced CD25 expression and IL-2 signaling through increased STAT5 phosphorylation. Immunization of DUSP4(-/-) mice recapitulated the T-cell hyperproliferation phenotype in antigen recall responses, while the profile of Th1/Th2-polarized antibody production was not altered. Overall, these results suggest that other DUSPs may compensate for DUSP4 deficiency in T-cell development, MAP kinase regulation, and Th1/Th2-mediated antibody responses. More importantly, our data indicate that DUSP4 suppresses CD4(+) T-cell proliferation through novel regulations in STAT5 phosphorylation and IL-2 signaling.","author":[{"dropping-particle":"","family":"Huang","given":"Ching-Yu","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lin","given":"Yu-Chun","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hsiao","given":"Wan-Yi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Liao","given":"Fang-Hsuean","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Huang","given":"Pau-Yi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tan","given":"Tse-Hua","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"European Journal of Immunology","id":"ITEM-2","issue":"2","issued":{"date-parts":[["2012","2"]]},"page":"476-488","title":"DUSP4 deficiency enhances CD25 expression and CD4 ⁺ T-cell proliferation without impeding T-cell development","type":"article-journal","volume":"42"},"uris":[""]},{"id":"ITEM-3","itemData":{"DOI":"10.1073/pnas.1617115114","ISBN":"1091-6490 (Electronic) 0027-8424 (Linking)","ISSN":"0027-8424","PMID":"28049829","abstract":"Pregnancy is one of the strongest inducers of immunological tolerance. Disease activity of many autoimmune diseases including multiple sclerosis (MS) is temporarily suppressed by pregnancy, but little is known about the underlying molecular mechanisms. Here, we investigated the endocrine regulation of conventional and regulatory T cells (Tregs) during reproduction. In vitro, we found the pregnancy hormone progesterone to robustly increase Treg frequencies via promiscuous binding to the glucocorticoid receptor (GR) in T cells. In vivo, T-cell–specific GR deletion in pregnant animals undergoing experimental autoimmune encephalomyelitis (EAE), the animal model of MS, resulted in a reduced Treg increase and a selective loss of pregnancy-induced protection, whereas reproductive success was unaffected. Our data imply that steroid hormones can shift the immunological balance in favor of Tregs via differential engagement of the GR in T cells. This newly defined mechanism confers protection from autoimmunity during pregnancy and represents a potential target for future therapy.","author":[{"dropping-particle":"","family":"Engler","given":"Jan Broder","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kursawe","given":"Nina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Solano","given":"María Emilia","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Patas","given":"Kostas","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wehrmann","given":"Sabine","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Heckmann","given":"Nina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lühder","given":"Fred","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Reichardt","given":"Holger M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Arck","given":"Petra Clara","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gold","given":"Stefan M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friese","given":"Manuel A","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Proceedings of the National Academy of Sciences","id":"ITEM-3","issue":"2","issued":{"date-parts":[["2017","1","10"]]},"page":"E181-E190","publisher":"National Academy of Sciences","title":"Glucocorticoid receptor in T cells mediates protection from autoimmunity in pregnancy","type":"article-journal","volume":"114"},"uris":[""]}],"mendeley":{"formattedCitation":"(Xiao et al., 2015; Huang et al., 2012; Engler et al., 2017)","plainTextFormattedCitation":"(Xiao et al., 2015; Huang et al., 2012; Engler et al., 2017)","previouslyFormattedCitation":"(Xiao et al., 2015; Huang et al., 2012; Engler et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Xiao et al., 2015; Huang et al., 2012; Engler et al., 2017). Nonetheless, these TRM cells expressed high transcript levels for cytotoxicity molecules (Perforin, Granzyme A and Granzyme B) and several co-stimulatory molecules such as 4-1BB, ICOS and GITR (TNFRSF18) (Figs. 4 C and S3 A) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nrc3239","ISBN":"1474-1768 (Electronic)\\r1474-175X (Linking)","ISSN":"1474-1768","PMID":"22437870","abstract":"Among the most promising approaches to activating therapeutic antitumour immunity is the blockade of immune checkpoints. Immune checkpoints refer to a plethora of inhibitory pathways hardwired into the immune system that are crucial for maintaining self-tolerance and modulating the duration and amplitude of physiological immune responses in peripheral tissues in order to minimize collateral tissue damage. It is now clear that tumours co-opt certain immune-checkpoint pathways as a major mechanism of immune resistance, particularly against T cells that are specific for tumour antigens. Because many of the immune checkpoints are initiated by ligand-receptor interactions, they can be readily blocked by antibodies or modulated by recombinant forms of ligands or receptors. Cytotoxic T-lymphocyte-associated antigen 4 (CTLA4) antibodies were the first of this class of immunotherapeutics to achieve US Food and Drug Administration (FDA) approval. Preliminary clinical findings with blockers of additional immune-checkpoint proteins, such as programmed cell death protein 1 (PD1), indicate broad and diverse opportunities to enhance antitumour immunity with the potential to produce durable clinical responses.","author":[{"dropping-particle":"","family":"Pardoll","given":"Drew M.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature reviews. Cancer","id":"ITEM-1","issue":"4","issued":{"date-parts":[["2012","4","1"]]},"page":"252-264","publisher":"Nature Publishing Group","title":"The blockade of immune checkpoints in cancer immunotherapy.","type":"article-journal","volume":"12"},"uris":[""]}],"mendeley":{"formattedCitation":"(Pardoll, 2012)","plainTextFormattedCitation":"(Pardoll, 2012)","previouslyFormattedCitation":"(Pardoll, 2012)"},"properties":{"noteIndex":0},"schema":""}(Pardoll, 2012). This co-expression program appeared to be specific to the tumor TRM compartment, given it was also reflected in a SAVER-imputed ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/s41592-018-0033-z","ISSN":"1548-7105","abstract":"In single-cell RNA sequencing (scRNA-seq) studies, only a small fraction of the transcripts present in each cell are sequenced. This leads to unreliable quantification of genes with low or moderate expression, which hinders downstream analysis. To address this challenge, we developed SAVER (single-cell analysis via expression recovery), an expression recovery method for unique molecule index (UMI)-based scRNA-seq data that borrows information across genes and cells to provide accurate expression estimates for all genes.","author":[{"dropping-particle":"","family":"Huang","given":"Mo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wang","given":"Jingshu","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Torre","given":"Eduardo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Dueck","given":"Hannah","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Shaffer","given":"Sydney","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bonasio","given":"Roberto","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Murray","given":"John I","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Raj","given":"Arjun","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Li","given":"Mingyao","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Nancy R","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Methods","id":"ITEM-1","issue":"7","issued":{"date-parts":[["2018"]]},"page":"539-542","title":"SAVER: gene expression recovery for single-cell RNA sequencing","type":"article-journal","volume":"15"},"uris":[""]}],"mendeley":{"formattedCitation":"(Huang et al., 2018)","plainTextFormattedCitation":"(Huang et al., 2018)","previouslyFormattedCitation":"(Huang et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Huang et al., 2018) co-expression profile being identified specifically in the TRM subsets, but not the non-TRM subsets (Fig. S3 B). In addition, direct comparison (Methods) of the transcriptome of all PDCD1-expressing TRM cells versus. the non-TRM cells present in tumor, confirmed that PDCD1+ TRM cells displayed significantly higher expression of transcripts linked to effector function (IFNG, CXCL13, GZMB, CCL3) when compared to PDCD1+ non-TRM cells and to CTLs not expressing PDCD1 (Fig. 4 D and Table S7). More specifically PDCD1+ TRM cells that also co-expressed TIM-3 (cells in cluster 2) showed the highest expression levels of effector molecules compared to other subsets (Fig. 4D). Overall, these findings agree with the bulk RNA-seq analysis, indicating that in TRM cells expression of particular inhibitory molecules, such as PD-1 and TIM-3, does not reflect exhaustion.PD-1- and TIM-3-expressing tumor-infiltrating TRM cells are not exhausted To further address whether PDCD1-expressing TRM cells in cluster 2 (TIM-3+IL7R– TRM cells) were exhausted, or functionally active, we performed single-cell RNA-seq in tumor-infiltrating TRM and non-TRM cells, using the more sensitive Smart-seq2 assay (Table S1). This also enabled paired transcriptomic and TCR clonotype analysis ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-1","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1038/nprot.2014.006","ISSN":"1754-2189","abstract":"Emerging methods for the accurate quantification of gene expression in individual cells hold promise for revealing the extent, function and origins of cell-to-cell variability. Different high-throughput methods for single-cell RNA-seq have been introduced that vary in coverage, sensitivity and multiplexing ability. We recently introduced Smart-seq for transcriptome analysis from single cells, and we subsequently optimized the method for improved sensitivity, accuracy and full-length coverage across transcripts. Here we present a detailed protocol for Smart-seq2 that allows the generation of full-length cDNA and sequencing libraries by using standard reagents. The entire protocol takes ～2 d from cell picking to having a final library ready for sequencing; sequencing will require an additional 1–3 d depending on the strategy and sequencer. The current limitations are the lack of strand specificity and the inability to detect nonpolyadenylated (polyA?) RNA.","author":[{"dropping-particle":"","family":"Picelli","given":"Simone","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Faridani","given":"Omid R","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bj?rklund","given":"?sa K","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Winberg","given":"G?sta","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sagasser","given":"Sven","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sandberg","given":"Rickard","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Protocols","id":"ITEM-2","issue":"1","issued":{"date-parts":[["2014","1","2"]]},"page":"171-181","publisher":"Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.","title":"Full-length RNA-seq from single cells using Smart-seq2","type":"article-journal","volume":"9"},"uris":[""]}],"mendeley":{"formattedCitation":"(Patil et al., 2018; Picelli et al., 2014)","plainTextFormattedCitation":"(Patil et al., 2018; Picelli et al., 2014)","previouslyFormattedCitation":"(Patil et al., 2018; Picelli et al., 2014)"},"properties":{"noteIndex":0},"schema":""}(Patil et al., 2018; Picelli et al., 2014). We reconstructed the TCRβ chains (Methods) in 80.5% of single cells, the TCRα chain in 76.6%, and both chains in 66.6% of cells (Table S8). As expected, clonally expanded tumor-infiltrating TRM cells, which are likely to be reactive to TAA, were significantly enriched for genes specific to TIM-3+IL7R– TRM cells (Fig. 5 A and Table S7). Among tumor-infiltrating CTLs, a greater proportion of TIM-3-expressing (Methods) TRM cells were clonally expanded compared with other TRM and non-TRM cells (Fig. 5 B). Furthermore, TIM-3-expressing TRM cells were significantly enriched for key effector cytokines and cytotoxicity transcripts (Table S9), despite expressing significantly higher levels of PDCD1 (Fig. 5 C). The higher sensitivity of the SMART-seq2 assay compared to the high-throughput 10X genomics platform also allowed co-expression analysis due to lower dropout rates ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-1","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]}],"mendeley":{"formattedCitation":"(Patil et al., 2018)","plainTextFormattedCitation":"(Patil et al., 2018)","previouslyFormattedCitation":"(Patil et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Patil et al., 2018). Co-expression analysis showed that expression of PDCD1 and HAVCR2 (TIM-3) correlated with that of activation markers (TNFRSF9 and CD74), IFNG and cytotoxicity-related transcripts more strongly in TRM cells when compared with non-TRM cells (Fig. 5 D). Specifically, IFNG and PDCD1 expression levels were better correlated in TIM-3-expressing TRM cells compared with all TRM cells and non-TRM cells (Fig. 5 D and Table S10), and the proportion of cells strongly co-expressing these transcripts was notably higher (30.3% versus. 9.2% versus. 0.6%, Fig. 5 E). Furthermore, in concordance with our high-throughput single-cell RNA-seq assays, this higher resolution analysis verified that IFNG, alongside additional effector molecule-associated transcripts (CXCL13, CCL3, GZMB and PRF1) were particularly enriched in the TIM-3+ TRM versus. the TIM-3– TRM cells, and both the PDCD1+ and PDCD1– non-TRM cells (Figs. 4 D and 5 F,G). Overall, these results strongly support that PD-1 and TIM-3 expressing tumor-infiltrating TRM cells were not exhausted, but instead were enriched for transcripts (IFNG, PRF1, GZMB) encoding for molecules linked to effector functions.In keeping with our transcriptomic assays, when stimulated ex-vivo, the percentage of tumor-infiltrating TRM cells that co-expressed PD-1 (stained before stimulation) and effector cytokines was significantly higher, when compared to the non-TRM CTLs (Fig. 5 H) (Gating previously reported ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3775","ISSN":"1529-2908","PMID":"28628092","abstract":"Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.","author":[{"dropping-particle":"","family":"Ganesan","given":"Anusha-Preethi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garrido-Martin","given":"Eva M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alzetani","given":"Aiman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friedmann","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2017","6","19"]]},"page":"940-950","title":"Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer","type":"article-journal","volume":"18"},"uris":[""]}],"mendeley":{"formattedCitation":"(Ganesan et al., 2017)","plainTextFormattedCitation":"(Ganesan et al., 2017)","previouslyFormattedCitation":"(Ganesan et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Ganesan et al., 2017)). Analysis directly ex-vivo demonstrated there was also greater co-expression of PD-1 and cytotoxic-associated proteins, granzyme A and granzyme B, in the TRM cells when compared to the non-TRM CTLs in the tumor (Fig. 5 I). These data verify that PD-1 expression in the TRM subset of tumor-infiltrating CTLs does not necessarily reflect dysfunctional properties.Surface TIM-3+IL-7R– status uniquely characterizes a set of tumor TRM cellsWe next evaluated the protein expression of selected molecules to better discern the tumor-infiltrating TRM subsets. Multi-parameter protein analysis of CTLs (Methods) present in tumors and adjacent normal lung revealed a subset of TRM (CD103+) cells localized distinctly when the data was visualized in 2D space (Fig. 6 A). This subset consisted of tumor TRM cells only from tumor tissue (purple circle, Fig. 6 A), and uniquely expressed high levels of TIM-3 and lacked IL-7R, indicating that this cluster is the same as the TIM-3-expressing tumor TRM cluster (cluster 2) identified by single-cell RNA analysis (Fig. 6 B). Consistent with the single-cell transcriptome analysis, the TIM-3-expressing TRM cluster was unique to the TRM cells isolated from the tumor and expressed higher levels of CD39, PD-1 and 4-1BB (Fig. 6 A, C). PD-1 and TIM-3 expression levels were also positively correlated with expression of 4-1BB, which is expressed following TCR engagement by antigen ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.cell.2016.09.050","ISBN":"1097-4172 (Electronic)\\r0092-8674 (Linking)","ISSN":"00928674","PMID":"27773482","abstract":"FOXP3+ regulatory T cells (Tregs) maintain tolerance against self-antigens and innocuous environmental antigens. However, it is still unknown whether Treg-mediated tolerance is antigen specific and how Treg specificity contributes to the selective loss of tolerance, as observed in human immunopathologies such as allergies. Here, we used antigen-reactive T cell enrichment to identify antigen-specific human Tregs. We demonstrate dominant Treg-mediated tolerance against particulate aeroallergens, such as pollen, house dust mites, and fungal spores. Surprisingly, we found no evidence of functional impairment of Treg responses in allergic donors. Rather, major allergenic proteins, known to rapidly dissociate from inhaled allergenic particles, have a generally reduced capability to generate Treg responses. Most strikingly, in individual allergic donors, Th2 cells and Tregs always target disparate proteins. Thus, our data highlight the importance of Treg antigen-specificity for tolerance in humans and identify antigen-specific escape from Treg control as an important mechanism enabling antigen-specific loss of tolerance in human allergy.","author":[{"dropping-particle":"","family":"Bacher","given":"Petra","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Heinrich","given":"Frederik","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Stervbo","given":"Ulrik","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nienen","given":"Mikalai","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vahldieck","given":"Marco","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Iwert","given":"Christina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vogt","given":"Katrin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kollet","given":"Jutta","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Babel","given":"Nina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sawitzki","given":"Birgit","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schwarz","given":"Carsten","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bereswill","given":"Stefan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Heimesaat","given":"Markus M.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Heine","given":"Guido","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gadermaier","given":"Gabriele","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Asam","given":"Claudia","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Assenmacher","given":"Mario","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kniemeyer","given":"Olaf","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Brakhage","given":"Axel A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ferreira","given":"Fátima","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wallner","given":"Michael","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Worm","given":"Margitta","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Scheffold","given":"Alexander","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Cell","id":"ITEM-1","issue":"4","issued":{"date-parts":[["2016","11"]]},"page":"1067-1078.e16","title":"Regulatory T Cell Specificity Directs Tolerance versus Allergy against Aeroantigens in Humans","type":"article-journal","volume":"167"},"uris":[""]}],"mendeley":{"formattedCitation":"(Bacher et al., 2016)","plainTextFormattedCitation":"(Bacher et al., 2016)","previouslyFormattedCitation":"(Bacher et al., 2016)"},"properties":{"noteIndex":0},"schema":""}(Bacher et al., 2016) (Fig. 6 D,E), indicating that these cells are highly enriched for TAA-specific cells. TIM-3-expressing CTLs were also detected among tumor-infiltrating TRM cells isolated from both treatment na?ve lung cancer and head and neck squamous cell carcinoma (HNSCC) samples (Fig. 6 F), but not among non-TRM cells in these treatment na?ve tumors or TRM cells in lung. Multi-color immunohistochemistry was used to confirm the presence of TIM-3-expressing TRM cells in lung tumor samples, which also showed enrichment of this subset in TILhiTRMhi “immune hot” tumors (Fig. 6 G, H and Table S11). These findings confirmed, at the protein level, the restriction of the TIM-3+IL-7R– TRM subset to tumors from two cancer types. Single-cell transcriptome analysis of CTLs from anti-PD-1 responders We next analyzed tumor-infiltrating T cells from 19 biopsies (Table S1) with known divergent responses to anti-PD-1 therapy. Flow cytometry analysis of tumor TRM cells isolated from responding patients pre-, during- and post-treatment, showed increased proportion of TIM-3+IL-7R– TRM cells compared to the tumor TRM cells from our cohort of treatment na?ve lung cancer patients and those not responding to anti-PD-1 (median ~70% versus. ~24% and ~19%, respectively; Figs. 7 A and S4 A). This population also expressed high levels of PD-1 in samples, pre-anti-PD-1 therapy that was diminished post-treatment likely reflective of the clinical antibody blocking flow cytometric analysis ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nature22079","ISSN":"1476-4687","abstract":"Despite the success of monotherapies based on blockade of programmed cell death 1 (PD-1) in human melanoma, most patients do not experience durable clinical benefit. Pre-existing T-cell infiltration and/or the presence of PD-L1 in tumours may be used as indicators of clinical response; however, blood-based profiling to understand the mechanisms of PD-1 blockade has not been widely explored. Here we use immune profiling of peripheral blood from patients with stage IV melanoma before and after treatment with the PD-1-targeting antibody pembrolizumab and identify pharmacodynamic changes in circulating exhausted-phenotype CD8 T cells (T(ex) cells). Most of the patients demonstrated an immunological response to pembrolizumab. Clinical failure in many patients was not solely due to an inability to induce immune reinvigoration, but rather resulted from an imbalance between T-cell reinvigoration and tumour burden. The magnitude of reinvigoration of circulating T(ex) cells determined in relation to pretreatment tumour burden correlated with clinical response. By focused profiling of a mechanistically relevant circulating T-cell subpopulation calibrated to pretreatment disease burden, we identify a clinically accessible potential on-treatment predictor of response to PD-1 blockade.","author":[{"dropping-particle":"","family":"Huang","given":"Alexander C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Postow","given":"Michael A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Orlowski","given":"Robert J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mick","given":"Rosemarie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bengsch","given":"Bertram","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Manne","given":"Sasikanth","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Xu","given":"Wei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harmon","given":"Shannon","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Giles","given":"Josephine R","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wenz","given":"Brandon","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Adamow","given":"Matthew","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kuk","given":"Deborah","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Panageas","given":"Katherine S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Carrera","given":"Cristina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wong","given":"Phillip","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Quagliarello","given":"Felix","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wubbenhorst","given":"Bradley","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"D'Andrea","given":"Kurt","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pauken","given":"Kristen E","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Herati","given":"Ramin S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Staupe","given":"Ryan P","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schenkel","given":"Jason M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"McGettigan","given":"Suzanne","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kothari","given":"Shawn","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"George","given":"Sangeeth M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vonderheide","given":"Robert H","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Amaravadi","given":"Ravi K","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Karakousis","given":"Giorgos C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schuchter","given":"Lynn M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Xu","given":"Xiaowei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nathanson","given":"Katherine L","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wolchok","given":"Jedd D","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gangadhar","given":"Tara C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wherry","given":"E John","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature","edition":"2017/04/10","id":"ITEM-1","issue":"7652","issued":{"date-parts":[["2017","5","4"]]},"page":"60-65","title":"T-cell invigoration to tumour burden ratio associated with anti-PD-1 response","type":"article-journal","volume":"545"},"uris":[""]}],"mendeley":{"formattedCitation":"(Huang et al., 2017)","plainTextFormattedCitation":"(Huang et al., 2017)","previouslyFormattedCitation":"(Huang et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Huang et al., 2017) (Fig. 7 B). Given this population had high expression of PD-1 (Figs. 6 A-E and Fig. 7 B), we concluded that these TIM-3+IL-7R– TRM cells are likely to be one of the key immune cell types that respond to anti-PD-1 therapy.To comprehensively evaluate the molecular features and clonality of the CTLs (Fig. S4 A-C and Methods) responding to anti-PD-1 therapy, we performed paired single-cell transcriptomic and TCR analysis of CTLs isolated from biopsies both pre-and post-therapy from two donors. This enabled us to maximize the usage of the material in these small, clinically difficult to obtain biopsies. Differential expression analysis of all CD8+ tumor-infiltrating CTLs revealed a significant enrichment of markers linked to cytotoxic function (PRF1, GZMB and GZMH) and activation (CD38) in post-treatment when compared to pre-treatment samples (Figs. 7 C,D, and Tables S1, S12). Notably, we found increased expression of ITGAE, a marker of TRM cells, in CTLs from post-treatment samples (Fig. 7 C,D). GSEA analysis also showed that tumor-infiltrating T cells from post-treatment samples were enriched for TRM features as well as those linked to TIM3+IL7R– TRM subset (Fig. 7 E and Tables S4, S7). Unbiased co-expression analysis of transcripts from post-treatment CTLs demonstrated that the transcripts linked to cytotoxicity (GZMH) and activation (CD38) clustered together with the TRM marker gene (ITGAE; Fig. 7 F and Table S12). Furthermore, we found several expanded TCR clones that were present before and after therapy (Fig. S4 D, E), which indicated that TIM-3 expressing TRM cells (>87% of the TRM cells in pre-treatment samples) with these clonotypes persisted in-vivo for several weeks during treatment and largely maintained TIM-3 expression in post-treatment samples (>79% of the TRM cells Fig. S4 C). By restricting our analysis to these expanded clones, we found that the expression of GZMB, PRF1, GZMH and CD38 (Fig. S4 F) was increased in CTLs from post-treatment samples, which suggested that tumor-infiltrating CTLs with the same specificity displayed enhanced cytotoxic properties following anti-PD-1 treatment and that TRM cells largely likely contributed to this feature.To provide a further line of evidence for the functional potential of TIM-3+IL-7R– TRM cells and to further characterize their epigenetic profile, we performed OMNI-ATAC-seq ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nmeth.4396","ISBN":"0026101505","ISSN":"15487105","PMID":"28846090","abstract":"We present Omni-ATAC, an improved ATAC-seq protocol for chromatin accessibility profiling that works across multiple applications with substantial improvement of signal-to-background ratio and information content. The Omni-ATAC protocol generates chromatin accessibility profiles from archival frozen tissue samples and 50-μm sections, revealing the activities of disease-associated DNA elements in distinct human brain structures. The Omni-ATAC protocol enables the interrogation of personal regulomes in tissue context and translational studies.","author":[{"dropping-particle":"","family":"Corces","given":"M. 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All Rights Reserved.","title":"An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues","type":"article-journal","volume":"14"},"uris":[""]}],"mendeley":{"formattedCitation":"(Corces et al., 2017)","plainTextFormattedCitation":"(Corces et al., 2017)","previouslyFormattedCitation":"(Corces et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Corces et al., 2017) on purified populations of tumor-infiltrating TIM3+IL7R– TRM and non-TRM subsets pooled from lung cancer patients (n=9, Table S1 and Fig. 6 B). These subsets clustered separately, highlighting the distinct chromatin accessibility profiles of these populations (Fig. 7 G). In keeping with our transcriptomic analyses (Fig. 1 E), we identified greater chromatin accessibility within 5kb of the transcriptional start site of the CD103 (ITGAE) and KLF3 loci, in the TRM and non-TRM compartment, respectively. Furthermore, consistent with single-cell transcriptional data, the TIM3+IL7R–TRM cells when compared to non-TRM cells showed increased chromatin accessibility of genes encoding effector molecules such as granzyme B and IFN-?, despite showing increased accessibility at the PDCD1 (PD-1) and TIM-3 (HAVCR2) loci (Fig. 7 H). Taken together, these epigenetic and transcriptomic data, combined with protein validation highlighted the potential functionality of the TIM-3+IL-7R– TRM cells, which positively correlated with expression of PD-1 specifically in this subset.DISCUSSIONOur bulk and single-cell transcriptomic analysis showed that the molecular program of tumor-infiltrating TRM cells?is substantially distinct from?that observed in the human background lung tissue?or in murine models. The most striking discovery was the identification of a TIM-3+IL-7R– TRM subset present exclusively in tumors. This subset expressed high levels of PD-1 and other molecules previously thought to reflect exhaustion. Surprisingly, however, they proliferated in the tumor milieu, were capable of robust up-regulation of TCR-activation-induced genes and exhibited a transcriptional program indicative of superior effector, survival and tissue residency properties. Functionality may not be truly reflected by transcript expression levels, hence to support the conclusion that PD-1 expression does not reflect exhaustion in TRM cells, we showed that the expression of key effector cytokines, IL-2, TNF and IFN-γ, and cytotoxicity molecules Granzyme A and Granzyme B was increased in PD-1 expressing TRM cells when compared to non-TRM cells. When compared to recent reports on transcriptomic analysis of tumor-infiltrating lymphocytes ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/s41591-018-0078-7","ISSN":"1078-8956","abstract":"The quantity of tumor-infiltrating lymphocytes (TILs) in breast cancer (BC) is a robust prognostic factor for improved patient survival, particularly in triple-negative and HER2-overexpressing BC subtypes 1 . Although T cells are the predominant TIL population 2 , the relationship between quantitative and qualitative differences in T cell subpopulations and patient prognosis remains unknown. We performed single-cell RNA sequencing (scRNA-seq) of 6,311 T cells isolated from human BCs and show that significant heterogeneity exists in the infiltrating T cell population. We demonstrate that BCs with a high number of TILs contained CD8+ T cells with features of tissue-resident memory T (TRM) cell differentiation and that these CD8+ TRM cells expressed high levels of immune checkpoint molecules and effector proteins. A CD8+ TRM gene signature developed from the scRNA-seq data was significantly associated with improved patient survival in early-stage triple-negative breast cancer (TNBC) and provided better prognostication than CD8 expression alone. Our data suggest that CD8+ TRM cells contribute to BC immunosurveillance and are the key targets of modulation by immune checkpoint inhibition. Further understanding of the development, maintenance and regulation of TRM cells will be crucial for successful immunotherapeutic development in BC.","author":[{"dropping-particle":"","family":"Savas","given":"Peter","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Virassamy","given":"Balaji","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ye","given":"Chengzhong","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Salim","given":"Agus","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mintoff","given":"Christopher 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in different CTL subsets in the tumor and challenges the current dogma of PD-1 expression representing dysfunctional T cells in human tumors. While this protein-validated transcriptomic assessment was also corroborated by the results of chromatin accessibility profile, an important caveat is that functional validation was performed using PMA and ionomycin stimulation, which does not fully reflect physiological TCR activation.We defined a core set of genes commonly expressed in both lung and tumor TRM cells, including a number of novel genes whose expression was highly correlated with known tissue residency (TRM) genes. Any of these genes may also be critically important for the development, trafficking or function of lung or lung tumor-infiltrating TRM cells. Some notable examples known or likely to have such functions are GPR25, whose closest homolog, GPR15 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/science.1237013","ISSN":"0036-8075","PMID":"23661644","abstract":"Lymphocyte homing, which contributes to inflammation, has been studied extensively in the small intestine, but there is little known about homing to the large intestine, the site most commonly affected in inflammatory bowel disease. GPR15, an orphan heterotrimeric guanine nucleotide-binding protein (G protein)-coupled receptor, controlled the specific homing of T cells, particularly FOXP3(+) regulatory T cells (Tregs), to the large intestine lamina propria (LILP). GPR15 expression was modulated by gut microbiota and transforming growth factor-β1, but not by retinoic acid. GPR15-deficient mice were prone to develop more severe large intestine inflammation, which was rescued by the transfer of GPR15-sufficient Tregs. Our findings thus describe a T cell-homing receptor for LILP and indicate that GPR15 plays a role in mucosal immune tolerance largely by regulating the influx of Tregs.","author":[{"dropping-particle":"V.","family":"Kim","given":"S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V.","family":"Xiang","given":"W.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kwak","given":"C.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yang","given":"Y.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lin","given":"X. 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Here we identify an epithelial γδ T cell–specific costimulatory molecule, junctional adhesion molecule–like protein (JAML). Binding of JAML to its ligand Coxsackie and adenovirus receptor (CAR) provides costimulation leading to cellular proliferation and cytokine and growth factor production. Inhibition of JAML costimulation leads to diminished γδ T cell activation and delayed wound closure akin to that seen in the absence of γδ T cells. Our results identify JAML as a crucial component of epithelial γδ T cell biology and have broader implications for CAR and JAML in tissue homeostasis and repair.","author":[{"dropping-particle":"","family":"Witherden","given":"Deborah A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Verdino","given":"Petra","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Rieder","given":"Stephanie E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garijo","given":"Olivia","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mills","given":"Robyn E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Teyton","given":"Luc","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Fischer","given":"Wolfgang H.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wilson","given":"Ian A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Havran","given":"Wendy L.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science","id":"ITEM-1","issue":"5996","issued":{"date-parts":[["2010","9","3"]]},"page":"1205-1210","title":"The junctional adhesion molecule JAML is a costimulatory receptor for epithelial γδ T cell activation","type":"article-journal","volume":"329"},"uris":[""]}],"mendeley":{"formattedCitation":"(Witherden et al., 2010)","plainTextFormattedCitation":"(Witherden et al., 2010)","previouslyFormattedCitation":"(Witherden et al., 2010)"},"properties":{"noteIndex":0},"schema":""}(Witherden et al., 2010), encoding JAML (junctional adhesion molecule-like), which contributes to the proliferation and cytokine release of skin-resident ?T cells; and SRGAP3, whose product functions in neuronal migration ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.mod.2012.10.005","ISBN":"0925-4773","ISSN":"09254773","PMID":"23127797","abstract":"The Slit-Robo GTPase activating protein 3 (srGAP3) dynamically regulates cytoskeletal reorganisation through inhibition of the Rho GTPase Rac1 and interaction with actin remodelling proteins. SrGAP3-mediated reorganisation of the actin cytoskeleton is crucial for the normal development of dendritic spines and loss of srGAP3 leads to abnormal synaptic activity and impaired cognitive behaviours in mice, which is reminiscent of an association between disrupted srGAP3 and intellectual disability in humans. Additionally, srGAP3 has been implicated to act downstream of Slit-Robo signalling in commissural axons of the spinal cord. Thus, srGAP3-mediated cytoskeletal reorganisation has an important influence on a variety of neurodevelopmental processes, which may be required for normal cognitive function. ?2012 Elsevier Ireland Ltd.","author":[{"dropping-particle":"","family":"Bacon","given":"Claire","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Endris","given":"Volker","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Rappold","given":"Gudrun A.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Mechanisms of Development","id":"ITEM-1","issue":"6","issued":{"date-parts":[["2013","6","1"]]},"page":"391-395","publisher":"Elsevier","title":"The cellular function of srGAP3 and its role in neuronal morphogenesis","type":"article-journal","volume":"130"},"uris":[""]}],"mendeley":{"formattedCitation":"(Bacon et al., 2013)","plainTextFormattedCitation":"(Bacon et al., 2013)","previouslyFormattedCitation":"(Bacon et al., 2013)"},"properties":{"noteIndex":0},"schema":""}(Bacon et al., 2013). Thus, our study provides a valuable resource for defining molecules that are likely to be important for the development and function of human lung and tumor TRM cells. PDCD1 was a prominent hit in the ‘shared lung tissue residency’ gene list, and its expression was confirmed at the protein level in both lung and tumor TRM cells. The fact that PD-1 was expressed by the majority of the TRM cells isolated from uninvolved lung tissue of subjects with no active infection suggests that PD-1 might be constitutively expressed by these cells, as has been recently described for brain TRM cells ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/icb.2017.62","ISSN":"0818-9641","PMID":"28829048","author":[{"dropping-particle":"","family":"Shwetank","given":"","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Abdelsamed","given":"Hossam A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Frost","given":"Elizabeth L","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmitz","given":"Heather M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mockus","given":"Taryn E","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Youngblood","given":"Ben A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lukacher","given":"Aron E","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Immunology and Cell Biology","id":"ITEM-1","issue":"10","issued":{"date-parts":[["2017"]]},"page":"953-959","publisher":"Nature Publishing Group","title":"Maintenance of PD-1 on brain-resident memory CD8 T cells is antigen independent","type":"article-journal","volume":"95"},"uris":[""]}],"mendeley":{"formattedCitation":"(Shwetank et al., 2017)","plainTextFormattedCitation":"(Shwetank et al., 2017)","previouslyFormattedCitation":"(Shwetank et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Shwetank et al., 2017). Given that TIM-3+IL7R– expressing tumor-infiltrating TRM cells also express substantial levels of PD-1, we speculate that they may be the major cellular targets of anti-PD-1 therapy. We speculate that differences in the magnitude of this population of TRMs could thus be an explanation for the variation in the clinical response to PD-1 inhibitors. We speculate further that the constitutive expression of PD-1 by the majority of TRM cells in the lung tissue and presumably other organs (skin and pituitary gland) raises the possibility that anti-PD-1 therapy may non-specifically activate potentially non-TAA-reactive TRM cells to cause adverse immune reactions such as pneumonitis, dermatitis and hypophysitis ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nm.4321","ISBN":"1520-6890 (Electronic) 0009-2665 (Linking)","ISSN":"1078-8956","PMID":"28475571","abstract":"In this Perspective, June, Bluestone and Warshauer discuss potential cellular and molecular explanations for the autoimmunity often associated with immunotherapy, and propose additional research and changes to reporting practices to aid efforts to understand and minimize these toxic side effects.","author":[{"dropping-particle":"","family":"June","given":"Carl H","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Warshauer","given":"Jeremy T","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bluestone","given":"Jeffrey A","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Medicine","id":"ITEM-1","issue":"5","issued":{"date-parts":[["2017","5","5"]]},"page":"540-547","publisher":"Nature Publishing Group","title":"Is autoimmunity the Achilles' heel of cancer immunotherapy?","type":"article-journal","volume":"23"},"uris":[""]}],"mendeley":{"formattedCitation":"(June et al., 2017)","plainTextFormattedCitation":"(June et al., 2017)","previouslyFormattedCitation":"(June et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(June et al., 2017). Comprehensive analysis of the TRM phenotype and TCR repertoire of CTLs present in tumor and organs affected by adverse reactions may substantiate these hypotheses. A recent study that compared PD-1high versus. other tumor-localized CTL populations demonstrated that the presence of PD-1high cells was predictive of response to anti-PD-1 therapy ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/s41591-018-0057-z","ISSN":"1078-8956","author":[{"dropping-particle":"","family":"Thommen","given":"DS Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Koelzer","given":"VH","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Herzig","given":"P","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Roller","given":"A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Trefny","given":"M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kiialainen","given":"A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hanhart","given":"J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schill","given":"C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hess","given":"C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Savic Prince","given":"S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wiese","given":"M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lardinois","given":"D","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ho","given":"PC","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Klein","given":"C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Karanikas","given":"V","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mertz","given":"KD","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schumacher","given":"TN","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zippelius","given":"A","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Medicine","id":"ITEM-1","issued":{"date-parts":[["2018"]]},"publisher":"Springer US","title":"A transcriptionally and functionally distinct PD-1 + CD8 + T cell pool with predictive potential in non-small cell lung cancer treated with PD-1 blockade","type":"article-journal"},"uris":[""]}],"mendeley":{"formattedCitation":"(Thommen et al., 2018)","plainTextFormattedCitation":"(Thommen et al., 2018)","previouslyFormattedCitation":"(Thommen et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Thommen et al., 2018). However, the authors did not segregate PD-1high cells based on expression of TRM associated molecules, hence this population of cells will have a mixture of PD-1+ non-TRM cells and PD-1+ TRM cells. Our findings have highlighted the profound differences in the properties of PD-1 expressing TRM cells and non-TRM cells. Hence by studying a mixed population without delineating the contribution from PD-1 expressing TRM cells, their study lacked the resolution to highlight the contribution of a specific TRM subsets with transcriptomic features associated with increased functional properties and potential responsiveness to anti-PD-1 therapy. Our findings also raise the question of which molecular players are essential for the generation and maintenance of this TIM-3+IL-R7– subset of TRM cells. Our analysis identified a number of potential transcription factors (e.g., STAT3, ID2, ZEB2, ETS-1) and other molecules (e.g., PTPN22, DUSP4, LAYN, KRT86, CD39) that are uniquely expressed in this subset and could thus be key players in their development or function, further underscoring the utility of the resource generated here. The results herein also provide a rationale for assessing tumor TRM subsets in both early and late phase studies of novel immunotherapies and cancer vaccines to provide early proof of efficacy as well as potential response biomarkers. The TIM-3+IL-7R– TRM subset can be readily isolated from tumor samples using the surface markers we identified, and potentially expanded in vitro to screen and test for TRM-targeted adoptive T cell therapies. Because the TIM-3+IL-7R– TRM subset is likely to be enriched for TAA-specific cells, specifically expanding this TRM subset could improve the efficacy of adoptive T cell therapies. In summary, our studies have provided rich molecular insights into the potential roles of human tumor-infiltrating TRM subsets and thus should pave the way for developing novel approaches to improve TRM immune responses in cancer.AUTHOR CONTRIBUTIONS J.C., A.-P.G., P.S.F., T.S.-E., C.H.O., and P.V. conceived of the work; J.C., O.W., S.E., S.J.C., A.A., C.J.H., K.J.M., performed cell isolations, phenotyping and immunohistochemistry data analysis under the supervision of G.J.T., P.V., and C.H.O.; S.J.C., A.A., K.J.M., E.W. and E.V.K. assisted in patient recruitment, obtaining consent and sample collection; J.C., R.G., S.B., B.P. performed bulk RNA-seq and OMNI-ATAC-seq assays and analysis under the supervision of F.A., P.V.; J.C., D.S., A.M., performed the single-cell experiments and analysis under the supervision of F.A., G.S., P.V; J.C. wrote the first draft of the manuscript that was revised and edited by P.S.F., A.-P.G., F.A., C.H.O., and P.V. ACKNOWLEDGMENTS We thank M. Chamberlain, K. Amer, D. Jeffrey, M. Lane, C. Fixmer, M. Lopez, N. Graham, M. Machado, T. Mellows and B. Johnson for assistance with recruitment of study subjects and processing of samples. We thank D. Chudakov for sharing the detailed protocol for TCR-seq. We recognize C. Kim, L. Boggeman, D. Hinz, C. Dillingham and R. Simmons for their assistance with cell sorting, FACSAria II Cell Sorter S10 RR027366; S. Liang, S. Lisette Rosales and J. Greenbaum for assistance with library preparation, next generation sequencing and bioinformatics at the LJI, using Illumina HiSeq 2500 - NIH #S10OD016262 and NovaSeq6000 #S10OD025052-01). J. Moore, B. Schmiedel, and other members of the laboratory for their assistance with editing the figures and manuscript. Supported by the Wessex Clinical Research Network and the National Institute of Health Research, UK (sample collection), the William K. Bowes Jr Foundation (P.V.), the Cancer Research UK Centres Network Accelerator Award Grant - A21998 (P.V., T.S.-E. and C.H.O.), the Faculty of Medicine of the University of Southampton (P.V., T.S.-E. and C.H.O.) and Cancer Research UK (J.C., E.K., C.H.O.). J.C., S.E., F.A., C.H.O., T.S.-E., and P.V have filed a patent associated with the results presented here. The authors have no additional financial interests.REFERENCESADDIN Mendeley Bibliography CSL_BIBLIOGRAPHY Anders, S., P.T. Pyl, and W. Huber. 2015. HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics. 31:166–169. doi:10.1093/bioinformatics/btu638.Aranda, J.F., N. Reglero-Real, L. Kremer, B. Marcos-Ramiro, A. Ruiz-Saenz, M. Calvo, C. Enrich, I. Correas, J. Millan, and M.A. Alonso. 2011. MYADM regulates Rac1 targeting to ordered membranes required for cell spreading and migration. Mol. Biol. Cell. 22:1252–1262. doi:10.1091/mbc.E10-11-0910.Bacher, P., F. Heinrich, U. Stervbo, M. Nienen, M. 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Lower, waterfall plots represent the DESeq2 normalized fold change from the human lung comparison of genes not significantly (≤ 2-fold, > an adjusted P value of 0.05) differentially expressed between lung TRM (CD103+) and non-TRM (CD103–) CTLs (marked in red font in the Venn diagram). (D) Venn diagram and (E) heat map of RNA-seq analysis of 89 common transcripts (one per row) expressed differentially by lung TRM versus. lung non-TRM, and tumor TRM?versus. tumor non-TRM?(pairwise comparison; change in expression of 2-fold with an adjusted?P?value of ≤ 0.05 (DESeq2 analysis; Benjamini-Hochberg test)), presented as row-wise?z-scores of TPM counts; each column represents an individual sample; known TRM or non-TRM transcripts are indicated. The color scheme and number of samples are identical to (A). (F) Spearman co-expression analysis of the 89 differentially expressed genes as in (D) and (E); values are clustered with complete linkage. (G) Weighted gene co-expression network analysis visualized in Gephi, the nodes are colored and sized according to the number of edges (connections), and the edge thickness is proportional to the edge weight (strength of correlation). (H) Expression values according to RNA-seq data of the indicated differentially expressed genes shared by lung and tumor TRM cells. Each symbol represents an individual sample, the bar represents the mean and colored as in (A), t-line the s.e.m. (I) Flow-cytometry analysis of the expression of PD-1 versus. that of CD103 on live and singlet-gated CD14-CD19–CD20–CD56–CD4–CD45+CD3+CD8+ cells obtained from lung cancer CTLs and matched paired lung CTLs; right, frequency of cell that express PD-1 in the indicated populations (* P ≤ 0.05, ** ≤ 0.01; n = 8; Wilcoxon rank-sum test), each symbol represents a sample, bars represent the mean, t-line the s.e.m, colored as per (A). (J) RNA-seq analysis of genes (row) commonly up- or downregulated in the 4 cell types following 4 h of ex-vivo stimulation. Left, heat map as in (E); right, bar graphs showing expression of transcripts in the indicated populations (n = 6 for all comparisons; represented as in (K), left bar is ex-vivo (-) right bar is the expression profile following stimulation (+)). Figure 2. Tumor TRM cells were clonally expanded. (A) RNA-seq analysis of transcripts (one per row) differentially expressed by tumor TRM?relative to lung TRM, lung non-TRM, and tumor non-TRM (pairwise comparison; change in expression of 2-fold with an adjusted?P?value of ≤ 0.05 (DESeq2 analysis; Benjamini-Hochberg test)), presented as row-wise?z-scores of TPM counts; each column represents an individual sample (lung non-TRM = 21, lung TRM = 20, tumor non-TRM = 25, tumor TRM = 19). (B) Summary of over-representation analysis (using Reactome) of genes involved in the cell cycle that are differentially expressed by lung tumor TRM relative to the other lung CTLs; q values represent false discovery rate. (C) Shannon-Wiener diversity and Inverse Simpson indices obtained using V(D)J tools following TCR-seq analysis of β chains in tumor TRM and tumor non-TRM populations. Bars represent the mean, t-line the s.e.m., and symbols represent individual data points (* P ≤ 0.05; ** P ≤ 0.01; n = 10 patients; Wilcoxon rank-sum test). (D) Left, bar graphs show the percentage of total TCRβ chains that were expanded (≥ 3 clonotypes). Bars represent the mean, t-line the s.e.m., and dots individual data points (* P ≤ 0.05; n = 10 patients). Right, pie charts show the distribution of TCRβ clonotypes based on clonal frequency. (E) Left, Spearman co-expression analysis of the 77 genes up-regulated (A) in tumor TRM cells; values are clustered with complete linkage. (F) Weighted gene co-expression network analysis visualized in Gephi, the nodes are colored and sized according to the number of edges (connections), and the edge thickness is proportional to the edge weight (strength of correlation). (G) Correlation of the expression of HAVCR2 (TIM-3) transcripts and the indicated transcripts in tumor TRM population; r indicates Spearman correlation value (* P ≤ 0.05; *** P ≤ 0.001; **** P ≤ 0.0001, n = 19 patients). Figure 3. Single-cell transcriptomic analysis reveals previously uncharacterized TRM subsets. (A) tSNE visualization of ~12,000 live and singlet-gated CD14–CD19–CD20–CD4–CD56–CD45+CD3+CD8+ single cell transcriptomes obtained from 12 tumors and 6 matched normal lung samples. Each symbol represents a cell; color indicates protein expression of CD103 detected by flow cytometry. (B) Seurat clustering of cells in (A) identifying 9 clusters. (C) Cells from tumor and lung were randomly down sampled to equivalent numbers of cells. Left, distribution of TRM-enriched clusters in tumor and lung. Right, pie chart representing the relative proportions of cells in each TRM cluster. (D) Expression of transcripts previously identified as upregulated in the bulk tumor TRM population (Fig. 2 A) by each cluster; each column represents the average expression in a particular cluster. (E) Breakdown of cell type and tissue localization of cells defined as being in cluster 1 (light purple). (F) Violin plots of expression of example tumor TRM genes in each TRM-enriched cluster (square below indicates the cluster type) and non-TRM cells; shape represents the distribution of expression among cells and color represents the Seurat-normalized average expression counts. (G) Cell-state hierarchy maps generated by Monocle2 bioinformatic modelling of the TRM clusters; center plot, each dot represents a cell colored according to Seurat- assigned cluster; surrounding panels show relative Seurat-normalized expression of the indicated genes. (H) Cluster analysis of the location in PCA space for cells, each cluster was randomly down sampled to the equivalent size of the smallest cluster (n = 135 cells per cluster, 675 total). The correlation method was spearman and the dataset was clustered with average linkage.Figure 4. TIM-3+IL7R- TRM subset was enriched for transcripts linked to cytotoxicity. (A) Single-cell RNA-seq analysis of transcripts (one per row) uniquely differentially expressed by each tumor TRM?subset in pairwise analysis compared to other clusters (adjusted?P?value of ≤ 0.01; MAST analysis), presented as row-wise?z-scores of Seurat-normalized count, each column represents an individual cell. Horizontal breaks separate genes enriched in each of the 4 tumor TRM subsets. (B) Seurat-normalized expression of indicated transcripts identified as differentially enriched in each cluster (as per A), overlaid across the tSNE plot, with expression levels represented by the color scale. (C) Violin plot of expression of functionally important genes identified as significantly enriched in a tumor TRM subset; shape represents the distribution of expression among cells and color represents the Seurat-normalized average expression (cluster identification as per A). (D) Percentage of cells expressing the indicated transcripts in each population, where positive expression was defined as greater than 1 Seurat-normalized count; “TRM” corresponds to tumor-infiltrating CTLs isolated from clusters 2, 3, 4, and 5 and “non-TRM” to the remaining cells not assigned into the proliferating TRM cluster 1.Figure 5. PD-1- and TIM-3-expressing tumor-infiltrating TRM cells are not exhausted. (A) GSEA of the TIM-3+IL7R– TRM subset signature in the transcriptome of clonally expanded tumor TRM?versus. that of non-expanded TRM cells: top,?running enrichment score (RES) for the gene set, from most enriched at the left to most under-represented at the right; middle, positions of gene set members (blue vertical lines) in the ranked list of genes; bottom, value of the ranking metric. Values above the plot represent the normalized enrichment score (NES) and FDR-corrected significance. (B) Left, percentage of cells that were clonally expanded in TIM-3+ (HAVCR2 ≥ 10 TPM counts) TRM cells, remaining TRMs and non-TRM; clonal expansion was determined for cells from 4 and 2 patients for TRM and non-TRM, respectively. Right, section of a clonotype network graph of cells from a representative patient. TIM-3+ (HAVCR2 ≥ 10 TPM counts) TRM cells are marked with a purple circle; cells with greater than 10 TPM counts expression of either MKI67 or TOP2A were considered cycling and denoted with an asterisk. (C) Violin plot of expression of indicated transcripts; shape represents the distribution of expression among cells and color represents average expression, calculated from the TPM counts, color code as per (B). (D) Spearman co-expression analysis of genes whose expression is enriched in the TIM-3+IL7R– TRM cluster (Fig. 4 A) in tumor TRM and non-TRM populations, respectively; matrix is clustered according to complete linkage. (E) Correlation of PDCD1 and IFNG expression in non-TRM cells, all TRM cells and then in TIM-3+ TRM; each dot represents a cell. Percentages indicate the percentage of cells inside each of the graph sections (r indicates Spearman correlation value; ** P ≤ 0.01, N/S = no significance). (F) Percentage of cells expressing IFNG, in each indicated population segregated on PD-1+ (PDCD1 ≥ 10 TPM counts). The final two bars are the TRM population, as segregated by having expression of HAVCR2 (TIM-3) ≥ 10 TPM counts. (G) Percentage of cells expressing the indicated transcript as identified above the plot, in each population (as per F). (H) Flow-cytometry analysis of the percentage of PD-1+ TRM and PD-1+ non-TRM cells that express effector cytokines (as indicated above the graph) following 4 hours of ex-vivo stimulation. Gated on live and singlet-gated CD14–CD20–CD4–CD45+CD3+CD8+ cells obtained from lung cancer TILs, discriminated on CD103 expression (** ≤ 0.01; n = 11; Wilcoxon rank-sum test), each symbol represents a sample. Surface molecules (e.g., PD-1) were stained before stimulation. (I) Analysis of Granzyme A and Granzyme B directly ex-vivo, gated and analyzed as per (H; *** P ≤ 0.001; Wilcoxon rank-sum test).Figure 6. Surface TIM-3+IL-7R– status uniquely characterizes a set of tumor TRM cells. (A) tSNE visualization of flow cytometry data from 3,000 randomly selected live and singlet-gated CD14–CD19–CD20–CD56–CD4–CD45+CD3+CD8+ cells isolated from 8 paired tumor and lung samples; each cell is represented by a dot colored as TRM or non-TRM (left), tumor or lung (second and third from left), and according to Z-score expression value of the protein indicated above the plot (remaining panels). (B) Left, contour plots show the expression of TIM-3 versus. IL-7R in the cell type and tissue indicated above the plot; percentage of tumor CTLs (gated as above) in the indicated populations that express TIM-3 is shown. Right, quantification of TIM-3+ in cells isolated from each tissue location, each symbol represents an individual sample; the small line indicates the s.e.m, bars are mean and colored as indicated (* P ≤ 0.05; n = 8, 3). (C) Geometric mean fluorescent intensity (GMFI) of CD39, PD-1 and 4-1BB for each Lung tumor-TRM subset; bars represent the mean, t-line the s.e.m., and each symbol represents data from individual samples (** P ≤ 0.01; n = 8; Wilcoxon rank-sum test); representative histograms shown at left. (D) Co-expression analysis of flow cytometry data (C), as per Spearman correlation. (E) Contour plot highlighting the expression of PD-1 versus. TIM-3 in CD14–CD19–CD20–CD56–CD4–CD45+CD3+CD8+CD103+ cells in a representative donor. (F) Analysis of three head and neck squamous cell carcinoma samples – HNSCC, as per (B). (F) Left, representative multiplexed immunohistochemistry of CD8A, CD103 and TIM-3 in tumor specimens from a patient with TILlow/TRMlow tumor status, the representative false colour image (middle) and the overlaid image (bottom). Right, as the left plots for a patient with TILhigh/TRMhigh tumor status (scale bar = 50 μm). (G) Left, quantification of the number of CD8A+CD103+TIM-3+ cells per region in biopsies defined as having a TILhigh/TRMhigh status versus. TILlow/TRMlow status. Right, percent of CD8A+CD103+ CTLs expressing TIM-3 in each clinical subtype. Bars represent the mean, t-line the s.e.m., and symbols represent individual data points (* P ≤ 0.05; **** P ≤ 0.0001; n = 21; Mann-Whitney test).Figure 7. Single-cell transcriptome analysis of CTLs from anti-PD-1 responders. (A) Left, contour plots show the expression of TIM-3 and IL-7R in CD14–CD19–CD20–CD4–CD45+CD3+CD8+CD103+ cells isolated from patients receiving anti-PD-1 treatment, at the time point indicated above the plot (TP); number in red indicates the percentage of tumor TRM cells (CD8+CD103+) with TIM-3+IL-7R– surface phenotype Right, quantification of the percentage of tumor-infiltrating TIM-3+IL-7R– TRM cells, isolated from the anti-PD-1 responding, non-responding and treatment na?ve patients. Bars represent the mean, t-line the s.e.m., and symbols represent individual data points (* P ≤ 0.05; ** P ≤ 0.01; n = 7,8 and 12 biopsies for responders, treatment na?ve and non-responders, respectively; Mann-Whitney test). (B) Contour plots demonstrate the expression of TIM-3 and PD-1 in the TRM cells isolated from pre-immunotherapy biopsies (gated as per Fig. 7 A). (C) Single-cell RNA-seq analysis of transcripts (one per row) differentially expressed between CTLs pre- and post-anti-PD-1 (MAST analysis), with an adjusted?P value of ≤ 0.05), presented as row-wise?z-scores of TPM counts; each column represents a single cell (n = 127 and 151 cells, respectively). (D) Violin plot of expression of indicated transcripts differentially expressed between tumor-infiltrating CTLs isolated from pre- and post-anti-PD-1 treatment samples (as per c); shape represents the distribution of expression among cells and color represents average expression, calculated from the TPM counts. (E) GSEA of the bulk tumor CD103+ versus. CD103- transcriptional signature (Fig. 2 A) and TIM-3+IL7R– TRM cell signature (Fig. 4 A) in tumor-infiltrating CTLs isolated from pre- and post-anti-PD-1 treatment samples: top,?running enrichment score (RES) for the gene set, from most enriched at the left to most under-represented at the right; middle, positions of gene set members (blue vertical lines) in the ranked list of genes; bottom, value of the ranking metric. Values above the plot represent the normalized enrichment score (NES) and FDR-corrected significance. (F) Spearman co-expression analysis of transcripts enriched in tumor-infiltrating CTLs from post-anti-PD-1 treatment samples (C); matrix is clustered according to complete linkage. (G) Correlation analysis of all peaks identified in the OMNI-ATAC-seq libraries, pooled from 9 donors across two experiments, cells were sorted on CD14–CD19–CD20–CD4–CD45+CD3+CD8+CD103+TIM-3+IL-7R– and CD14–CD19–CD20–CD4–CD45+CD3+CD8+CD103-. Matrix is clustered according to complete linkage. (H) University of California Santa Cruz genome browser tracks for key TRM-associated gene loci as indicated above the tracks. RNA-seq tracks are merged from all purified bulk RNA-seq data, presented as Reads Per Kilobase Million (RPKM) (as per Fig. 1 A; tumor non-TRM = 25, tumor TRM = 19; OMNI-ATAC-seq as per Fig. 7 G). MATERIALS AND METHODSEthics and sample processing The Southampton and South West Hampshire Research Ethics Board approved the study, and written informed consent was obtained from all subjects ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3775","ISSN":"1529-2908","PMID":"28628092","abstract":"Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.","author":[{"dropping-particle":"","family":"Ganesan","given":"Anusha-Preethi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garrido-Martin","given":"Eva M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alzetani","given":"Aiman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friedmann","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2017","6","19"]]},"page":"940-950","title":"Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer","type":"article-journal","volume":"18"},"uris":[""]}],"mendeley":{"formattedCitation":"(Ganesan et al., 2017)","plainTextFormattedCitation":"(Ganesan et al., 2017)","previouslyFormattedCitation":"(Ganesan et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Ganesan et al., 2017). Newly diagnosed, untreated patients with respiratory malignancies or HNSCC, were prospectively recruited once referred ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1158/1078-R-17-0373","ISSN":"15573265","PMID":"28951517","abstract":"Purpose: Genetic and morphologic heterogeneity is well-documented in solid cancers. Immune cells are also variably distributed within the tumor; this heterogeneity is difficult to assess in small biopsies, and may confound our understanding of the determinants of successful immunotherapy. We examined the transcriptomic variability of the immunologic signature in head and neck squamous cell carcinoma (HNSCC) within individual tumors using transcriptomic and IHC assessments.Experimental Design: Forty-four tumor biopsies from 16 HNSCC patients, taken at diagnosis and later at resection, were analyzed using RNA-sequencing. Variance filtering was used to identify the top 4,000 most variable genes. Principal component analysis, hierarchical clustering, and correlation analysis were performed. Gene expression of CD8A was correlated to IHC analysis.Results: Analysis of immunologic gene expression was highly consistent in replicates from the same cancer. Across the cohort, samples from the same patient were most similar to each other, both spatially (at diagnosis) and, notably, over time (diagnostic biopsy compared with resection); comparison of global gene expression by hierarchical clustering (P ≤ 0.0001) and correlation analysis [median intrapatient r = 0.82; median interpatient r = 0.63]. CD8A gene transcript counts were highly correlated with CD8 T-cell counts by IHC (r = 0.82).Conclusions: Our data demonstrate that in HNSCC the global tumor and adaptive immune signatures are stable between discrete parts of the same tumor and also at different timepoints. This suggests that immunologic heterogeneity may not be a key reason for failure of immunotherapy and underpins the use of transcriptomics for immunologic evaluation of novel agents in HNSCC patients. Clin Cancer Res; 23(24); 7641-9. ?2017 AACR.","author":[{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Jeongmin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mirza","given":"Adal H.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woelk","given":"Christopher H.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Clinical Cancer Research","id":"ITEM-1","issue":"24","issued":{"date-parts":[["2017","12","15"]]},"page":"7641-7649","title":"Head and neck squamous cell carcinomas are characterized by a stable immune signature within the primary tumor over time and space","type":"article-journal","volume":"23"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1038/bjc.2017.269","ISSN":"0007-0920","PMID":"28817839","abstract":"BACKGROUND We systematically assessed the prognostic and predictive value of infiltrating adaptive and innate immune cells in a large cohort of patients with advanced mesothelioma. METHODS A tissue microarray from 302 samples was constructed. Markers of adaptive immune response in T-cells (CD8(+), FOXP3(+), CD4(+), CD45RO(+), CD3(+)) and B-cells (CD20(+)), and of innate immune response; neutrophils (NP57(+)), natural killer cells (CD56(+)) and macrophages (CD68(+)) were evaluated. RESULTS We found that in the epithelioid tumours, high CD4(+) and CD20(+) counts, and low FOXP3(+), CD68(+) and NP57(+) counts linked to better outcome. In the non-epithelioid group low CD8(+) and low FOXP3(+) counts were beneficial.On multivariate analysis low FOXP3(+) remained independently associated with survival in both groups. In the epithelioid group additionally high CD4(+), high CD20(+), and low NP57(+) counts were prognostic. CONCLUSIONS Our data demonstrate for the first time, in predominately advanced disease, the association of key markers of adaptive and innate immunity with survival and the differential effect of histology. A better understanding of the immunological drivers of the different subtypes of mesothelioma will assist prognostication and disease-specific clinical decision-making.","author":[{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lopez","given":"Maria","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gankande","given":"Sharmali","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Moutasim","given":"Karwan A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Scott","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"British Journal of Cancer","id":"ITEM-2","issue":"9","issued":{"date-parts":[["2017","10","24"]]},"page":"1341-1348","publisher":"Nature Publishing Group","title":"Evaluating the effect of immune cells on the outcome of patients with mesothelioma","type":"article-journal","volume":"117"},"uris":[""]}],"mendeley":{"formattedCitation":"(Wood et al., 2017; Chee et al., 2017)","plainTextFormattedCitation":"(Wood et al., 2017; Chee et al., 2017)","previouslyFormattedCitation":"(Wood et al., 2017; Chee et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Wood et al., 2017; Chee et al., 2017). Freshly resected tumor tissue and, where available, matched adjacent non-tumor tissue was obtained from lung cancer patients following surgical resection. HNSCC tumors were macroscopically dissected and slowly frozen in 90% FBS (Thermo) and 10% DMSO (Sigma) for storage, until samples could be prepared. Samples pre- and post-anti-PD-1 therapy were frozen as per HNSCC samples. Flow cytometry of fresh materialSamples were processed as described previously ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3775","ISSN":"1529-2908","PMID":"28628092","abstract":"Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.","author":[{"dropping-particle":"","family":"Ganesan","given":"Anusha-Preethi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garrido-Martin","given":"Eva M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alzetani","given":"Aiman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friedmann","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2017","6","19"]]},"page":"940-950","title":"Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer","type":"article-journal","volume":"18"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.18632/oncotarget.10788","ISSN":"1949-2553","PMID":"27462861","abstract":"Human papilloma virus (HPV)-associated head and neck squamous cell carcinoma (HNSCC) has a better prognosis than it's HPV negative (HPV(-)) counterpart. This may be due to the higher numbers of tumor-infiltrating lymphocytes (TILs) in HPV positive (HPV(+)) tumors. RNA-Sequencing (RNA-Seq) was used to evaluate whether the differences in clinical behaviour simply reflect a numerical difference in TILs or whether there is a fundamental behavioural difference between TILs in these two settings. Thirty-nine HNSCC tumors were scored for TIL density by immunohistochemistry. After the removal of 16 TILlow tumors, RNA-Seq analysis was performed on 23 TILhigh/med tumors (HPV(+) n=10 and HPV(-) n=13). Using EdgeR, differentially expressed genes (DEG) were identified. Immune subset analysis was performed using Functional Analysis of Individual RNA-Seq/ Microarray Expression (FAIME) and immune gene RNA transcript count analysis. In total, 1,634 DEGs were identified, with a dominant immune signature observed in HPV(+) tumors. After normalizing the expression profiles to account for differences in B- and T-cell number, 437 significantly DEGs remained. A B-cell associated signature distinguished HPV(+) from HPV(-) tumors, and included the DEGs CD200, GGA2, ADAM28, STAG3, SPIB, VCAM1, BCL2 and ICOSLG; the immune signal relative to T-cells was qualitatively similar between TILs of both tumor cohorts. Our findings were validated and confirmed in two independent cohorts using TCGA data and tumor-infiltrating B-cells from additional HPV(+) HNSCC patients. A B-cell associated signal segregated tumors relative to HPV status. Our data suggests that the role of B-cells in the adaptive immune response to HPV(+) HNSCC requires re-assessment.","author":[{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Jeongmin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Savelyeva","given":"Natalia","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"McCann","given":"Katy J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jones","given":"Terry","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peel","given":"Lailah","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Breen","given":"Michael S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ward","given":"Matthew","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Martin","given":"Eva Garrido","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woelk","given":"Christopher H","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Oncotarget","id":"ITEM-2","issue":"35","issued":{"date-parts":[["2016","8","30"]]},"page":"56781-56797","title":"Gene expression analysis of TIL rich HPV-driven head and neck tumors reveals a distinct B-cell signature when compared to HPV independent tumors","type":"article-journal","volume":"7"},"uris":[""]}],"mendeley":{"formattedCitation":"(Ganesan et al., 2017; Wood et al., 2016)","plainTextFormattedCitation":"(Ganesan et al., 2017; Wood et al., 2016)","previouslyFormattedCitation":"(Ganesan et al., 2017; Wood et al., 2016)"},"properties":{"noteIndex":0},"schema":""}(Ganesan et al., 2017; Wood et al., 2016). For sorting of fresh CTLs for population transcriptomic analysis, cells were first incubated at 4°C with FcR block (Miltenyi Biotec) for 10 min, then stained with a mixture of the following antibodies: anti-CD45-FITC (HI30; BioLegend), anti-CD4-PE (OKT4; BD Biosciences), anti-CD3-APC-Cy7 (SK7; BioLegend), anti-CD8A-PerCP-Cy5.5 (SK1; BioLegend), and anti-CD103-APC (Ber-ACT8; BioLegend) for 30 min at 4°C. Live/dead discrimination was by DAPI stainingADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3775","ISSN":"1529-2908","PMID":"28628092","abstract":"Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.","author":[{"dropping-particle":"","family":"Ganesan","given":"Anusha-Preethi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garrido-Martin","given":"Eva M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alzetani","given":"Aiman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friedmann","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2017","6","19"]]},"page":"940-950","title":"Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer","type":"article-journal","volume":"18"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.18632/oncotarget.10788","ISSN":"1949-2553","PMID":"27462861","abstract":"Human papilloma virus (HPV)-associated head and neck squamous cell carcinoma (HNSCC) has a better prognosis than it's HPV negative (HPV(-)) counterpart. This may be due to the higher numbers of tumor-infiltrating lymphocytes (TILs) in HPV positive (HPV(+)) tumors. RNA-Sequencing (RNA-Seq) was used to evaluate whether the differences in clinical behaviour simply reflect a numerical difference in TILs or whether there is a fundamental behavioural difference between TILs in these two settings. Thirty-nine HNSCC tumors were scored for TIL density by immunohistochemistry. After the removal of 16 TILlow tumors, RNA-Seq analysis was performed on 23 TILhigh/med tumors (HPV(+) n=10 and HPV(-) n=13). Using EdgeR, differentially expressed genes (DEG) were identified. Immune subset analysis was performed using Functional Analysis of Individual RNA-Seq/ Microarray Expression (FAIME) and immune gene RNA transcript count analysis. In total, 1,634 DEGs were identified, with a dominant immune signature observed in HPV(+) tumors. After normalizing the expression profiles to account for differences in B- and T-cell number, 437 significantly DEGs remained. A B-cell associated signature distinguished HPV(+) from HPV(-) tumors, and included the DEGs CD200, GGA2, ADAM28, STAG3, SPIB, VCAM1, BCL2 and ICOSLG; the immune signal relative to T-cells was qualitatively similar between TILs of both tumor cohorts. Our findings were validated and confirmed in two independent cohorts using TCGA data and tumor-infiltrating B-cells from additional HPV(+) HNSCC patients. A B-cell associated signal segregated tumors relative to HPV status. Our data suggests that the role of B-cells in the adaptive immune response to HPV(+) HNSCC requires re-assessment.","author":[{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Jeongmin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Savelyeva","given":"Natalia","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"McCann","given":"Katy J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jones","given":"Terry","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peel","given":"Lailah","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Breen","given":"Michael S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ward","given":"Matthew","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Martin","given":"Eva Garrido","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woelk","given":"Christopher H","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Oncotarget","id":"ITEM-2","issue":"35","issued":{"date-parts":[["2016","8","30"]]},"page":"56781-56797","title":"Gene expression analysis of TIL rich HPV-driven head and neck tumors reveals a distinct B-cell signature when compared to HPV independent tumors","type":"article-journal","volume":"7"},"uris":[""]}],"mendeley":{"formattedCitation":"(Ganesan et al., 2017; Wood et al., 2016)","plainTextFormattedCitation":"(Ganesan et al., 2017; Wood et al., 2016)","previouslyFormattedCitation":"(Ganesan et al., 2017; Wood et al., 2016)"},"properties":{"noteIndex":0},"schema":""}(Ganesan et al., 2017; Wood et al., 2016). CTLS were sorted based on CD103 expression using a BD FACSAria-II (BD Biosciences) into ice-cold TRIzol LS reagent (Thermo). Flow cytometry of cryopreserved materialFor single-cell transcriptomic, stimulation assays, and phenotypic characterization, tumor and lung samples were first dispersed (as above) and cryopreserved in freezing media (50% complete RMPI (Fisherscientific), 40% human decomplemented AB serum, 10% DMSO (both Sigma). Cryopreserved samples were thawed, washed twice with pre-warmed (37°C) and room temperature MACS buffer and prepared for staining as above. The second wash included an underlayer of FBS to help collect debris. The material was stained with a combination of: anti-CD45-AlexaFluor700 (HI30; BioLegend); anti-CD3-APC-Cy7 (SK7; BioLegend); anti-CD8A-PerCP-Cy5.5 (SK1; BioLegend); anti-CD103-Pe-Cy7 (Ber-ACT8; BioLegend). Cells were counter stained where described with anti-CD19/20 (HIB19/2H7; BioLegend); anti-CD14 (HCD14; BioLegend); anti-CD56 (HCD56; BioLegend) and anti-CD4 (OKT4; BioLegend) for flow cytometric analysis and sorting. Live and dead cells were discriminated using propidium iodide (PI). Cells were stimulated for transcriptomic analysis when noted, with PMA-and-ionomycin, as previously described ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3775","ISSN":"1529-2908","PMID":"28628092","abstract":"Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.","author":[{"dropping-particle":"","family":"Ganesan","given":"Anusha-Preethi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garrido-Martin","given":"Eva M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alzetani","given":"Aiman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friedmann","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2017","6","19"]]},"page":"940-950","title":"Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer","type":"article-journal","volume":"18"},"uris":[""]}],"mendeley":{"formattedCitation":"(Ganesan et al., 2017)","plainTextFormattedCitation":"(Ganesan et al., 2017)","previouslyFormattedCitation":"(Ganesan et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Ganesan et al., 2017). For 10x single-cell transcriptomic analysis (10X Genomics), 1500 cells each of CD103+ and CD103– CTLs from tumor and lung samples were sorted and mixed into 50% ice cold PBS, 50% FBS (Sigma) on a BD Aria-II or Fusion cell sorter. From the 12 patients used for 10x genomics, 6 were used for the background lung. CTLs for assessments of the bulk transcriptome following stimulation, was collected by sorting 200 cells into 8 μL lysis buffer (Triton X-100 (0.1%), containing RNase inhibitor (1U/ μL and dNTP mix (2.5mM) on an Aria-II (BD); for Smart-seq2-based single-cell analysis, CTLs were sorted as above, using single cell purity into 4 μL lysis buffer on a BD Aria-II as described previously ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-1","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1038/ni.3437","ISSN":"1529-2908","PMID":"27089380","abstract":"Natural killer T cells (NKT cells) have stimulatory or inhibitory effects on the immune response that can be attributed in part to the existence of functional subsets of NKT cells. These subsets have been characterized only on the basis of the differential expression of a few transcription factors and cell-surface molecules. Here we have analyzed purified populations of thymic NKT cell subsets at both the transcriptomic level and epigenomic level and by single-cell RNA sequencing. Our data indicated that despite their similar antigen specificity, the functional NKT cell subsets were highly divergent populations with many gene-expression and epigenetic differences. Therefore, the thymus 'imprints' distinct gene programs on subsets of innate-like NKT cells that probably impart differences in proliferative capacity, homing, and effector functions.","author":[{"dropping-particle":"","family":"Engel","given":"Isaac","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chavez","given":"Lukas","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"White","given":"Brandie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chawla","given":"Ashu","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mock","given":"Dennis","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kronenberg","given":"Mitchell","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-2","issue":"6","issued":{"date-parts":[["2016","4","18"]]},"page":"728-739","title":"Innate-like functions of natural killer T cell subsets result from highly divergent gene programs","type":"article-journal","volume":"17"},"uris":[""]},{"id":"ITEM-3","itemData":{"DOI":"10.1038/nprot.2014.006","ISSN":"1754-2189","abstract":"Emerging methods for the accurate quantification of gene expression in individual cells hold promise for revealing the extent, function and origins of cell-to-cell variability. Different high-throughput methods for single-cell RNA-seq have been introduced that vary in coverage, sensitivity and multiplexing ability. We recently introduced Smart-seq for transcriptome analysis from single cells, and we subsequently optimized the method for improved sensitivity, accuracy and full-length coverage across transcripts. Here we present a detailed protocol for Smart-seq2 that allows the generation of full-length cDNA and sequencing libraries by using standard reagents. The entire protocol takes ～2 d from cell picking to having a final library ready for sequencing; sequencing will require an additional 1–3 d depending on the strategy and sequencer. The current limitations are the lack of strand specificity and the inability to detect nonpolyadenylated (polyA?) RNA.","author":[{"dropping-particle":"","family":"Picelli","given":"Simone","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Faridani","given":"Omid R","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bj?rklund","given":"?sa K","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Winberg","given":"G?sta","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sagasser","given":"Sven","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sandberg","given":"Rickard","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Protocols","id":"ITEM-3","issue":"1","issued":{"date-parts":[["2014","1","2"]]},"page":"171-181","publisher":"Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.","title":"Full-length RNA-seq from single cells using Smart-seq2","type":"article-journal","volume":"9"},"uris":[""]}],"mendeley":{"formattedCitation":"(Patil et al., 2018; Engel et al., 2016; Picelli et al., 2014)","plainTextFormattedCitation":"(Patil et al., 2018; Engel et al., 2016; Picelli et al., 2014)","previouslyFormattedCitation":"(Patil et al., 2018; Engel et al., 2016; Picelli et al., 2014)"},"properties":{"noteIndex":0},"schema":""}(Patil et al., 2018; Engel et al., 2016; Picelli et al., 2014).For tumor TRM phenotyping in treatment na?ve patients, samples were analyzed on a FACS-Fusion (BD) following staining with: anti-CD45-AlexaFluor700 (HI30; BioLegend); anti-CD3-APC-Cy7 (SK7; BioLegend); anti-CD8A-PerCP-Cy5.5 (SK1; BioLegend); anti-CD103-Pe-Cy7 (Ber-ACT8; BioLegend); anti-CD127-APC (eBioRDR5; ThermoFisher); anti-CD39-BB515 (TU66; BD); anti-4-1BB-PE (4B4-1; BioLegend), anti-PD-1-BV421 (EH12.1; BD); anti-TIM-3-BV605 (F38-2E2; BioLegend). Cells were counter stained where described with anti-CD19/20-PE-Dazzle (HIB19/2H7; BioLegend); anti-CD14-PE-Dazzle (HCD14; BioLegend); anti-CD56-BV570 (HCD56; BioLegend) and anti-CD4-BV510 (OKT4; BioLegend). Dead cells were discriminated using PI. Phenotypic characterization of lung TRM was completed using the antibodies above with anti-CD49A-PE (SR84; BD) and anti-KLRG1-APC (2F1/KLRG1; BioLegend) on a LSRII (BD), using a gating strategy previously described ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3775","ISSN":"1529-2908","PMID":"28628092","abstract":"Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.","author":[{"dropping-particle":"","family":"Ganesan","given":"Anusha-Preethi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garrido-Martin","given":"Eva M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alzetani","given":"Aiman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friedmann","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2017","6","19"]]},"page":"940-950","title":"Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer","type":"article-journal","volume":"18"},"uris":[""]}],"mendeley":{"formattedCitation":"(Ganesan et al., 2017)","plainTextFormattedCitation":"(Ganesan et al., 2017)","previouslyFormattedCitation":"(Ganesan et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Ganesan et al., 2017). For paired analyses of patients pre- and post-anti-PD-1 treatment, we collected tissue from patients with metastatic melanoma (patients 53-54; Tables S1 and S12) before the first dose and after six weeks of immunotherapy. Patient 53 received ipilimumab at 3mg/kg and nivolumab 1mg/kg at three weekly intervals. Patient 54 was treated with pembrolizumab at 2mg/kg, given three weekly. Both patients achieved a complete remission.?Biopsies were cryopreserved in 90% FBS 10% DMSO until data acquisition.?Phenotypic characterization of TRM?samples pre- and post-immunotherapy was completed by thawing the material and dispersing the biopsies, using mechanical and enzymatic digestion, as described previously ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3775","ISSN":"1529-2908","PMID":"28628092","abstract":"Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.","author":[{"dropping-particle":"","family":"Ganesan","given":"Anusha-Preethi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garrido-Martin","given":"Eva M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alzetani","given":"Aiman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friedmann","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2017","6","19"]]},"page":"940-950","title":"Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer","type":"article-journal","volume":"18"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.18632/oncotarget.10788","ISSN":"1949-2553","PMID":"27462861","abstract":"Human papilloma virus (HPV)-associated head and neck squamous cell carcinoma (HNSCC) has a better prognosis than it's HPV negative (HPV(-)) counterpart. This may be due to the higher numbers of tumor-infiltrating lymphocytes (TILs) in HPV positive (HPV(+)) tumors. RNA-Sequencing (RNA-Seq) was used to evaluate whether the differences in clinical behaviour simply reflect a numerical difference in TILs or whether there is a fundamental behavioural difference between TILs in these two settings. Thirty-nine HNSCC tumors were scored for TIL density by immunohistochemistry. After the removal of 16 TILlow tumors, RNA-Seq analysis was performed on 23 TILhigh/med tumors (HPV(+) n=10 and HPV(-) n=13). Using EdgeR, differentially expressed genes (DEG) were identified. Immune subset analysis was performed using Functional Analysis of Individual RNA-Seq/ Microarray Expression (FAIME) and immune gene RNA transcript count analysis. In total, 1,634 DEGs were identified, with a dominant immune signature observed in HPV(+) tumors. After normalizing the expression profiles to account for differences in B- and T-cell number, 437 significantly DEGs remained. A B-cell associated signature distinguished HPV(+) from HPV(-) tumors, and included the DEGs CD200, GGA2, ADAM28, STAG3, SPIB, VCAM1, BCL2 and ICOSLG; the immune signal relative to T-cells was qualitatively similar between TILs of both tumor cohorts. Our findings were validated and confirmed in two independent cohorts using TCGA data and tumor-infiltrating B-cells from additional HPV(+) HNSCC patients. A B-cell associated signal segregated tumors relative to HPV status. Our data suggests that the role of B-cells in the adaptive immune response to HPV(+) HNSCC requires re-assessment.","author":[{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Jeongmin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Savelyeva","given":"Natalia","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"McCann","given":"Katy J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jones","given":"Terry","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peel","given":"Lailah","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Breen","given":"Michael S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ward","given":"Matthew","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Martin","given":"Eva Garrido","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woelk","given":"Christopher H","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Oncotarget","id":"ITEM-2","issue":"35","issued":{"date-parts":[["2016","8","30"]]},"page":"56781-56797","title":"Gene expression analysis of TIL rich HPV-driven head and neck tumors reveals a distinct B-cell signature when compared to HPV independent tumors","type":"article-journal","volume":"7"},"uris":[""]}],"mendeley":{"formattedCitation":"(Ganesan et al., 2017; Wood et al., 2016)","plainTextFormattedCitation":"(Ganesan et al., 2017; Wood et al., 2016)","previouslyFormattedCitation":"(Ganesan et al., 2017; Wood et al., 2016)"},"properties":{"noteIndex":0},"schema":""}(Ganesan et al., 2017; Wood et al., 2016). Cells were stained as above and sorted into 2 μL lysis buffer on a BD Aria-II as described above ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-1","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1038/ni.3437","ISSN":"1529-2908","PMID":"27089380","abstract":"Natural killer T cells (NKT cells) have stimulatory or inhibitory effects on the immune response that can be attributed in part to the existence of functional subsets of NKT cells. These subsets have been characterized only on the basis of the differential expression of a few transcription factors and cell-surface molecules. Here we have analyzed purified populations of thymic NKT cell subsets at both the transcriptomic level and epigenomic level and by single-cell RNA sequencing. Our data indicated that despite their similar antigen specificity, the functional NKT cell subsets were highly divergent populations with many gene-expression and epigenetic differences. Therefore, the thymus 'imprints' distinct gene programs on subsets of innate-like NKT cells that probably impart differences in proliferative capacity, homing, and effector functions.","author":[{"dropping-particle":"","family":"Engel","given":"Isaac","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chavez","given":"Lukas","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"White","given":"Brandie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chawla","given":"Ashu","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mock","given":"Dennis","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kronenberg","given":"Mitchell","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-2","issue":"6","issued":{"date-parts":[["2016","4","18"]]},"page":"728-739","title":"Innate-like functions of natural killer T cell subsets result from highly divergent gene programs","type":"article-journal","volume":"17"},"uris":[""]},{"id":"ITEM-3","itemData":{"DOI":"10.1038/nprot.2014.006","ISSN":"1754-2189","abstract":"Emerging methods for the accurate quantification of gene expression in individual cells hold promise for revealing the extent, function and origins of cell-to-cell variability. Different high-throughput methods for single-cell RNA-seq have been introduced that vary in coverage, sensitivity and multiplexing ability. We recently introduced Smart-seq for transcriptome analysis from single cells, and we subsequently optimized the method for improved sensitivity, accuracy and full-length coverage across transcripts. Here we present a detailed protocol for Smart-seq2 that allows the generation of full-length cDNA and sequencing libraries by using standard reagents. The entire protocol takes ～2 d from cell picking to having a final library ready for sequencing; sequencing will require an additional 1–3 d depending on the strategy and sequencer. The current limitations are the lack of strand specificity and the inability to detect nonpolyadenylated (polyA?) RNA.","author":[{"dropping-particle":"","family":"Picelli","given":"Simone","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Faridani","given":"Omid R","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bj?rklund","given":"?sa K","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Winberg","given":"G?sta","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sagasser","given":"Sven","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sandberg","given":"Rickard","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Protocols","id":"ITEM-3","issue":"1","issued":{"date-parts":[["2014","1","2"]]},"page":"171-181","publisher":"Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.","title":"Full-length RNA-seq from single cells using Smart-seq2","type":"article-journal","volume":"9"},"uris":[""]}],"mendeley":{"formattedCitation":"(Patil et al., 2018; Engel et al., 2016; Picelli et al., 2014)","plainTextFormattedCitation":"(Patil et al., 2018; Engel et al., 2016; Picelli et al., 2014)","previouslyFormattedCitation":"(Patil et al., 2018; Engel et al., 2016; Picelli et al., 2014)"},"properties":{"noteIndex":0},"schema":""}(Patil et al., 2018; Engel et al., 2016; Picelli et al., 2014). Live, singlet, CD14–CD19–CD20–CD45+CD3+ or CD14–CD19–CD20–CD45+CD3+CD8+ cells (depending upon the amount of the material available) were then index sorted on a BD Aria-II using the reagents described above. The data was then concatenated in FlowJo (v10.4.1) and if required, CD8+CD4–CD103+ CTLs were then further isolated in-silico based on protein and/or gene expression data and the analysis completed as described in the RNA-seq section below. Flow cytometry analysis of the remaining donors were completed as above, using: anti-CD45-Alexa-R700 (HI30; BD); anti-CD3-PE-Dazzle (SK7; BioLegend); anti-CD20-APC-Cy7 (2H7; BioLegend); anti-CD14-APC-Cy7 (HCD14; BioLegend); anti-CD8A-PerCP-Cy5.5 (SK1; BioLegend); anti-CD103-Pe-Cy7 (Ber-ACT8; BioLegend); anti-CD127-APC (eBioRDR5; Thermo); anti-PD-1-BV421 (EH12.1; BD); anti-TIM-3-BV605 (F38-2E2; BioLegend) and live/dead discrimination was completed with fixable/live dead (Fixable Viability Dye eFluor? 780; Thermo). The cytometric analysis was completed on a Fusion cell sorter (BD). Samples that had less than 100 CTLs were removed from further analysis.Flow cytometry-based intracellular protein validation was completed by thawing and washing samples as described above. The samples were incubated for 10 minutes at 4°C with FcR block as above and then stained using a combination of: anti-CD45-Alexa-R700 (HI30; BD); anti-CD3-PE-Dazzle (SK7; BioLegend); anti-CD20-APC-Cy7 (2H7; BioLegend); anti-CD14-APC-Cy7 (HCD14; BioLegend); anti-CD4-BV510 (OKT4; BioLegend); anti-CD8A-PerCP-Cy5.5 (SK1; BioLegend); anti-CD103-Pe-Cy7 (Ber-ACT8; BioLegend); anti-CD127-APC (eBioRDR5; Thermo); anti-PD-1-BV421 (EH12.1; BD); and live/dead discrimination was completed with fixable/live dead (Fixable Viability Dye eFluor? 780; Thermo). TIM-3 staining following ex-vivo stimulation and fixation was affected, thus limiting our ability to study the intracellular cytokine profile of TIM-3+ cells directly. The sample was then washed and material for ex-vivo quantification was immediately fixed (Fixation and Permeabilization Solution - BD) for 20 minutes at room temperature. The sample was then washed in Permeabilization wash (Intracellular Staining Permeabilization Wash Buffer, BioLegend). The sample then received additional FcR blocking reagent, and was stained with anti-Granzyme B-PE (REA226; Miltenyi Biotec) and anti-Granzyme A-Alexa Fluor647 (CB9; BioLegend) for 30 minutes at 4°C. Following this the material was washed in Permeabilization Wash Buffer. For samples analyzed for ex-vivo cytokine production, fixable/live dead was added after three hours of the stimulation to account for any changes in cell viability during stimulation. For PMA/ionomycin analysis, the cell suspension was stimulated in for 4 hours at 37°C in an incubator, at 5% CO2, in 200 μL complete RPMI with Cell Activation Cocktail (with Brefeldin A; BioLegend) as per manufacturer’s recommendation. Following the addition of further FcR blocking reagent, cytokine staining was completed with: anti-IL-2-PE (MQ1-17H12; BioLegend); anti-IFN-γ-BV785 (4S.B3; BioLegend) and anti-TNF-APC (MAb11; Biolegend). Data acquisition was completed on a Fortessa (BD), using a gating strategy previously described ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3775","ISSN":"1529-2908","PMID":"28628092","abstract":"Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.","author":[{"dropping-particle":"","family":"Ganesan","given":"Anusha-Preethi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garrido-Martin","given":"Eva M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alzetani","given":"Aiman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friedmann","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2017","6","19"]]},"page":"940-950","title":"Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer","type":"article-journal","volume":"18"},"uris":[""]}],"mendeley":{"formattedCitation":"(Ganesan et al., 2017)","plainTextFormattedCitation":"(Ganesan et al., 2017)","previouslyFormattedCitation":"(Ganesan et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Ganesan et al., 2017) and data was analyzed as above. One sample with less than 100 total CTLs quantified was removed.All FACS data was analyzed in FlowJo (v10.4.1), and geometric-mean florescence intensity and population percentage data were exported and visualized in Graphpad Prism (v7.0a; Treestar). For tSNE and co-expression analysis of flow cytometry data, each sample was down-sampled to exactly 3,000 randomly selected live and singlet-gated, CD14–CD19–CD20–CD4–CD56–CD45+CD3+CD8+ CTLs using the gating strategy described above, and 24,000 cells each from the lung and tumor samples were merged to yield 48,000 total cells. A tSNE plot was constructed using 1,000 permutations and default settings in FlowJo (v10.4.1), z-score expression was mean centered. Flow cytometry data was exported from FlowJo (using the channel values) and these data were imported into R for co-expression analysis (described below). Bulk-RNA sequencing and TCR-SeqTotal RNA was purified using a miRNAeasy kit (Qiagen) from CD103+ and CD103– CTLs and was quantified as described previouslyADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3775","ISSN":"1529-2908","PMID":"28628092","abstract":"Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.","author":[{"dropping-particle":"","family":"Ganesan","given":"Anusha-Preethi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garrido-Martin","given":"Eva M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alzetani","given":"Aiman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friedmann","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2017","6","19"]]},"page":"940-950","title":"Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer","type":"article-journal","volume":"18"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1038/ni.3437","ISSN":"1529-2908","PMID":"27089380","abstract":"Natural killer T cells (NKT cells) have stimulatory or inhibitory effects on the immune response that can be attributed in part to the existence of functional subsets of NKT cells. These subsets have been characterized only on the basis of the differential expression of a few transcription factors and cell-surface molecules. Here we have analyzed purified populations of thymic NKT cell subsets at both the transcriptomic level and epigenomic level and by single-cell RNA sequencing. Our data indicated that despite their similar antigen specificity, the functional NKT cell subsets were highly divergent populations with many gene-expression and epigenetic differences. Therefore, the thymus 'imprints' distinct gene programs on subsets of innate-like NKT cells that probably impart differences in proliferative capacity, homing, and effector functions.","author":[{"dropping-particle":"","family":"Engel","given":"Isaac","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chavez","given":"Lukas","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"White","given":"Brandie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chawla","given":"Ashu","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mock","given":"Dennis","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kronenberg","given":"Mitchell","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-2","issue":"6","issued":{"date-parts":[["2016","4","18"]]},"page":"728-739","title":"Innate-like functions of natural killer T cell subsets result from highly divergent gene programs","type":"article-journal","volume":"17"},"uris":[""]}],"mendeley":{"formattedCitation":"(Ganesan et al., 2017; Engel et al., 2016)","plainTextFormattedCitation":"(Ganesan et al., 2017; Engel et al., 2016)","previouslyFormattedCitation":"(Ganesan et al., 2017; Engel et al., 2016)"},"properties":{"noteIndex":0},"schema":""}(Ganesan et al., 2017; Engel et al., 2016). For assessment of the stimulated transcriptome, RNA from ~100 sorted cells were used. Total RNA was amplified according to the Smart-seq2 protocol ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nprot.2014.006","ISSN":"1754-2189","abstract":"Emerging methods for the accurate quantification of gene expression in individual cells hold promise for revealing the extent, function and origins of cell-to-cell variability. Different high-throughput methods for single-cell RNA-seq have been introduced that vary in coverage, sensitivity and multiplexing ability. We recently introduced Smart-seq for transcriptome analysis from single cells, and we subsequently optimized the method for improved sensitivity, accuracy and full-length coverage across transcripts. Here we present a detailed protocol for Smart-seq2 that allows the generation of full-length cDNA and sequencing libraries by using standard reagents. The entire protocol takes ～2 d from cell picking to having a final library ready for sequencing; sequencing will require an additional 1–3 d depending on the strategy and sequencer. The current limitations are the lack of strand specificity and the inability to detect nonpolyadenylated (polyA?) RNA.","author":[{"dropping-particle":"","family":"Picelli","given":"Simone","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Faridani","given":"Omid R","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bj?rklund","given":"?sa K","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Winberg","given":"G?sta","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sagasser","given":"Sven","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sandberg","given":"Rickard","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Protocols","id":"ITEM-1","issue":"1","issued":{"date-parts":[["2014","1","2"]]},"page":"171-181","publisher":"Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.","title":"Full-length RNA-seq from single cells using Smart-seq2","type":"article-journal","volume":"9"},"uris":[""]}],"mendeley":{"formattedCitation":"(Picelli et al., 2014)","plainTextFormattedCitation":"(Picelli et al., 2014)","previouslyFormattedCitation":"(Picelli et al., 2014)"},"properties":{"noteIndex":0},"schema":""}(Picelli et al., 2014). cDNA was purified using AMPure XP beads (0.9:1 ratio, Beckman Coulter). From this step, 1 ng of cDNA was used to prepare a standard Nextera XT sequencing library (Nextera XT DNA sample preparation and index kits, Illumina)ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3775","ISSN":"1529-2908","PMID":"28628092","abstract":"Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.","author":[{"dropping-particle":"","family":"Ganesan","given":"Anusha-Preethi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garrido-Martin","given":"Eva M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alzetani","given":"Aiman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friedmann","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2017","6","19"]]},"page":"940-950","title":"Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer","type":"article-journal","volume":"18"},"uris":[""]}],"mendeley":{"formattedCitation":"(Ganesan et al., 2017)","plainTextFormattedCitation":"(Ganesan et al., 2017)","previouslyFormattedCitation":"(Ganesan et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Ganesan et al., 2017). Samples were sequenced using an Illumina HiSeq2500 to obtain 50-bp single-end reads. For quality control, steps were included to determine total RNA quality and quantity, the optimal number of PCR pre-amplification cycles, and cDNA fragment size. Samples that failed quality control, or had a low number of starting cells were eliminated from further sequencing and analysis. TCR-seq was performed as previously described ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-1","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]}],"mendeley":{"formattedCitation":"(Patil et al., 2018)","plainTextFormattedCitation":"(Patil et al., 2018)","previouslyFormattedCitation":"(Patil et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Patil et al., 2018), using Tru-seq single indexes (Illumina). Sequencing data was mapped and analyzed using MIGEC ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nmeth.2960","ISBN":"1548-7105","ISSN":"15487105","PMID":"24793455","abstract":"Deep profiling of antibody and T cell-receptor repertoires by means of high-throughput sequencing has become an attractive approach for adaptive immunity studies, but its power is substantially compromised by the accumulation of PCR and sequencing errors. Here we report MIGEC (molecular identifier groups-based error correction), a strategy for high-throughput sequencing data analysis. MIGEC allows for nearly absolute error correction while fully preserving the natural diversity of complex immune repertoires.","author":[{"dropping-particle":"","family":"Shugay","given":"Mikhail","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"Britanova","given":"Olga","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Merzlyak","given":"Ekaterina M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Turchaninova","given":"Maria A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mamedov","given":"Ilgar Z","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tuganbaev","given":"Timur R","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bolotin","given":"Dmitriy A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Staroverov","given":"Dmitry B","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"Putintseva","given":"Ekaterina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Plevova","given":"Karla","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Linnemann","given":"Carsten","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Shagin","given":"Dmitriy","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pospisilova","given":"Sarka","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lukyanov","given":"Sergey","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schumacher","given":"Ton N","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chudakov","given":"Dmitriy M","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Methods","id":"ITEM-1","issue":"6","issued":{"date-parts":[["2014","6","4"]]},"page":"653-655","publisher":"Nature Publishing Group","title":"Towards error-free profiling of immune repertoires","type":"article-journal","volume":"11"},"uris":[""]}],"mendeley":{"formattedCitation":"(Shugay et al., 2014)","plainTextFormattedCitation":"(Shugay et al., 2014)","previouslyFormattedCitation":"(Shugay et al., 2014)"},"properties":{"noteIndex":0},"schema":""}(Shugay et al., 2014) software (v1.2.7) with default settings, followed by V(D)J tools (v1.1.7) with default settings. Mapping QC metrics are included in (Tables S1 and S6).10x Single-cell RNA sequencing Samples were processed using 10x v2 chemistry as per manufacturer’s recommendations; 11 and 12 cycles were used for cDNA amplification and library preparation respectively ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-1","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]}],"mendeley":{"formattedCitation":"(Patil et al., 2018)","plainTextFormattedCitation":"(Patil et al., 2018)","previouslyFormattedCitation":"(Patil et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Patil et al., 2018). To minimize experimental batch effects cells were sorted from groups of 6 donors each day, and cells were pooled for 10X sequencing library preparation. Barcoded RNA was collected and processed following manufacturer recommendations, as described previously. Libraries were sequenced on a HiSeq2500 and HiSeq4000 (Illumina) to obtain 100- and 32-bp paired-end reads using the following read length: read 1, 26 cycles; read 2, 98 cycles; and i7 index, 8 cycles (Table S1). Samples were pooled together DNA samples from whole blood were extracted using a High salt method ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/B978-0-7506-7152-1.50011-4","ISBN":"0896030644","ISSN":"0305-1048","PMID":"3344216","author":[{"dropping-particle":"","family":"Miller","given":"S A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Dykes","given":"D D","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Polesky","given":"H F","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nucleic acids research","id":"ITEM-1","issue":"3","issued":{"date-parts":[["1988","2","11"]]},"page":"1215","title":"A simple salting out procedure for extracting DNA from human nucleated cells.","type":"article-journal","volume":"16"},"uris":[""]}],"mendeley":{"formattedCitation":"(Miller et al., 1988)","plainTextFormattedCitation":"(Miller et al., 1988)","previouslyFormattedCitation":"(Miller et al., 1988)"},"properties":{"noteIndex":0},"schema":""}(Miller et al., 1988) and were quantified using the Qubit 2.0 (Thermo). Genotyping was completed through the Infinium Multi-Ethnic Global-8 Kit (Illumina), following the manufacturer’s instructions. Raw data from the genotyping analysis was exported using Genotyping module and Plug-in PLINK Input Report Plug-in (v2.1.4) from GenomeStudio v2.0.4 (Illumina). The data quality was assessed using the snpQC package ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"doi:10.1111/age.12198","ISSN":"0268-9146","abstract":"Summary In genome-wide association studies, quality control (QC) of genotypes is important to avoid spurious results. It is also important to maintain long-term data integrity, particularly in settings with ongoing genotyping (e.g. estimation of genomic breeding values). Here we discuss snpqc, a fully automated pipeline to perform QC analyses of Illumina SNP array data. It applies a wide range of common quality metrics with user-defined filtering thresholds to generate a comprehensive QC report and a filtered dataset, including a genomic relationship matrix, ready for further downstream analyses which make it amenable for integration in high-throughput environments. snpqc also builds a database to store genotypic, phenotypic and quality metrics to ensure data integrity and the option of integrating more samples from subsequent runs. The program is generic across species and array designs, providing a convenient interface between the genotyping laboratory and downstream genome-wide association study or genomic prediction.","author":[{"dropping-particle":"","family":"Gondro","given":"Cedric","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Porto-Neto","given":"Laercio R","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lee","given":"Seung Hwan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Animal Genetics","id":"ITEM-1","issue":"5","issued":{"date-parts":[["2014"]]},"page":"758-761","title":"snpqc – an R pipeline for quality control of Illumina SNP genotyping array data","type":"article-journal","volume":"45"},"uris":[""]}],"mendeley":{"formattedCitation":"(Gondro et al., 2014)","plainTextFormattedCitation":"(Gondro et al., 2014)","previouslyFormattedCitation":"(Gondro et al., 2014)"},"properties":{"noteIndex":0},"schema":""}(Gondro et al., 2014) with R and low-quality SNPs were detected: SNPs failing in more than 5% of the samples and SNPs with Illumina’s GC scores less than 0.2 in more than 10% of the samples were flagged. Subjects' sex was matched with the genotype data and flagged SNPs were removed for downstream analysis using PLINK (v1.90b3w) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1086/519795","ISSN":"0002-9297","abstract":"Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.","author":[{"dropping-particle":"","family":"Purcell","given":"Shaun","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Neale","given":"Benjamin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Todd-Brown","given":"Kathe","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Lori","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ferreira","given":"Manuel A R","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bender","given":"David","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Maller","given":"Julian","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sklar","given":"Pamela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bakker","given":"Paul I W","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Daly","given":"Mark J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sham","given":"Pak C","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"American journal of human genetics","edition":"2007/07/25","id":"ITEM-1","issue":"3","issued":{"date-parts":[["2007","9"]]},"page":"559-575","publisher":"The American Society of Human Genetics","title":"PLINK: a tool set for whole-genome association and population-based linkage analyses","type":"article-journal","volume":"81"},"uris":[""]}],"mendeley":{"formattedCitation":"(Purcell et al., 2007)","plainTextFormattedCitation":"(Purcell et al., 2007)","previouslyFormattedCitation":"(Purcell et al., 2007)"},"properties":{"noteIndex":0},"schema":""}(Purcell et al., 2007). Genetic multiplexing of barcoded single-cell RNA-seq was completed using Demuxlet ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nbt.4042","ISSN":"1087-0156","abstract":"Droplet single-cell RNA-sequencing (dscRNA-seq) has enabled rapid, massively parallel profiling of transcriptomes. However, assessing differential expression across multiple individuals has been hampered by inefficient sample processing and technical batch effects. Here we describe a computational tool, demuxlet, that harnesses natural genetic variation to determine the sample identity of each droplet containing a single cell (singlet) and detect droplets containing two cells (doublets). These capabilities enable multiplexed dscRNA-seq experiments in which cells from unrelated individuals are pooled and captured at higher throughput than in standard workflows. Using simulated data, we show that 50 single-nucleotide polymorphisms (SNPs) per cell are sufficient to assign 97% of singlets and identify 92% of doublets in pools of up to 64 individuals. Given genotyping data for each of eight pooled samples, demuxlet correctly recovers the sample identity of >99% of singlets and identifies doublets at rates consistent with previous estimates. We apply demuxlet to assess cell-type-specific changes in gene expression in 8 pooled lupus patient samples treated with interferon (IFN)-β and perform eQTL analysis on 23 pooled samples.","author":[{"dropping-particle":"","family":"Kang","given":"Hyun Min","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Subramaniam","given":"Meena","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Targ","given":"Sasha","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nguyen","given":"Michelle","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Maliskova","given":"Lenka","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"McCarthy","given":"Elizabeth","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wan","given":"Eunice","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wong","given":"Simon","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Byrnes","given":"Lauren","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lanata","given":"Cristina M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gate","given":"Rachel E","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mostafavi","given":"Sara","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Marson","given":"Alexander","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zaitlen","given":"Noah","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Criswell","given":"Lindsey A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ye","given":"Chun Jimmie","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Biotechnology","id":"ITEM-1","issue":"1","issued":{"date-parts":[["2017","12","11"]]},"page":"89-94","publisher":"Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.","title":"Multiplexed droplet single-cell RNA-sequencing using natural genetic variation","type":"article-journal","volume":"36"},"uris":[""]}],"mendeley":{"formattedCitation":"(Kang et al., 2017)","plainTextFormattedCitation":"(Kang et al., 2017)","previouslyFormattedCitation":"(H.M. et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Kang et al., 2017) and matched with the Seurat output. Cells with ambiguous or doublet identification were removed from analysis of cluster and/or donor proportions.Bulk RNA-seq analysis Bulk RNA-seq data were mapped against the hg19 reference using TopHat ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1093/bioinformatics/btp120","ISSN":"1460-2059","PMID":"19289445","abstract":"MOTIVATION: A new protocol for sequencing the messenger RNA in a cell, known as RNA-Seq, generates millions of short sequence fragments in a single run. These fragments, or 'reads', can be used to measure levels of gene expression and to identify novel splice variants of genes. However, current software for aligning RNA-Seq data to a genome relies on known splice junctions and cannot identify novel ones. TopHat is an efficient read-mapping algorithm designed to align reads from an RNA-Seq experiment to a reference genome without relying on known splice sites. RESULTS: We mapped the RNA-Seq reads from a recent mammalian RNA-Seq experiment and recovered more than 72% of the splice junctions reported by the annotation-based software from that study, along with nearly 20,000 previously unreported junctions. The TopHat pipeline is much faster than previous systems, mapping nearly 2.2 million reads per CPU hour, which is sufficient to process an entire RNA-Seq experiment in less than a day on a standard desktop computer. We describe several challenges unique to ab initio splice site discovery from RNA-Seq reads that will require further algorithm development. AVAILABILITY: TopHat is free, open-source software available from . SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.","author":[{"dropping-particle":"","family":"Trapnell","given":"Cole","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pachter","given":"Lior","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Salzberg","given":"Steven L","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Bioinformatics","id":"ITEM-1","issue":"9","issued":{"date-parts":[["2009","5","1"]]},"page":"1105-1111","title":"TopHat: discovering splice junctions with RNA-Seq","type":"article-journal","volume":"25"},"uris":[""]}],"mendeley":{"formattedCitation":"(Trapnell et al., 2009)","plainTextFormattedCitation":"(Trapnell et al., 2009)","previouslyFormattedCitation":"(Trapnell et al., 2009)"},"properties":{"noteIndex":0},"schema":""}(Trapnell et al., 2009) (v2.0.9 (--library-type fr-unstranded --no-coverage-search) with FastQC (v0.11.2), BowtieADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1186/gb-2009-10-3-r25","ISSN":"1465-6906","PMID":"19261174","abstract":"Bowtie is an ultrafast, memory-efficient alignment program for aligning short DNA sequence reads to large genomes. For the human genome, Burrows-Wheeler indexing allows Bowtie to align more than 25 million reads per CPU hour with a memory footprint of approximately 1.3 gigabytes. Bowtie extends previous Burrows-Wheeler techniques with a novel quality-aware backtracking algorithm that permits mismatches. Multiple processor cores can be used simultaneously to achieve even greater alignment speeds. Bowtie is open source ().","author":[{"dropping-particle":"","family":"Langmead","given":"Ben","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Trapnell","given":"Cole","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pop","given":"Mihai","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Salzberg","given":"Steven L","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Genome Biology","id":"ITEM-1","issue":"3","issued":{"date-parts":[["2009","1"]]},"page":"R25","title":"Ultrafast and memory-efficient alignment of short DNA sequences to the human genome","type":"article-journal","volume":"10"},"uris":[""]}],"mendeley":{"formattedCitation":"(Langmead et al., 2009)","plainTextFormattedCitation":"(Langmead et al., 2009)","previouslyFormattedCitation":"(Langmead et al., 2009)"},"properties":{"noteIndex":0},"schema":""}(Langmead et al., 2009) (v2.1.0.0), Samtools v0.1.19.0) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1093/bioinformatics/btp324","ISSN":"1367-4803","PMID":"19451168","abstract":"MOTIVATION The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. RESULTS We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows-Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is approximately 10-20x faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. AVAILABILITY .","author":[{"dropping-particle":"","family":"Li","given":"Heng","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Durbin","given":"Richard","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Bioinformatics","id":"ITEM-1","issue":"14","issued":{"date-parts":[["2009","7","15"]]},"page":"1754-1760","title":"Fast and accurate short read alignment with Burrows-Wheeler transform","type":"article-journal","volume":"25"},"uris":[""]}],"mendeley":{"formattedCitation":"(Li and Durbin, 2009)","plainTextFormattedCitation":"(Li and Durbin, 2009)","previouslyFormattedCitation":"(Li and Durbin, 2009)"},"properties":{"noteIndex":0},"schema":""}(Li and Durbin, 2009) and we employed htseq-count -m union -s no -t exon -i gene_name (part of the HTSeq framework, version v0.7.1) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1093/bioinformatics/btu638","ISSN":"1367-4803","PMID":"25260700","abstract":"MOTIVATION: A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard work flows, custom scripts are needed. RESULTS: We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data such as genomic coordinates, sequences, sequencing reads, alignments, gene model information, variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. Availability: HTSeq is released as open-source software under the GNU General Public Licence and available from or from the Python Package Index . CONTACT: sanders@fs.tum.de.","author":[{"dropping-particle":"","family":"Anders","given":"Simon","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pyl","given":"Paul Theodor","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Huber","given":"Wolfgang","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Bioinformatics","id":"ITEM-1","issue":"2","issued":{"date-parts":[["2015","1","15"]]},"page":"166-169","title":"HTSeq--a Python framework to work with high-throughput sequencing data","type":"article-journal","volume":"31"},"uris":[""]}],"mendeley":{"formattedCitation":"(Anders et al., 2015)","plainTextFormattedCitation":"(Anders et al., 2015)","previouslyFormattedCitation":"(Anders et al., 2015)"},"properties":{"noteIndex":0},"schema":""}(Anders et al., 2015)). Trimmomatic (v0.36) was used to remove adaptersADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1093/bioinformatics/btu170","ISSN":"1460-2059","PMID":"24695404","abstract":"MOTIVATION Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. RESULTS The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. AVAILABILITY AND IMPLEMENTATION Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at CONTACT usadel@bio1.rwth-aachen.de SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.","author":[{"dropping-particle":"","family":"Bolger","given":"Anthony M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lohse","given":"Marc","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Usadel","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Bioinformatics","id":"ITEM-1","issue":"15","issued":{"date-parts":[["2014","8","1"]]},"page":"2114-2120","publisher":"Oxford University Press","title":"Trimmomatic: a flexible trimmer for Illumina sequence data","type":"article-journal","volume":"30"},"uris":[""]}],"mendeley":{"formattedCitation":"(Bolger et al., 2014)","plainTextFormattedCitation":"(Bolger et al., 2014)","previouslyFormattedCitation":"(Bolger et al., 2014)"},"properties":{"noteIndex":0},"schema":""}(Bolger et al., 2014). Values throughout are displayed as log2 TPM (transcripts per million) counts; a value of 1 was added prior to log transformation. To identify genes expressed differentially by various cell types, we performed negative binomial tests for paired comparisons by employing the Bioconductor package DESeq2 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1186/s13059-014-0550-8","ISSN":"1474-760X","author":[{"dropping-particle":"","family":"Love","given":"Michael I","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Huber","given":"Wolfgang","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Anders","given":"Simon","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Genome Biology","id":"ITEM-1","issue":"12","issued":{"date-parts":[["2014","12","5"]]},"page":"550","title":"Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2","type":"article-journal","volume":"15"},"uris":[""]}],"mendeley":{"formattedCitation":"(Love et al., 2014)","plainTextFormattedCitation":"(Love et al., 2014)","previouslyFormattedCitation":"(Love et al., 2014)"},"properties":{"noteIndex":0},"schema":""}(Love et al., 2014) (v1.14.1), disabling the default options for independent filtering and Cooks cutoff. We considered genes to be expressed differentially by any comparison when the DESeq2 analysis resulted in a Benjamini-Hochberg–adjusted P value of ≤ 0.05 and a fold change of at least 2. Union gene signatures were calculated using the online tool jVenn ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1186/1471-2105-15-293","ISSN":"1471-2105","PMID":"25176396","abstract":"BACKGROUND Venn diagrams are commonly used to display list comparison. In biology, they are widely used to show the differences between gene lists originating from different differential analyses, for instance. They thus allow the comparison between different experimental conditions or between different methods. However, when the number of input lists exceeds four, the diagram becomes difficult to read. Alternative layouts and dynamic display features can improve its use and its readability. RESULTS jvenn is a new JavaScript library. It processes lists and produces Venn diagrams. It handles up to six input lists and presents results using classical or Edwards-Venn layouts. User interactions can be controlled and customized. Finally, jvenn can easily be embeded in a web page, allowing to have dynamic Venn diagrams. CONCLUSIONS jvenn is an open source component for web environments helping scientists to analyze their data. The library package, which comes with full documentation and an example, is freely available at .","author":[{"dropping-particle":"","family":"Bardou","given":"Philippe","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mariette","given":"Jér?me","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Escudié","given":"Frédéric","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Djemiel","given":"Christophe","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Klopp","given":"Christophe","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"BMC Bioinformatics","id":"ITEM-1","issue":"1","issued":{"date-parts":[["2014","8","29"]]},"page":"293","title":"jvenn: an interactive Venn diagram viewer","type":"article-journal","volume":"15"},"uris":[""]}],"mendeley":{"formattedCitation":"(Bardou et al., 2014)","plainTextFormattedCitation":"(Bardou et al., 2014)","previouslyFormattedCitation":"(Bardou et al., 2014)"},"properties":{"noteIndex":0},"schema":""}(Bardou et al., 2014), of which genes must have common directionality. GSEA, correlations, and heatmaps were generated as previously described ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3775","ISSN":"1529-2908","PMID":"28628092","abstract":"Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.","author":[{"dropping-particle":"","family":"Ganesan","given":"Anusha-Preethi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garrido-Martin","given":"Eva M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alzetani","given":"Aiman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friedmann","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2017","6","19"]]},"page":"940-950","title":"Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer","type":"article-journal","volume":"18"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-2","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]},{"id":"ITEM-3","itemData":{"DOI":"10.1038/ni.3437","ISSN":"1529-2908","PMID":"27089380","abstract":"Natural killer T cells (NKT cells) have stimulatory or inhibitory effects on the immune response that can be attributed in part to the existence of functional subsets of NKT cells. These subsets have been characterized only on the basis of the differential expression of a few transcription factors and cell-surface molecules. Here we have analyzed purified populations of thymic NKT cell subsets at both the transcriptomic level and epigenomic level and by single-cell RNA sequencing. Our data indicated that despite their similar antigen specificity, the functional NKT cell subsets were highly divergent populations with many gene-expression and epigenetic differences. Therefore, the thymus 'imprints' distinct gene programs on subsets of innate-like NKT cells that probably impart differences in proliferative capacity, homing, and effector functions.","author":[{"dropping-particle":"","family":"Engel","given":"Isaac","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chavez","given":"Lukas","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"White","given":"Brandie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chawla","given":"Ashu","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mock","given":"Dennis","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kronenberg","given":"Mitchell","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-3","issue":"6","issued":{"date-parts":[["2016","4","18"]]},"page":"728-739","title":"Innate-like functions of natural killer T cell subsets result from highly divergent gene programs","type":"article-journal","volume":"17"},"uris":[""]}],"mendeley":{"formattedCitation":"(Ganesan et al., 2017; Patil et al., 2018; Engel et al., 2016)","plainTextFormattedCitation":"(Ganesan et al., 2017; Patil et al., 2018; Engel et al., 2016)","previouslyFormattedCitation":"(Ganesan et al., 2017; Patil et al., 2018; Engel et al., 2016)"},"properties":{"noteIndex":0},"schema":""}(Ganesan et al., 2017; Patil et al., 2018; Engel et al., 2016). Genes used in the GSEA analysis are shown (Table S3). For the preservation of complementary signatures, read count data from Cheuk, et al., 2017 ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.immuni.2017.01.009","ISSN":"1097-4180","PMID":"28214226","abstract":"Tissue-resident memory T (Trm) cells form a heterogeneous population that provides localized protection against pathogens. Here, we identify CD49a as a marker that differentiates CD8(+) Trm cells on a compartmental and functional basis. In human skin epithelia, CD8(+)CD49a(+) Trm cells produced interferon-γ, whereas CD8(+)CD49a(-) Trm cells produced interleukin-17 (IL-17). In addition, CD8(+)CD49a(+) Trm cells from healthy skin rapidly induced the expression of the effector molecules perforin and granzyme B when stimulated with IL-15, thereby promoting a strong cytotoxic response. In skin from patients with vitiligo, where melanocytes are eradicated locally, CD8(+)CD49a(+) Trm cells that constitutively expressed perforin and granzyme B accumulated both in the epidermis and dermis. Conversely, CD8(+)CD49a(-) Trm cells from psoriasis lesions predominantly generated IL-17 responses that promote local inflammation in this skin disease. Overall, CD49a expression delineates CD8(+) Trm cell specialization in human epithelial barriers and correlates with the effector cell balance found in distinct inflammatory skin diseases.","author":[{"dropping-particle":"","family":"Cheuk","given":"Stanley","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schlums","given":"Heinrich","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gallais Sérézal","given":"Irène","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Martini","given":"Elisa","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chiang","given":"Samuel C.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Marquardt","given":"Nicole","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gibbs","given":"Anna","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Detlofsson","given":"Ebba","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Introini","given":"Andrea","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Forkel","given":"Marianne","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"H??g","given":"Charlotte","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tjernlund","given":"Annelie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Micha?lsson","given":"Jakob","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Folkersen","given":"Lasse","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mj?sberg","given":"Jenny","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Blomqvist","given":"Lennart","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ehrstr?m","given":"Marcus","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"St?hle","given":"Mona","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bryceson","given":"Yenan T.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Eidsmo","given":"Liv","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Immunity","id":"ITEM-1","issue":"2","issued":{"date-parts":[["2017","2","21"]]},"page":"287-300","title":"CD49a Expression Defines Tissue-Resident CD8(+) T Cells Poised for Cytotoxic Function in Human Skin.","type":"article-journal","volume":"46"},"uris":[""]}],"mendeley":{"formattedCitation":"(Cheuk et al., 2017)","plainTextFormattedCitation":"(Cheuk et al., 2017)","previouslyFormattedCitation":"(Cheuk et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Cheuk et al., 2017), was downloaded from code GSE83637 and differential expression analysis was completed as above. For the murine composite signature ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nature24993","ISSN":"0028-0836","author":[{"dropping-particle":"","family":"Milner","given":"J Justin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Toma","given":"Clara","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yu","given":"Bingfei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Kai","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Omilusik","given":"Kyla","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Phan","given":"Anthony T","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wang","given":"Dapeng","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Getzler","given":"Adam J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nguyen","given":"Toan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Crotty","given":"Shane","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wang","given":"Wei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pipkin","given":"Matthew E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Goldrath","given":"Ananda W.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature","id":"ITEM-1","issued":{"date-parts":[["2017","12","6"]]},"page":"253–257","publisher":"Nature Publishing Group","title":"Runx3 programs CD8+ T cell residency in non-lymphoid tissues and tumours","type":"article-journal","volume":"552"},"uris":[""]}],"mendeley":{"formattedCitation":"(Milner et al., 2017)","plainTextFormattedCitation":"(Milner et al., 2017)","previouslyFormattedCitation":"(Milner et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Milner et al., 2017), orthologues between human and murine signatures were compared using Ensembl to facilitate converting from the murine to human signature, genes that had opposing expression changes were not considered conserved (Table S3). Reactome pathways were generated using the online tool () for tumor TRM-specific genes, a pathway was considered significantly different if the FDR (q) values was ≤ 0.05 (Table S4). Visualizations were generated in ggplot2 using custom scripts, while expression values were calculated using Graphpad Prism7 (v7.0a). For tSNE analysis, the data frame was filtered to genes with mean ≥ 1 TPM counts expression in at least one condition and visualizations created using the top 2000 most variable genes, as calculated in DESeq2ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1186/s13059-014-0550-8","ISSN":"1474-760X","author":[{"dropping-particle":"","family":"Love","given":"Michael I","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Huber","given":"Wolfgang","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Anders","given":"Simon","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Genome Biology","id":"ITEM-1","issue":"12","issued":{"date-parts":[["2014","12","5"]]},"page":"550","title":"Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2","type":"article-journal","volume":"15"},"uris":[""]}],"mendeley":{"formattedCitation":"(Love et al., 2014)","plainTextFormattedCitation":"(Love et al., 2014)","previouslyFormattedCitation":"(Love et al., 2014)"},"properties":{"noteIndex":0},"schema":""}(Love et al., 2014) (v1.16.1); this allowed for unbiased visualization of the Log2 (TPM counts + 1) data, using package Rtsne (v0.13). Co-expression networks were generated in gplots (v3.0.1) using the heatmap2 function, while weighted correlation analysis was completed using WGCNA ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1186/1471-2105-9-559","ISSN":"1471-2105","PMID":"19114008","abstract":"BACKGROUND: Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial.\n\nRESULTS: The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings.\n\nCONCLUSION: The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at .","author":[{"dropping-particle":"","family":"Langfelder","given":"Peter","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Horvath","given":"Steve","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"BMC bioinformatics","id":"ITEM-1","issue":"1","issued":{"date-parts":[["2008","1","29"]]},"language":"En","page":"559","publisher":"BioMed Central","title":"WGCNA: an R package for weighted correlation network analysis.","type":"article-journal","volume":"9"},"uris":[""]}],"mendeley":{"formattedCitation":"(Langfelder and Horvath, 2008)","plainTextFormattedCitation":"(Langfelder and Horvath, 2008)","previouslyFormattedCitation":"(Langfelder and Horvath, 2008)"},"properties":{"noteIndex":0},"schema":""}(Langfelder and Horvath, 2008) (v1.61) from the Log2 (TPM counts + 1) data matrix and the function TOMsimilarityfromExpr (Beta = 5) and exportNetworkToCytoscape, weighted = true, threshold = 0.05. Highlighted genes were ordered as per the order in the correlation plot. Networks were generated in Gephi (v0.92) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.18632/aging.101127","ISSN":"19454589","PMID":"27992856","abstract":"Cancer-associated fibroblasts (CAF) remain a poorly characterized, heterogeneous cell population. Here we characterized two previously described tumor-promoting CAF sub-types, smooth muscle actin (SMA)-positive myofibroblasts and senescent fibroblasts, identifying a novel link between the two. Analysis of CAF cultured ex vivo, showed that senescent CAF are predominantly SMA-positive; this was confirmed by immunochemistry in head & neck (HNSCC) and esophageal (EAC) cancers. In vitro, we found that fibroblasts induced to senesce develop molecular, ultrastructural and contractile features typical of myofibroblasts and this is dependent on canonical TGF-β signaling. Similar to TGF-β1-generated myofibroblasts, these cells secrete soluble factors that promote tumor cell motility. However, RNA-sequencing revealed significant transcriptomic differences between the two SMA-positive CAF groups, particularly in genes associated with extracellular matrix (ECM) deposition and organization, which differentially promote tumor cell invasion. Notably, second harmonic generation imaging and bioinformatic analysis of SMA-positive human HNSCC and EAC showed that collagen fiber organization correlates with poor prognosis, indicating that heterogeneity within the SMA-positive CAF population differentially impacts on survival. These results show that non-fibrogenic, SMA-positive myofibroblasts can be directly generated through induction of fibroblast senescence and suggest that senescence and myofibroblast differentiation are closely linked processes.","author":[{"dropping-particle":"","family":"Mellone","given":"Massimiliano","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hanley","given":"Christopher J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thirdborough","given":"Steve","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garcia","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Jeongmin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tod","given":"Joanne","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Frampton","given":"Steve","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jenei","given":"Veronika","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Moutasim","given":"Karwan A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kabir","given":"Tasnuva D.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Brennan","given":"Peter A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Venturi","given":"Giulia","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ford","given":"Kirsty","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Herranz","given":"Nicolas","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lim","given":"Kue Peng","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lambert","given":"Daniel W.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Prime","given":"Stephen S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Underwood","given":"Timothy J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Eliceiri","given":"Kevin W.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woelk","given":"Christopher","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V.","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gil","given":"Jesus","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Aging","id":"ITEM-1","issue":"1","issued":{"date-parts":[["2016","12","15"]]},"page":"114-132","title":"Induction of fibroblast senescence generates a non-fibrogenic myofibroblast phenotype that differentially impacts on cancer prognosis","type":"article-journal","volume":"9"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1158/0008-5472.CAN-15-3121","ISSN":"0008-5472","PMID":"27206847","abstract":"Antibodies that block T-cell-regulatory checkpoints have recently emerged as a transformative approach to cancer treatment. However, the clinical efficacy of checkpoint blockade depends upon inherent tumor immunogenicity, with variation in infiltrating T cells contributing to differences in objective response rates. Here, we sought to understand the molecular correlates of tumor-infiltrating T lymphocytes (TIL) in squamous cell carcinoma (SCC), using a systems biologic approach to integrate publicly available omics datasets with histopathologic features. We provide evidence that links TIL abundance and therapeutic outcome to the regulation of tumor glycolysis by EGFR and HIF, both of which are attractive molecular targets for use in combination with immunotherapeutics. Cancer Res; 76(14); 4136-48. ?2016 AACR.","author":[{"dropping-particle":"","family":"Ottensmeier","given":"Christian H.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Perry","given":"Kate L.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harden","given":"Elena L.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Stasakova","given":"Jana","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jenei","given":"Veronika","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Fleming","given":"Jason","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Jeongmin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woelk","given":"Christopher H.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thirdborough","given":"Stephen M.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Cancer Research","id":"ITEM-2","issue":"14","issued":{"date-parts":[["2016","7","15"]]},"page":"4136-4148","title":"Upregulated Glucose Metabolism Correlates Inversely with CD8 ⁺ T-cell Infiltration and Survival in Squamous Cell Carcinoma","type":"article-journal","volume":"76"},"uris":[""]}],"mendeley":{"formattedCitation":"(Mellone et al., 2016; Ottensmeier et al., 2016)","plainTextFormattedCitation":"(Mellone et al., 2016; Ottensmeier et al., 2016)","previouslyFormattedCitation":"(Mellone et al., 2016; Ottensmeier et al., 2016)"},"properties":{"noteIndex":0},"schema":""}(Mellone et al., 2016; Ottensmeier et al., 2016) using Fruchterman Reingold and Noverlap functions. The size and color were scaled according to the Average Degree as calculated in Gephi, while the edge width was scaled according to the WGCNA edge weight value. The statistical analysis of the overlap between gene sets was calculated in R (v3.5.0) using the fisher.test function (Stats – v3.5.0) using the number of total quantified genes used for DESeq2, as the total value (20231), with alternative="greater". Single-cell RNA-seq analysis Raw 10x data (Table S1) was processed as previously described ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-1","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]}],"mendeley":{"formattedCitation":"(Patil et al., 2018)","plainTextFormattedCitation":"(Patil et al., 2018)","previouslyFormattedCitation":"(Patil et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Patil et al., 2018), merging multiple sequencing runs using cellranger count function in cell ranger, then merging multiple cell types with cell ranger aggr (v2.0.2). The merged data was transferred to the R statistical environment for analysis using the package Seurat ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.cell.2015.05.002","ISSN":"00928674","author":[{"dropping-particle":"","family":"Macosko","given":"Evan?Z.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Basu","given":"Anindita","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Satija","given":"Rahul","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nemesh","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Shekhar","given":"Karthik","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Goldman","given":"Melissa","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tirosh","given":"Itay","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bialas","given":"Allison?R.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kamitaki","given":"Nolan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Martersteck","given":"Emily?M.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Trombetta","given":"John?J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weitz","given":"David?A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanes","given":"Joshua?R.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Shalek","given":"Alex?K.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Regev","given":"Aviv","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"McCarroll","given":"Steven?A.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Cell","id":"ITEM-1","issue":"5","issued":{"date-parts":[["2015"]]},"page":"1202-1214","publisher":"Elsevier Inc.","title":"Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets","type":"article-journal","volume":"161"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-2","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]}],"mendeley":{"formattedCitation":"(Macosko et al., 2015; Patil et al., 2018)","plainTextFormattedCitation":"(Macosko et al., 2015; Patil et al., 2018)","previouslyFormattedCitation":"(Macosko et al., 2015; Patil et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Macosko et al., 2015; Patil et al., 2018) (v2.2.1). Only cells expressing more than 200 genes and genes expressed in at least 3 cells were included in the analysis. The data was then log-normalized and scaled per cell and variable genes were detected. Transcriptomic data from each cell was then further normalized by the number of UMI-detected and mitochondrial genes. A principal component analysis was then run on variable genes, and the first 8 principal components (PCs) were selected for further analyses based on the standard deviation of PCs, as determined by an “elbow plot” in Seurat. Cells were clustered using the FindClusters function in Seurat with default settings, resolution = 0.6 and 8 PCs. Differential expression between clusters was determined by converting the data to CPM (counts per million) and analyzing cluster specific differences using MAST (q ≤ 0.01, v1.2.1) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nmeth.4612","ISSN":"1548-7091","PMID":"29481549","abstract":"Many methods have been used to determine differential gene expression from single-cell RNA (scRNA)-seq data. We evaluated 36 approaches using experimental and synthetic data and found considerable differences in the number and characteristics of the genes that are called differentially expressed. Prefiltering of lowly expressed genes has important effects, particularly for some of the methods developed for bulk RNA-seq data analysis. However, we found that bulk RNA-seq analysis methods do not generally perform worse than those developed specifically for scRNA-seq. We also present conquer, a repository of consistently processed, analysis-ready public scRNA-seq data sets that is aimed at simplifying method evaluation and reanalysis of published results. Each data set provides abundance estimates for both genes and transcripts, as well as quality control and exploratory analysis reports.","author":[{"dropping-particle":"","family":"Soneson","given":"Charlotte","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Robinson","given":"Mark D","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Methods","id":"ITEM-1","issue":"4","issued":{"date-parts":[["2018","2","26"]]},"page":"255-261","publisher":"Nature Publishing Group","title":"Bias, robustness and scalability in single-cell differential expression analysis","type":"article-journal","volume":"15"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-2","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]},{"id":"ITEM-3","itemData":{"DOI":"10.1186/s13059-015-0844-5","ISBN":"10.1186/s13059-015-0844-5","ISSN":"1474760X","PMID":"26653891","abstract":"Single-cell transcriptomics reveals gene expression heterogeneity but suffers from stochastic dropout and characteristic bimodal expression distributions in which expression is either strongly non-zero or non-detectable. We propose a two-part, generalized linear model for such bimodal data that parameterizes both of these features. We argue that the cellular detection rate, the fraction of genes expressed in a cell, should be adjusted for as a source of nuisance variation. Our model provides gene set enrichment analysis tailored to single-cell data. It provides insights into how networks of co-expressed genes evolve across an experimental treatment. MAST is available at .","author":[{"dropping-particle":"","family":"Finak","given":"Greg","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"McDavid","given":"Andrew","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yajima","given":"Masanao","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Deng","given":"Jingyuan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gersuk","given":"Vivian","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Shalek","given":"Alex K","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Slichter","given":"Chloe K","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Miller","given":"Hannah W","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"McElrath","given":"M Juliana","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Prlic","given":"Martin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Linsley","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gottardo","given":"Raphael","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Genome Biology","id":"ITEM-3","issue":"1","issued":{"date-parts":[["2015","12","10"]]},"page":"278","publisher":"BioMed Central","title":"MAST: A flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data","type":"article-journal","volume":"16"},"uris":[""]}],"mendeley":{"formattedCitation":"(Soneson and Robinson, 2018; Patil et al., 2018; Finak et al., 2015)","plainTextFormattedCitation":"(Soneson and Robinson, 2018; Patil et al., 2018; Finak et al., 2015)","previouslyFormattedCitation":"(Soneson and Robinson, 2018; Patil et al., 2018; Finak et al., 2015)"},"properties":{"noteIndex":0},"schema":""}(Soneson and Robinson, 2018; Patil et al., 2018; Finak et al., 2015). A gene was considered significantly different, only if the gene was commonly positively enriched in every comparison for a singular cluster ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-1","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1038/ni.3437","ISSN":"1529-2908","PMID":"27089380","abstract":"Natural killer T cells (NKT cells) have stimulatory or inhibitory effects on the immune response that can be attributed in part to the existence of functional subsets of NKT cells. These subsets have been characterized only on the basis of the differential expression of a few transcription factors and cell-surface molecules. Here we have analyzed purified populations of thymic NKT cell subsets at both the transcriptomic level and epigenomic level and by single-cell RNA sequencing. Our data indicated that despite their similar antigen specificity, the functional NKT cell subsets were highly divergent populations with many gene-expression and epigenetic differences. Therefore, the thymus 'imprints' distinct gene programs on subsets of innate-like NKT cells that probably impart differences in proliferative capacity, homing, and effector functions.","author":[{"dropping-particle":"","family":"Engel","given":"Isaac","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chavez","given":"Lukas","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"White","given":"Brandie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chawla","given":"Ashu","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mock","given":"Dennis","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kronenberg","given":"Mitchell","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-2","issue":"6","issued":{"date-parts":[["2016","4","18"]]},"page":"728-739","title":"Innate-like functions of natural killer T cell subsets result from highly divergent gene programs","type":"article-journal","volume":"17"},"uris":[""]}],"mendeley":{"formattedCitation":"(Patil et al., 2018; Engel et al., 2016)","plainTextFormattedCitation":"(Patil et al., 2018; Engel et al., 2016)","previouslyFormattedCitation":"(Patil et al., 2018; Engel et al., 2016)"},"properties":{"noteIndex":0},"schema":""}(Patil et al., 2018; Engel et al., 2016). Further visualizations of exported normalized data were generated using the Seurat package and custom R scripts. Cell-state hierarchy maps were generated using Monocle (v2.6.1) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nbt.2859","ISSN":"1087-0156","PMID":"24658644","abstract":"Defining the transcriptional dynamics of a temporal process such as cell differentiation is challenging owing to the high variability in gene expression between individual cells. Time-series gene expression analyses of bulk cells have difficulty distinguishing early and late phases of a transcriptional cascade or identifying rare subpopulations of cells, and single-cell proteomic methods rely on a priori knowledge of key distinguishing markers. Here we describe Monocle, an unsupervised algorithm that increases the temporal resolution of transcriptome dynamics using single-cell RNA-Seq data collected at multiple time points. Applied to the differentiation of primary human myoblasts, Monocle revealed switch-like changes in expression of key regulatory factors, sequential waves of gene regulation, and expression of regulators that were not known to act in differentiation. We validated some of these predicted regulators in a loss-of function screen. Monocle can in principle be used to recover single-cell gene expression kinetics from a wide array of cellular processes, including differentiation, proliferation and oncogenic transformation.","author":[{"dropping-particle":"","family":"Trapnell","given":"Cole","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Cacchiarelli","given":"Davide","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Grimsby","given":"Jonna","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pokharel","given":"Prapti","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Li","given":"Shuqiang","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Morse","given":"Michael","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lennon","given":"Niall J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Livak","given":"Kenneth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mikkelsen","given":"Tarjei S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Rinn","given":"John L","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Biotechnology","id":"ITEM-1","issue":"4","issued":{"date-parts":[["2014","4","23"]]},"page":"381-386","title":"The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells","type":"article-journal","volume":"32"},"uris":[""]}],"mendeley":{"formattedCitation":"(Trapnell et al., 2014)","plainTextFormattedCitation":"(Trapnell et al., 2014)","previouslyFormattedCitation":"(Trapnell et al., 2014)"},"properties":{"noteIndex":0},"schema":""}(Trapnell et al., 2014) and default settings with expressionFamily=negbinomial.size(), lowerDetectionLimit = 1 and mean_expression ≥ 0.1, including the most variable genes identified in Seurat for consistency. Average expression across a cell cluster was calculated using the AverageExpression function, and downsampling was achieved using the SubsetData function (both in Seurat). Distance between clusters was calculated by calculating a particular cells location in PCA space (Principle component 1:3) using the function GetCellembeddings (in Seurat), the values for each cell were then scaled per column (Scale function, core R) where described, and finally a distance matrix was calculated (dist function, core R, method = euclidean). This matrix was filtered to the cells assigned to cluster 1, and the mean distance of each cell in cluster 1 to all cells in each of the remaining TRM clusters (2,3,4,5) was calculated. The clustering analysis was completed using the hclust function in R (stats, R v3.5.0) with average linkage and generated from the spearman correlation analysis of each cell’s location in PCA space (as above). SAVER co-expression analysis ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/s41592-018-0033-z","ISSN":"1548-7105","abstract":"In single-cell RNA sequencing (scRNA-seq) studies, only a small fraction of the transcripts present in each cell are sequenced. This leads to unreliable quantification of genes with low or moderate expression, which hinders downstream analysis. To address this challenge, we developed SAVER (single-cell analysis via expression recovery), an expression recovery method for unique molecule index (UMI)-based scRNA-seq data that borrows information across genes and cells to provide accurate expression estimates for all genes.","author":[{"dropping-particle":"","family":"Huang","given":"Mo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wang","given":"Jingshu","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Torre","given":"Eduardo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Dueck","given":"Hannah","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Shaffer","given":"Sydney","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Bonasio","given":"Roberto","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Murray","given":"John I","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Raj","given":"Arjun","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Li","given":"Mingyao","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhang","given":"Nancy R","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Methods","id":"ITEM-1","issue":"7","issued":{"date-parts":[["2018"]]},"page":"539-542","title":"SAVER: gene expression recovery for single-cell RNA sequencing","type":"article-journal","volume":"15"},"uris":[""]}],"mendeley":{"formattedCitation":"(Huang et al., 2018)","plainTextFormattedCitation":"(Huang et al., 2018)","previouslyFormattedCitation":"(Huang et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Huang et al., 2018) was completed on the raw-UMI counts of the TRM cells (clusters 1-5) and the non-TRM cells (remaining cells) using the function saver (v1.1.1) with pred.genes.only = TRUE, estimates.only = FALSE on transcripts assigned as uniquely enriched in cluster 2, removing genes not expressed in any cells in the non-TRM compartment. Correlation values were isolated using the cor.genes function in SAVER and co-expression plots generated as described above. Smart-seq2 single cell analysis (Table S1) was completed as previously described using TraCeR ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nmeth.3800","ISSN":"1548-7105","PMID":"26950746","abstract":"We developed TraCeR, a computational method to reconstruct full-length, paired T cell receptor (TCR) sequences from T lymphocyte single-cell RNA sequence data. TraCeR links T cell specificity with functional response by revealing clonal relationships between cells alongside their transcriptional profiles. We found that T cell clonotypes in a mouse Salmonella infection model span early activated CD4(+) T cells as well as mature effector and memory cells.","author":[{"dropping-particle":"","family":"Stubbington","given":"Michael J T","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"L?nnberg","given":"Tapio","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Proserpio","given":"Valentina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clare","given":"Simon","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Speak","given":"Anneliese O","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Dougan","given":"Gordon","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Teichmann","given":"Sarah A","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature methods","id":"ITEM-1","issue":"4","issued":{"date-parts":[["2016","4","28"]]},"language":"en","page":"329-332","publisher":"Cold Spring Harbor Labs Journals","title":"T cell fate and clonality inference from single-cell transcriptomes.","type":"article-journal","volume":"13"},"uris":[""]},{"id":"ITEM-2","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-2","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]}],"mendeley":{"formattedCitation":"(Stubbington et al., 2016; Patil et al., 2018)","plainTextFormattedCitation":"(Stubbington et al., 2016; Patil et al., 2018)","previouslyFormattedCitation":"(Stubbington et al., 2016; Patil et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Stubbington et al., 2016; Patil et al., 2018) (v0.5.1) and custom scripts to identify αβ chains, showing only cells were both TCR chains were detected and to remove cells with low QC values as previously described ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-1","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]}],"mendeley":{"formattedCitation":"(Patil et al., 2018)","plainTextFormattedCitation":"(Patil et al., 2018)","previouslyFormattedCitation":"(Patil et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Patil et al., 2018). Here, we removed cells with fewer than 200,000 reads and less than 30% of sequenced bases were assigned to UTRs and coding regions of mRNA. Samples were mapped as described previously ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-1","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]}],"mendeley":{"formattedCitation":"(Patil et al., 2018)","plainTextFormattedCitation":"(Patil et al., 2018)","previouslyFormattedCitation":"(Patil et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Patil et al., 2018), and the data was log transformed and displayed as normalized TPM counts; a value of 1 was added prior to log transformation. Visualizations were completed in ggplot2, Prism (v7.0a) and custom scripts in TraCer. A cell was considered expanded when both the most highly expressed α and β TCR chain sequences matched other cells with the same stringent criteria. Cells were considered not expanded when neither α or β TCR productive chain sequences matched those of any other cells. A cell was considered PD-1+ or TIM-3+ when the expression of PDCD1 or HAVCR2 was greater than 10 TPM counts, while a cell was considered cycling if expression of cell cycle genes TOP2A and/or MKI67 was greater than 10 TPM counts. Differential expression profiling was completed using MAST ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1186/s13059-015-0844-5","ISBN":"10.1186/s13059-015-0844-5","ISSN":"1474760X","PMID":"26653891","abstract":"Single-cell transcriptomics reveals gene expression heterogeneity but suffers from stochastic dropout and characteristic bimodal expression distributions in which expression is either strongly non-zero or non-detectable. We propose a two-part, generalized linear model for such bimodal data that parameterizes both of these features. We argue that the cellular detection rate, the fraction of genes expressed in a cell, should be adjusted for as a source of nuisance variation. Our model provides gene set enrichment analysis tailored to single-cell data. It provides insights into how networks of co-expressed genes evolve across an experimental treatment. MAST is available at .","author":[{"dropping-particle":"","family":"Finak","given":"Greg","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"McDavid","given":"Andrew","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yajima","given":"Masanao","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Deng","given":"Jingyuan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gersuk","given":"Vivian","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Shalek","given":"Alex K","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Slichter","given":"Chloe K","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Miller","given":"Hannah W","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"McElrath","given":"M Juliana","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Prlic","given":"Martin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Linsley","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gottardo","given":"Raphael","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Genome Biology","id":"ITEM-1","issue":"1","issued":{"date-parts":[["2015","12","10"]]},"page":"278","publisher":"BioMed Central","title":"MAST: A flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data","type":"article-journal","volume":"16"},"uris":[""]}],"mendeley":{"formattedCitation":"(Finak et al., 2015)","plainTextFormattedCitation":"(Finak et al., 2015)","previouslyFormattedCitation":"(Finak et al., 2015)"},"properties":{"noteIndex":0},"schema":""}(Finak et al., 2015) (q ≤ 0.05) as previously described ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1126/sciimmunol.aan8664","ISSN":"2470-9468","PMID":"29352091","abstract":"1,5,6 CD4 + cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and het-erogeneity, especially in relation to other well-described CD4 + memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the T EMRA (effector memory T cells express-ing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4 + T cells in the central memory (T CM) and effector memory (T EM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-T EMRA cells show marked clonal expansion compared with T CM and T EM cells and that most of CD4-T EMRA were dengue virus (DENV)–specific in donors with previous DENV infection. The profile of CD4-T EMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the T EMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.","author":[{"dropping-particle":"","family":"Patil","given":"Veena S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Madrigal","given":"Ariel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmiedel","given":"Benjamin J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"O’Rourke","given":"Patrick","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Silva","given":"Aruna D.","non-dropping-particle":"de","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Harris","given":"Eva","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Peters","given":"Bjoern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Gregory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Weiskopf","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sette","given":"Alessandro","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Science Immunology","id":"ITEM-1","issue":"19","issued":{"date-parts":[["2018","1","19"]]},"page":"8664","title":"Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis","type":"article-journal","volume":"3"},"uris":[""]}],"mendeley":{"formattedCitation":"(Patil et al., 2018)","plainTextFormattedCitation":"(Patil et al., 2018)","previouslyFormattedCitation":"(Patil et al., 2018)"},"properties":{"noteIndex":0},"schema":""}(Patil et al., 2018). Matched flow cytometry data was analyzed using FlowJo (v10.4.1), values and gates were exported into ggplot and “in-silico gates” were applied using custom scripts in R. Given ~85% of the CD103+ cells were TIM-3+ from our flow cytometry data, cells were broadly classified into TRM or non-TRM based on an individual cell’s protein expression (FACS gating) for patient 53. Where there was no available cell-specific associated protein data (patient 54), CD3+ T cells were classified based on the lack of expression of CD4 and FOXP3, to remove CD4+ cells. Next, we stratified the single cell transcriptomes into TRM or non-TRM cells when expression of TRM associated genes, ITGAE (CD103), RBPJ and/or ZNF683 (HOBIT) were greater than 10 TPM counts, the classification of each single cell library is summarized in Table S12. Differential gene expression analysis was completed as above.Multiplex immunohistochemistryPatients included in this cohort had a known diagnosis of lung cancer. 23 patients were selected in total, categorizing the donors using criteria previously reportedADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/ni.3775","ISSN":"1529-2908","PMID":"28628092","abstract":"Therapies that boost the anti-tumor responses of cytotoxic T lymphocytes (CTLs) have shown promise; however, clinical responses to the immunotherapeutic agents currently available vary considerably, and the molecular basis of this is unclear. We performed transcriptomic profiling of tumor-infiltrating CTLs from treatment-naive patients with lung cancer to define the molecular features associated with the robustness of anti-tumor immune responses. We observed considerable heterogeneity in the expression of molecules associated with activation of the T cell antigen receptor (TCR) and of immunological-checkpoint molecules such as 4-1BB, PD-1 and TIM-3. Tumors with a high density of CTLs showed enrichment for transcripts linked to tissue-resident memory cells (TRM cells), such as CD103, and CTLs from CD103(hi) tumors displayed features of enhanced cytotoxicity. A greater density of TRM cells in tumors was predictive of a better survival outcome in lung cancer, and this effect was independent of that conferred by CTL density. Here we define the 'molecular fingerprint' of tumor-infiltrating CTLs and identify potentially new targets for immunotherapy.","author":[{"dropping-particle":"","family":"Ganesan","given":"Anusha-Preethi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Clarke","given":"James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wood","given":"Oliver","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Garrido-Martin","given":"Eva M","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chee","given":"Serena J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mellows","given":"Toby","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samaniego-Castruita","given":"Daniela","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Singh","given":"Divya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Seumois","given":"Grégory","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Alzetani","given":"Aiman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Woo","given":"Edwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Friedmann","given":"Peter S","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"V","family":"King","given":"Emma","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Thomas","given":"Gareth J","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sanchez-Elsner","given":"Tilman","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vijayanand","given":"Pandurangan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ottensmeier","given":"Christian H","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Immunology","id":"ITEM-1","issue":"8","issued":{"date-parts":[["2017","6","19"]]},"page":"940-950","title":"Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer","type":"article-journal","volume":"18"},"uris":[""]}],"mendeley":{"formattedCitation":"(Ganesan et al., 2017)","plainTextFormattedCitation":"(Ganesan et al., 2017)","previouslyFormattedCitation":"(Ganesan et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Ganesan et al., 2017). A multiplexed IHC method was utilized for repeated staining of a single paraffin-embedded tissue slide. Deparaffinisation, rehydration, antigen retrieval and IHC staining was carried out using a Dako PT Link Autostainer. Antigen retrieval was performed using the EnVision FLEX Target Retrieval Solution, High pH (Agilent Dako) for all antibodies. The slide was first stained with a standard primary antibody followed by an appropriate biotin-linked secondary antibody and horseradish peroxidase (HRP)-conjugated streptavidin to amplify the signal. Peroxidase-labelled compounds were revealed using 3-amino-9-ethylcarbazole (AEC), an aqueous substrate that results in red staining, or DAB that results in brown staining, and counter stained using hematoxylin (blue).The slides were stained initially with Cytokeratin (pre-diluted, Clone AE1/AE3; Agilent Dako) then sequentially with anti-CD8α (pre-diluted Kit IR62361-2; clone C8/144B; Agilent Dako), anti-CD103 (1:500; EPR4166(2); abcam) and anti-TIM-3 (1:50; D5D5R; Cell Signaling Technology). The slides were scanned at high resolution using a Zeiss Axio Scan.Z1 with a 20x air immersion objective. Between each staining iteration, antigen retrieval was performed along with removal of the labile AEC staining and denaturation of the preceding antibodies using a set of organic solvent based de-staining buffers; 50% ethanol for 2 minutes; 100% ethanol for 2 minutes; 100% xylene for 2 minutes; 100% ethanol for 2 minutes; 50% ethanol for 2 minutes. This process did not affect DAB staining. The process was repeated for each of the antibodies. Bright field images were separated into color channels in imaging processing software ImageJ FIJI ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nmeth.2019","ISBN":"1548-7105 (Electronic)\\r1548-7091 (Linking)","ISSN":"1548-7091","PMID":"22743772","author":[{"dropping-particle":"","family":"Schindelin","given":"Johannes","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Arganda-Carreras","given":"Ignacio","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Frise","given":"Erwin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kaynig","given":"Verena","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Longair","given":"Mark","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Pietzsch","given":"Tobias","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Preibisch","given":"Stephan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Rueden","given":"Curtis","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Saalfeld","given":"Stephan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmid","given":"Benjamin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tinevez","given":"Jean-Yves","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"White","given":"Daniel James","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hartenstein","given":"Volker","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Eliceiri","given":"Kevin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tomancak","given":"Pavel","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Cardona","given":"Albert","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Methods","id":"ITEM-1","issued":{"date-parts":[["2012","6","28"]]},"page":"676","publisher":"Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.","title":"Fiji: an open-source platform for biological-image analysis","type":"article-journal","volume":"9"},"uris":[""]}],"mendeley":{"formattedCitation":"(Schindelin et al., 2012)","plainTextFormattedCitation":"(Schindelin et al., 2012)","previouslyFormattedCitation":"(Schindelin et al., 2012)"},"properties":{"noteIndex":0},"schema":""}(Schindelin et al., 2012) (ImageJ Windows 64-bit final version). For the TILhighTRMhigh and TILlowTRMlow tumors the number of CD8+CD103+TIM3+ cells were quantified manually. Two samples with ≤ 3 CD8+CD103+ CTLs quantified were removed, to prevent calculating percentages of single events, resulting in a final number of 21 samples. These images were processed and combined to create pseudo-color multiplexed images. The raw counts for each protein, individually and together are presented in Table S11, as the number of cells per 0.15mm2. OMNI-ATAC-seqCTLs were FACS sorted from cryopreserved lung cancer samples as described above, using the following antibody cocktail: anti-CD45-AlexaFluor700 (HI30; BioLegend); anti-CD3-APC-Cy7 (SK7; BioLegend); anti-CD8A-PerCP-Cy5.5 (SK1; BioLegend); anti-CD103-Pe-Cy7 (Ber-ACT8; BioLegend); anti-CD127-APC (eBioRDR5; ThermoFisher); anti-TIM-3-BV605 (F38-2E2; BioLegend). Cells were counter stained with anti-CD19/20-PE-Dazzle (HIB19/2H7; BioLegend); anti-CD14-PE-Dazzle (HCD14; BioLegend); and anti-CD4-BV510 (OKT4; BioLegend). Dead cells were discriminated using PI. Samples were sorted into low retention 1.5ml eppendorfs containing 250 μL FBS and 250 μL PBS. Three to six donors were pooled together to guarantee sufficient cell numbers. For each pool of cells, two or three technical replicates of 15,000 – 25,000 CTLs were generated for each library. OMNI-ATAC-seq was performed as described in Corces, et al., with minor modifications. Isolated nuclei were incubated with tagmentation mix (2X TD buffer, 2.5 ?L transposase enzyme from Nextera kit, Illuminia) at 37°C for 30 minutes in a thermomixer, shaking at 1000 RPM ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1038/nmeth.4396","ISBN":"0026101505","ISSN":"15487105","PMID":"28846090","abstract":"We present Omni-ATAC, an improved ATAC-seq protocol for chromatin accessibility profiling that works across multiple applications with substantial improvement of signal-to-background ratio and information content. The Omni-ATAC protocol generates chromatin accessibility profiles from archival frozen tissue samples and 50-μm sections, revealing the activities of disease-associated DNA elements in distinct human brain structures. The Omni-ATAC protocol enables the interrogation of personal regulomes in tissue context and translational studies.","author":[{"dropping-particle":"","family":"Corces","given":"M. Ryan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Trevino","given":"Alexandro E.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hamilton","given":"Emily G.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Greenside","given":"Peyton G.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sinnott-Armstrong","given":"Nicholas A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Vesuna","given":"Sam","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Satpathy","given":"Ansuman T.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Rubin","given":"Adam J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Montine","given":"Kathleen S.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wu","given":"Beijing","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kathiria","given":"Arwa","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Cho","given":"Seung Woo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mumbach","given":"Maxwell R.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Carter","given":"Ava C.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kasowski","given":"Maya","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Orloff","given":"Lisa A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Risca","given":"Viviana I.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kundaje","given":"Anshul","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Khavari","given":"Paul A.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Montine","given":"Thomas J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Greenleaf","given":"William J.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chang","given":"Howard Y.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Nature Methods","id":"ITEM-1","issue":"10","issued":{"date-parts":[["2017","8","28"]]},"page":"959-962","publisher":"Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.","title":"An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues","type":"article-journal","volume":"14"},"uris":[""]}],"mendeley":{"formattedCitation":"(Corces et al., 2017)","plainTextFormattedCitation":"(Corces et al., 2017)","previouslyFormattedCitation":"(Corces et al., 2017)"},"properties":{"noteIndex":0},"schema":""}(Corces et al., 2017). Following tagmentation, the product was eluted in 0.1X Tris-EDTA buffer using DNA Clean and Concentrator-5 kit (Zymo). The Purified product was pre-amplified for 5 cycles using Kappa 2X enzyme along with Nextera indexes (Illumina) and based on qPCR amplification, an additional 7 cycles of amplification was performed for 20,000 cells. The PCR amplified product was purified using DNA Clean and Concentrator-5 kit (Zymo), and size selection was done using AMPure XP beads (Beckman Coulter). Finally, concentration and quality of libraries were determined by picogreen and bioAnalyzer assays. Equimolar libraries were sequenced as above, or on a NovaSeq 6000 for sequencing.Next, technical replicates were randomly down sampled to between 25,000,000 to 40,000,000 total reads (Table S1) and merged using Bash scripts, resulting in two TIM-3+IL-7R– TRM pools and two non- TRM pools. These reads were mapped to hg19 with bowtie2 (v2.3.3.1). Chromosomes 1-22, and X were retained, chrY, chrM, and other arbitrary chromosome information based reads were removed. Samtools (v1.9) was used to get the uniquely mappable reads, only reads MAPQ ≥ 30 were considered. Duplicate reads are removed by "MarkDuplicates" utility of Picard tool (v 2.18.14). Before peak calling, tag align files were created, by shifting forward strands by 4 bases, and reverse strands by 5 bases (TN5 shift). Peaks were identified with MACS2 (v 2.1.1.20160309) using the function. -f BED -g 'hs' -q 0.01 --nomodel --nolambda --keep-dup all --shift -100 --extsize 200. BamCoverage (v2.4.2) was used for converting bam files into bigwig, and further UCSC track generation (same normalization across all ATACseq and RNAseq samples), as per the following example: bamCoverage -b TIL_103pos.bam -o TIL_103pos_NormCov.bw -of bigwig -bs 10 --normalizeTo1x 2864785220 --normalizeUsingRPKM -e 200. The R package DiffBind (v2.2.12) was used to highlight differentially accessible peaks (based on DEseq2). R packages of org.Hs.eg.db (v3.4.0 and TxDb.Hsapiens.UCSC.hg19.knownGene (v3.2.2) were used to annotate peaks. Following differential expression peaks were filtered to those within 5kb of a transcription start site to focus directly on promoter accessibility. The correlation plot (spearman) was completed as described above, using all identified peaks. The plot was clustered according to complete linkage. ACCESSION CODESSequencing data has been uploaded onto the Gene Expression Omnibus (accession code GSE111898). Other Statistical Analysis The significance of differences among matched samples were determined by a Wilcoxon rank-sum test for paired data, or a Mann-Whitney test for non-paired data, unless otherwise stated. Statistical analyses were performed using Graphpad Prism7 (v7.0a). Spearman correlation coefficient (r value) was used to access significance of correlations between the levels of any two components of interest. Supplemental Material Fig. S1 includes additional analysis on lung-resident TRM cells. Fig. S2 provides additional information regarding the breakdown per donor in each cluster and expression of TCF7. Fig. S3 demonstrates additional transcripts identified as co-expressed in a particular cluster of tumor TRM cells. Fig. S4 presents additional data regarding TRM cells in the context of anti-PD-1 therapy. Table. S1 provides matched clinical data for the patient samples used in this study. Table. S2 includes the output and additional analysis of the differentially expressed genes in the lung TRM cell population. Table. S3 presents the genes used for GSEA analysis. Table. S4 provides further information regarding ‘shared tissue residency’ and ‘Tumor TRM-enriched’ transcripts. Table. S5 includes additional information regarding the transcriptome of TRM cells following ex-vivo stimulation. Table. S6 comprises output of TCR-seq analysis. Table. S7 covers the single cell transcriptomic analysis of clusters of tumor TRM cells. Table. S8 contains the output of single cell TCR-seq analysis. Table. S9 incorporates single cell transcriptomic analysis of TIM-3+ TRM cells. Table. S10 presents transcriptomic and protein co-expression analysis of tumor TRM and non-TRM cells. Table. S11 provides raw data associated with the immunohistochemistry analysis. Table. S12 contains single cell transcriptomic and TCR-seq analysis of TRM and non-TRM cells pre- and post-anti-PD-1 therapy.SUPPLEMENTARY LEGENDSFigure. S1. Validation of TRM phenotype. (A) tSNE plot of lung TRM (CD103+) and non-TRM (CD103–) CTLs. Each symbol represents an individual patient sample (n = 21 non-TRM; n = 20 TRM). (B) RNA-seq analysis of transcripts (one per row) expressed differentially between lung TRM and lung non-TRM, (pairwise comparison; change in expression of 2-fold with an adjusted?P?value of ≤ 0.05 (DESeq2 analysis; Benjamini-Hochberg test)), presented as row-wise?z-scores of transcripts per million (TPM counts). Each column represents an individual sample; key known TRM or non-TRM transcripts are indicated. (C) Flow-cytometry analysis of the expression of CD49A and KLRG1 versus. that of CD103 among live and singlet-gated CD14–CD19–CD20–CD45+CD3+CD8+ cells obtained from lung; right, frequency of CD103+CTLs or CD103–CTLs that express the indicated surface marker (* P ≤ 0.05, n = 6; Wilcoxon rank-sum test), bars represent the mean, t-line the s.e.m., and symbol represents data from individual samples. (D) GSEA of the murine composite TRM signature in the transcriptome of TRM versus. non-TRM: top, running enrichment score (RES) for the gene set, from most enriched genes at left to most under-represented at right; middle, positions of gene set members (blue vertical lines) in the ranked list of genes; bottom, value of the ranking metric. Values above the plot represent the normalized enrichment score (NES) and false discovery rate (FDR)-corrected significance value in CTLs isolated from lung and tumor samples. (E) GSEA of the lung TRM versus. non-TRM cells for non-preserved transcripts (in Fig. 1B,C; as per D; N/S = Not significant).Figure S2. TRM cells cluster into 4 major subtypes. (A) Principle component analysis of the single cell transcriptomes, each point represents a cell which are colored as per the cluster assignment in Fig. 3; numbers along perimeter indicate principal components (PC1–PC3). (B) tSNE visualization of single cell transcriptomes, shown per donor, obtained from 12 tumors and 6 matched normal lung samples. Each symbol represents a cell; color indicates Seurat clustering of cells, as per Fig. 3 B, identifying 9 clusters. (C) Breakdown of cells assigned to each cluster in each donor, separated by tissue type of origin (colored as per Fig. 3 B). (D) The distance in principle component space between a cell assigned to cluster 1 compared to the mean of cells assigned into the other clusters (colored as per Fig. 3 B). The difference was calculated with the raw (left) and z-score normalized (right) distances, bars represent the mean distance to each of the other clusters, t-line the s.e.m., and symbols represent individual cells in cluster 1 (**** P ≤ 0.0001; n = 135 cells; Wilcoxon rank-sum test). (E) Left, Seurat-normalized expression of indicated transcripts identified as differentially enriched in the non-TRM cluster 3 (colored as per Figs. 3 B and S3 A), overlaid across the tSNE plot, with expression levels represented by the color scale. Right, percentage of cells expressing TCF7 transcripts in each TRM cluster (as per Fig. 3 B), where positive expression was defined as greater than 1 Seurat-normalized count.Figure S3. Tumor TRM cells are enriched for transcripts associated with enhanced anti-tumor features. (A) Violin plot of expression of indicated transcripts; shape represents the distribution of expression among cells and color represents average expression, calculated from the Seurat-normalized counts. (B) SAVER-imputed spearman co-expression analysis of genes whose expression is enriched in the TIM-3+IL7R– TRM cluster (Fig. 4 A) in tumor TRM and non-TRM clusters, respectively; matrix is clustered according to complete linkage.Figure S4. Single-cell transcriptome analysis of CTLs from anti-PD-1 responders. (A) Schematic representation of clinical details and cells sorted for the patients selected for study (time point - TP). (B) Example of in-silico removal of CD4+ cells, highlighting the transcriptomic dropouts. The dashed line corresponds to the CD4+ cells removed. (C) Flow-cytometry analysis of the expression of TIM-3 versus. that of IL-7R in live, singlet CD14– CD19–CD20–CD4–CD45+CD3+CD8+CD103+ cells obtained from patients responding to anti-PD-1 therapy both pre- and post-therapy (n = 2 donors at 2 time points, as per A). (D) A clonotype network graph of cells from patient 53 and 54 (A), highlighting the time point from which the cells were isolated. Cells highlighted through a dashed line correspond to shared clonotypes across time points. (E) A clonotype network graph (as per D), highlighting the TRM cells and non-TRM cells, marked in purple and black respectively. Cells were assigned based on protein expression of CD103, alternatively if cell-specific protein expression was not available, cells with greater than 10 TPM counts expression of either ITGAE (CD103), RBPJ or ZNF683 (HOBIT) considered a TRM. (F) Percentage of cells expressing the indicated transcripts in each population, where TRM cells were identified as per (D,E).Table S1. Clinical and histopathological characteristics of patients used in this study. Details of RNA-seq libraries. Details of OMNI-ATAC-seq libraries.Table S2. List of differentially expressed genes in Lung TRM versus. non-TRM cells.Table S3. Gene lists utilized for GSEA analysis and preservation analysis of TRM signatures from published datasets.Table S4. List of differentially expressed genes in tumor TRM versus. tumor non-TRM cells. Co-expression analysis and weighted?gene co-expression network?analysis?(WGCNA) of ‘shared tissue residency’ transcripts. List of genes uniquely expressed in tumor TRM cells and Reactome pathway analysis, co-expression and WGCNA of genes uniquely enriched in tumor TRM cells. All cells were isolated from immunotherapy treatment na?ve patients.Table S5. List of differentially expressed genes in stimulated versus. unstimulated TRM and non-TRM cells from both lung and tumor, from cells isolated from immunotherapy treatment na?ve patients.Table S6. TCR-seq library and clonality information from cells isolated from immunotherapy treatment na?ve patients.Table S7. List of genes uniquely expressed in tumor TRM subsets from cells isolated from immunotherapy treatment na?ve patients; list of genes uniquely expressed in tumor CTL subsets from cells isolated from immunotherapy treatment na?ve patients; list of differentially expressed genes in PDCD1+ TRM (cluster 2-5) versus. PDCD1+ non-TRM cells (non-TRM clusters 1-4), from cells isolated from immunotherapy treatment na?ve patients.Table S8. TCR chain sequences from single-cell RNA-seq assays from cells isolated from immunotherapy treatment na?ve patients.Table S9. List of differentially expressed genes in TIM-3+ TRM cells versus. other TRM cells from cells isolated from immunotherapy treatment na?ve patients.Table S10. Single-cell co-expression and correlation analysis of genes enriched in ‘cluster 2’ TRM subset; correlation analysis of protein expression levels from flow cytometry data from cells isolated from immunotherapy treatment na?ve patients.Table S11. Quantification of CD8, CD103 and TIM-3 multiplexed immunohistochemistry counts from tumor samples of lung cancer patients with TILhighTRMhigh and TILlowTRMlow tumor status.Table S12. Assignment of single cell libraries into TRM and non-TRM cells; TCR chain sequences from single-cell RNA-seq assays; list of differentially expressed genes from cells pre- and post-anti-PD-1; single cell correlation analysis post-anti-PD-1 in CTLs. ................
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