Developing a Urine Test for Hepatitis B Related Liver Cancer
The promise of metabonomics in gastroenterology and hepatologyThe changing face of 21st century medicine. The concept of the patient as a totality of all their organs and tissues, held in a chemical equilibrium under the control of genetic and environmental factors, has only come to the fore in the last decade. The mindset of medical specialities being treated asin discrete silos with patients attending separate clinics for each condition still persists in mainstream medicine. The move towards personal or stratified medicine calls for a patient-centric approach where a global view of health demands knowledge of the integrated output of multiple systems and organs. The realisation that if we are to truly understand disease mechanisms, then we need to adopt a global investigative approach combining multiple bio-organizational layers, such as the genome, proteome, metabolome and, inflammasome has propelled the development of “Systems Biology” and “Systems Medicine”. Parallel development of ‘omics’ tools and advanced bioinformatics can be harnessed to help achieve this goal.Depersonalised or ‘one-size-fits-all’ treatments are the default approaches used for most patients and this can negatively impact negatively on the success of clinical trials, the cost-effectiveness of therapies and ultimately on patient safety. Variations in genetic profile, differential gene expression and gene-environment interactions all influence an individual’s response to drugs and indeed the risk of developing a particular disease. Genetic classifications of disease sub-types are well established, and modern genomic methods can provide rich information on large numbers of patients at relatively modest costs. However, there are orthogonal and highly complementary approaches to patient stratification, based on proteomic and metabolic information that can help place underlying genetic information in a biochemical or physiological context; these can also measure differential environmental, dietary and gut microbial contributions to patient diversity and response. Thus, even within selected genetic sub-classes of disease there is observed variation in therapeutic response that is dependent on environmental factors and conditional gene-environment interactions. In particular, metabolic and other clinical phenotyping approaches have been shown to be of great value in patient characterisation and can also be used to monitor direct responses to therapies through the patient journey{Holmes, 2008 #3;Nicholson, 2012 #4}. The 21st century heralds a move towards predictive, preventive, personalized and participatory (P4) approaches to medicine where each person serves as their own control over time and is interactive with their genetic and environmental background, with a responsibility for their own healthcare{Hood, 2012 #6}.The fundamental paradigm of clinical metabolic phenotyping is that any localised metabolic, physical or histological perturbation in the human body will result in global, systems level changes, which are detectable by profiling hundreds or thousands of system parameters in biological samples such as urine, serum (systemic snap shot and time-averaged signatures respectively) or tissue biopsies (intact or extracted). Localised and systemic metabolic phenotypes in tissue compartments and biofluids are the products of gene-environment interactions and so are both statistically and biologically connected to disease risk factors{Holmes, 2008 #3}, and individual patients responses to therapy. Alterations in metabolic profiles will be characteristic of the origin, behaviour and outcome of the original disease manifestation. We have developed novel and innovative molecular diagnostic phenotyping approaches for patient stratification across a range of technology platforms with application to many different pathological disease states and clinical conditions{Robinette, 2013 #9}. Modeling the responses to therapy via metabolic phenotyping can be viewed as a “dynamic stratification” process, which adds a new temporal and physiological dimension to understanding therapeutic response classes{Nicholson, 2012 #4}. Background to the use of metabonomics in the clinic. Metabolic profiling of biofluids using predominantly NMR spectroscopy and MS (often combined with a chromatographic separation) provide relatively high throughput generation of molecular fingerprints at low cost per sample and have been used to characterise a wide range of pre-pathological and pathological conditions including cardiovascular disease{Holmes, 2008 #10}, cancer, neurodegeneration, metabolic disorders{Maher, 2008 #11} and infection{Shariff, 2011 #12}. Profiling can be carried out in screening mode to obtain broad coverage of the metabolome without the need for a priori hypotheses, or in targeted mode to give deep coverage for selected metabolite classes, for example amino acids, eicosanoids (inflammatory conditions), bile aids (liver disease) or short chain fatty acids.NMR spectroscopy is rapid and non-destructive and has the advantage of high reproducibility. It is the only spectroscopic tool that can deliver atom-centred information, giving it premium position in molecular structural elucidation [REF]. Mass spectrometry, being inherently more sensitive than NMR, offers complementary molecular information. One of the first medical applications of both NMR and MS spectroscopic profiling in stratified medicine was in identification of infants with inborn errors of metabolism, and this technology is now routinely used in hospitals. Ultra performance liquid chromatography (UPLC), used as a molecular separation phase prior to MS detection, provides rapid analysis and delivers excellent chromatographic resolution{Plumb, 2004 #13}. Concatenation of NMR systems with liquid chromatographic devices, directly coupled to mass spectrometers, offer exquisite capability for enhanced structure elucidation{Shockcor, 1996 #14} and is equally applicable to endogenous and drug metabolite identification, although the majority of publications are focussed on drug metabolism {Duarte, 2009 #15}. Metabolic screening of biofluids has been at the forefront of profiling technologies in the clinical arena, but other spectroscopic tools have been developed for assessment of tissue biopsies. Amongst these magic angle spinning (MAS) NMR methods, operating on a 5-10 min per sample timescale, allow metabolic characterisation of intact tissue biopsies with one exemplar area being the differentiation of benign and malignant tissue from colon cancer biopsies with further correlation of the profile with tumour grade or stage (REF{Jimenez, 2013 #23). Related developments in molecular imaging of tissues to improve clinical decision-making and augment conventional histological and clinical pathology measurements are also being undertaken mainly in cancer diagnostics {Veselkov, 2014 #2} and are ready for further development in an experimental medicine environment. Current histopathological techniques offer little interpretable molecular information, without the use of specific non-routine stains or immunohistochemical procedures. Advances in DESI (invented by Takats et al.{Takats, 2004 #29}) and MALDI-IMS technology{Crecelius, 2005 #30} enable multi-modal tissue imaging utilising thousands of simultaneously collected molecular ion traces, which can be used to provide new molecular biomarker information relevant to disease aetiology and diagnostics as well as new imaging modalities. In parallel with spectroscopic developments, many computer-based pre-processing and multivariate modelling techniques have been developed to facilitate the analysis and interpretation of the complex high-density spectral data. Computational modelling tools have been developed to analyse, map and interpret spectroscopic data and these can be roughly divided into: i) pre-processing methods (e.g.such as spectral alignment and de-noising{Veselkov, 2009 #16}); ii) multivariate analysis methods (extensions to linear projection methods, Bayesian probabilistic models and so onetc){Trygg, 2007 #17}; iii) biomarker extraction algorithms, based on statistical spectroscopic tools{Cloarec, 2005 #19}, and; iv) pathway integration and mapping tools (e.g.such as MetabonetworksTM{Posma, 2014 #20}). Data filtering strategies and other pre-processing methods can be used to optimize models, and to increase the interpretability of the models focussing on important biochemical changes relating to single or combinatorial pathologies{Trygg, 2003 #21} by removing extraneous variation. Date fusion methods have also been developed to relate multiple data matrices, such as NMR and clinical chemistry or gene expressionPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5SYW50YWxhaW5lbjwvQXV0aG9yPjxZZWFyPjIwMDY8L1ll
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ADDIN EN.CITE.DATA {Rantalainen, 2006 #70} in order to achieve a more holistic picture of the dynamic and interactive biological processes occurring in an organism. Statistical correlation methods applied to spectroscopic data can be used to structurally identify candidate biomarkers of disease, to identify drugs and their metabolites (REF)PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5LZXVuPC9BdXRob3I+PFllYXI+MjAwODwvWWVhcj48UmVj
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ADDIN EN.CITE.DATA {Keun, 2008 #66} and to establish pathway connections between molelcules. Modifications of the basic statistical spectroscopy focus on identification of metabolites in relatively small subsets, otherwise hidden in large patient numbers or detection of idiosyncratic responses to drugs (subset optimisation by referencing matching, STORM) ADDIN EN.CITE <EndNote><Cite><Author>Posma</Author><Year>2012</Year><RecNum>64</RecNum><record><rec-number>64</rec-number><foreign-keys><key app="EN" db-id="zwaxsp2zstvse2ee9wcpxe9srzz00txwfxwf">64</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Posma, J. M.</author><author>Garcia-Perez, I.</author><author>De Iorio, M.</author><author>Lindon, J. C.</author><author>Elliott, P.</author><author>Holmes, E.</author><author>Ebbels, T. M.</author><author>Nicholson, J. K.</author></authors></contributors><auth-address>Section of Biomolecular Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College, London SW7 2AZ, United Kingdom.</auth-address><titles><title>Subset optimization by reference matching (STORM): an optimized statistical approach for recovery of metabolic biomarker structural information from 1H NMR spectra of biofluids</title><secondary-title>Analytical chemistry</secondary-title><alt-title>Anal Chem</alt-title></titles><periodical><full-title>Analytical chemistry</full-title><abbr-1>Anal Chem</abbr-1></periodical><alt-periodical><full-title>Analytical chemistry</full-title><abbr-1>Anal Chem</abbr-1></alt-periodical><pages>10694-701</pages><volume>84</volume><number>24</number><edition>2012/11/16</edition><dates><year>2012</year><pub-dates><date>Dec 18</date></pub-dates></dates><isbn>1520-6882 (Electronic)
0003-2700 (Linking)</isbn><accession-num>23151027</accession-num><work-type>Multicenter Study
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't</work-type><urls><related-urls><url>;{Posma, 2012 #64}. All of these methods and approaches aid the efficient recovery and validation of biomarker structure information, which is essential to provide the mechanistic underpinning of the diagnostic and prognostic information generated by spectroscopic phenotyping.These enabling technologies will be complemented by development of innovative bioinformatic and modelling methods to enhance relationships with other omics data. The proposed infrastructure framework bridges gaps between population phenotyping and real-time diagnostics and between systems biology and molecular technology framework that will facilitate harnessing the power of omic technology for mainstream use in clinical decision making, based on an incremental step in generation, organisation and extraction of information to establish a set of blueprints and technology units for carrying out efficient patient stratification with respect to disease diagnosis, intervention and prognosis.Importance of the gut microbiota in disease.Widespread realisation that the interaction between the gut microbiome and host metabolism has a critical impact on human health with long reaching effects. The microbiome is key to the status of the immune system with capacity to affect a diverse range of tissues and organs, including the liver and brain and is implicated in the aetiology or development of many diseases including inflammatory bowel disease, cardiovascular disease, asthma and even neurodevelopmental conditions, such as autism. Other examples of microbial-related differences in the phenotype include the fact that malignant gastrointestinal tumours carry differential 16S RNA bacterial profilesPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5NYXJjaGVzaTwvQXV0aG9yPjxZZWFyPjIwMTE8L1llYXI+
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ADDIN EN.CITE.DATA {Marchesi, 2011 #69}. Critical biosynthetic pathways that significantly extend host metabolic capacity are provided by the microbes. Metagenomic analysis can map the microbial community of faecal or intestinal samples. Parallel metabolic profiling of biofluids such as urine, plasma or faecal water can provide a window for investigating the functionality of the microbiome and assessing the consequences on human health and can demonstrate altered microbial activity reflected in microbial-host co-metabolite profiles such as phenolics and biogenic amines.and potential windows of impact for spectroscopic phenotyping.Increase in IBD, Unmet needs in Gastroenterology and Hepatology Death from liver disease is a major cause of mortality which is increasing in developed and developing countries alike with the combined burden of viral hepatitis, increased alcohol consumption amongst young people and the prevalence of obesity causing a steady rise in patients with cirrhosis. Over the past three decades, in the United Kingdom alone, deaths from chronic liver disease have increased eight-fold in men aged 35-44 and seven-fold in women (REF). Hepatocellular carcinoma (HCC) is the commonest primary liver cancer worldwide, killing up to one million people annually, most of whom have established cirrhosis as a precursor. Many of these deaths are preventable as HCC is curable if patients with pre-existing fibrotic and cirrhotic liver disease are regularly screened and the cancer is diagnosed early. However, small tumours are asymptomatic and standard diagnostic screening tests lack sensitivity and specificity. Similarly the incidence of inflammatory Bowel Disease (IBD), particularly Crohn’s Disease and uUlcerative colitis have increased xxxx significantly in the developedWestern world in the last decade. Much of this increase in prevalence has been attributed to lifestyle changes, such as increased consumption of fast foods with a corresponding decrease in dietary fibre.The following sections describe applications of metabolic profiling in gastroenterology and hepatology and explore potential avenues for its application with respect to addressing key unmet needs in these areas.Inflammatory Bowel DiseaseThere has been considerable interest in developing urine and serum biomarker diagnostic strategies in inflammatory bowel disease (IBD): both Crohn’s disease (CD) and ulcerative colitis (UC) have been investigated. Biomarkers of disease could be a useful non-invasive adjunct to current methods of diagnosis. One of the critical issues remains the differentiation of CD and UC from each other and from other inflammatory bowel conditions. Diagnosis is based upon clinical symptoms, endoscopic examination, radiographic data and histological evidence and is therefore an invasive and costly process (B. H. Stephen, W. Sandborn. Am. J. Gastroenterol. 2001, 96, 635–643.). Thus, specific biomarkers of the variants of IBD would be of immense clinical value. Since the manifestation of CD is heterogeneous and the severity of disease does not always mirror the endoscopic profile, new measures of disease presence and stage are needed. To this end, numerous genomic xxxx have been conducted. To date, there have only been a few metabolic studies conducted on serum or plasma. Dawiskiba et aland colleagues conducted an NMR-based metabolic profiling study in IBD patients (n=19 CD; n=24 UC; n=17 healthy controls) did not find a significant difference between the metabolic profiles of patients with CD and UC, although there was some evidence of predictivity of the metabolic profiles for IBD with serum providing a slightly stronger diagnostic (p=0.002) than urine (0.003) (REF). N-acetylated glycoproteins, often associated with inflammation, and phenylalanine were found to be upregulated in serum in patients with IBD, whereas the urine of patients with IBD was characterized by higher glycine and lower acetoacetate levels. Additional metabolites were found to be increased (leucine, isoleucine, 3-D- hydroxybutyrate, acetoacetate, glu]ycine and lactate) or decreased (creatine, histidine, choline) in the serum, when only the cases with active disease were compared with healthy controls. Similarly, urine profiles showed differentiation based on reduced excretion of hippurate, trigonelline citrate and taurine, when only active disease cases were compared with controls. In contrast to the results of Dawiskiba et al, Williams et aland colleagues found that it was possible to differentiate CD from UC patients in a similar sized cohort (n=24 CD; n=20 UC; n=23 healthy controls), based on NMR serum profiles and that the key discriminatory metabolites were N-acetylated glycoproteins, choline and lipoproteins (XXXXXXX). Fathi et aland colleagues performed random forest analysis of low molecular weight serum profiles to classify CD from healthy participants in 26 CD participants and 26 age- and gender-matched controls. The resulting model predicted CD with a sensitivity of 100% and a specificity of 88%, based on elevated isoleucine concentrations and lower valine concentrations in the CD participants. The altered levels of these amino acids was were attributed to the altered nutritional status often found in CD patients. The authors further assessed the profiles with respect to serum zinc levels, since low Cu2+-Zn2+ super oxide dismutase activity has been associated with IBD. A correlation between serum zinc levelrs and serum glutamine and lysine was established. One hypothesis arising from this study, given that glutamine is an essential nutrient for immune cells, was that CD patients may be susceptible to glutamine depletion (Fathi et al).Previous studies have demonstrated the importance of gut flora in modulating the disease process in inflammatory bowel disease (REF). The systemic effect of gut bacterial alterations in IBD is exemplified by a large urinary metabonomic investigation conducted by Williams and colleagues (REF). The group compared the urinary metabolic profiles from UC patients, CD patients, as well as healthy control subjects and concluded that specific urinary metabolites could differentiate between the cohorts. Statistically significant differences were found in hippurate, 4-cresol sulphate and formate: all metabolites of gut microbial activity. Most significant was hippurate, which was found to be lowered in CD patients, compared to UC patients and healthy controls. It has been hypothesised that lowered hippurate levels occurs in conjunction with reduced gut Clostridia spp. in IBD (REF). Future studies should attempt to clarify this relationship by correlating urinary hippurate levels with faecal studies of the gut moicrobiome, including the relative contribution of Clostridia spp.Colorectal CancerColorectal cancer (CRC) is the fourth most common cause of death due to malignancy and therefore remains an active area of investigation (REF). The use of NMR spectroscopy and MS to metabolically profile solid CRC tumours has expanded knowledge of tumour pathogenesis (REF).Many of the current metabolic phenotyping approaches to stratified medicine worldwide are subjective, empirical, labour intensive, unreliable and usually housed in disparate uncoordinated centres. A key goal will be to standardise upon reliable and robust protocols and applications that show statistically superior performance to existing pathology/clinical methods and to diffuse these nationally using the hub and spoke model, thereby providing added value to other UK metabolic phenotyping facilities. In terms of clinical adoption of the new technologies we propose, it should be emphasised that new discoveries in the medical field have to overcome barriers of conservative attitudes that place a burden on new methodologies to be proven at least better or more cost effective. For this reason, the early excitement and promise of the new methods in metabolic profiling now need significant investment to broaden their application base, and to create a community of users who will collaborate to create exemplars of the uses and robustness of the new methods in a range of clinical areas. In addition, by the nature of the novelty of these approaches, exemplars as yet undetermined will emerge from the user community to explore how the basic science can be applied to many areas of patient stratification (frameworks for stratification of therapeutic response, diagnostics, prognostics and improved mechanistic understanding of disease aetiologies) and it is difficult at this early stage to determine where the biggest impacts will lie. Hepatitis Hepatitis C virus (HCV) infection is a global health problem, with 130-170 million people currently infected worldwide. The infection may lead to chronic liver inflammation, fibrosis, cirrhosis and ultimately, HCC. The clinical spectrum and natural history of chronic liver disease is varied with some individuals having a rapidly progressive course and others having relatively indolent disease. There is wide geographical variability. For example, in northern Europe, chronic infection rates are estimated to be between 0.1 and 1%; in southern Europe, these are higher at 2.5%-3.5%. Egypt is worst affected with a prevalence of 22% or higher, owing to the high transmission of HCV in the parenteral antischistosomal therapy campaign in the 1970s and 19880s (REF). In about 80% of new cases, the infection becomes chronic. About 30% of individuals progress inexorably to develop cirrhosis over a variable period of up to 20 years after the initial infection, which is usually 5-10 years after initial medical presentation. Current treatment regimens are designed to prevent the progression in disease from mild hepatitis through significant fibrosis and subsequently, cirrhosis (REF).The late presentation of disease, as well as expensive serological tests and polymerase chain reaction (PCR) to identify viral RNA, present diagnostic conundra, especially in developing countries.To date, metabonomic studies of plasma in patients with hepatitis have largely concentrated on profiling of the lipid content. An exemplar of this is provided by Cassol and colleagues (REF). Distinct clusters of altered lipids correlated with markers of inflammation (interferon-α and interleukin-6), microbial translocation (lipopolysaccharide (LPS) and LPS-binding protein), and hepatic function (bilirubin). Lipid alterations showed substantial overlap with those reported in non-alcoholic fatty liver disease (NAFLD) (REF). Increased bile acids were associated with noninvasive markers of hepatic fibrosis and correlated with acylcarnitines, a marker of mitochondrial dysfunction (REF). Urinary metabolomics has been shown to be useful in studies from China, an example of which is from Zhang and colleagues, where a panel of 11 discriminant metabolites was found using UPLC-MS (REF). In the largest study of its kind, Ladep and colleagues found in an African population discriminant metabolites that distinguish patients with hepatitis B from those with cirrhosis and those with liver cancer using urinary NMR profiling (REF)Non-Alcoholic Fatty Liver Disease (NAFLD)Fatty liver, or hepatic steatosis, is a common finding in the general population and is a frequent cause for elevated serum aminotransferase levels (REF). This condition is the hepatic manifestation of the metabolic syndrome, where insulin resistance is the underlying factor with diabetes mellitus, obesity and hypertriglyceridaemia prominent clinical sequela. Steatosis may occur with other assaults on the liver, particularly in alcohol abuse and also in chronic HCV infection. NAFLD is defined as the presence of hepatic steatosis in the absence of excessive alcohol consumption. It encompasses a spectrum of disease, ranging from simple steatosis to steatohepatitis (NASH), with or without the development of fibrosis and cirrhosis. Estimates of hepatic steatosis prevalence vary, but incidence rates are increasing the world over (REF). Hepatic steatosis is also the commonest histological abnormality of the liver, affecting about 50% of patients who abuse alcohol. In addition to the well-known progression of patients with alcohol-related liver disease, those with NAFLD may also develop fibrosis and subsequently cirrhosis and liver cancer (REF). Metabonomic studies in NAFLD, show dysregulation of bile acid and phospholipid homeostasis (REF) with a concomitant upregulation of fatty acid β-oxidation. These studies may provide insight into hepatic metabolism in health and disease and aid targeted drug discovery.Liver Fibrosis and CirrhosisChronic liver injury over a period of months to years may lead to fibrosis. There are a variety of causes of liver injury, which include viral hepatitis, alcohol abuse, metabolic insults such as accumulation of iron, copper or fat, autoimmune disease and drugs. Liver injury leads to initiation and perpetuation of inflammatory processes, which lead to hepatic stellate cell (HSC) activation and resultant fibrosis. Traditionally, fibrosis has been considered reversible, while the end-stage, cirrhosis, is irreversible. However, with elimination of the cause of liver injury, a number of studies have demonstrated regression of fibrosis in animal models and in humans. ADDIN REFMGR.CITE <Refman><Cite><Author>Poynard</Author><Year>2002</Year><RecNum>58</RecNum><IDText>Impact of pegylated interferon alfa-2b and ribavirin on liver fibrosis in patients with chronic hepatitis C</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>58</Ref_ID><Title_Primary>Impact of pegylated interferon alfa-2b and ribavirin on liver fibrosis in patients with chronic hepatitis C</Title_Primary><Authors_Primary>Poynard,T.</Authors_Primary><Authors_Primary>McHutchison,J.</Authors_Primary><Authors_Primary>Manns,M.</Authors_Primary><Authors_Primary>Trepo,C.</Authors_Primary><Authors_Primary>Lindsay,K.</Authors_Primary><Authors_Primary>Goodman,Z.</Authors_Primary><Authors_Primary>Ling,M.H.</Authors_Primary><Authors_Primary>Albrecht,J.</Authors_Primary><Date_Primary>2002/5</Date_Primary><Keywords>administration & dosage</Keywords><Keywords>Adult</Keywords><Keywords>Antiviral Agents</Keywords><Keywords>drug therapy</Keywords><Keywords>Drug Therapy,Combination</Keywords><Keywords>Fibrosis</Keywords><Keywords>Hepatitis</Keywords><Keywords>Hepatitis C</Keywords><Keywords>Hepatitis C,Chronic</Keywords><Keywords>Humans</Keywords><Keywords>Inflammation</Keywords><Keywords>Interferon Alfa-2b</Keywords><Keywords>Liver</Keywords><Keywords>Liver Cirrhosis</Keywords><Keywords>methods</Keywords><Keywords>Necrosis</Keywords><Keywords>Polyethylene Glycols</Keywords><Keywords>Research Support,Non-U.'t</Keywords><Keywords>Ribavirin</Keywords><Reprint>Not in File</Reprint><Start_Page>1303</Start_Page><End_Page>1313</End_Page><Periodical>Gastroenterology</Periodical><Volume>122</Volume><Issue>5</Issue><Address>Service d'Hepato-Gastroenterologie, Groupe Hospitalier Pitie-Salpetriere, Universite Paris VI, Paris, France</Address><Web_URL>PM:11984517</Web_URL><ZZ_JournalStdAbbrev><f name="System">Gastroenterology</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite><Cite><Author>Hammel</Author><Year>2001</Year><RecNum>59</RecNum><IDText>Regression of liver fibrosis after biliary drainage in patients with chronic pancreatitis and stenosis of the common bile duct</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>59</Ref_ID><Title_Primary>Regression of liver fibrosis after biliary drainage in patients with chronic pancreatitis and stenosis of the common bile duct</Title_Primary><Authors_Primary>Hammel,P.</Authors_Primary><Authors_Primary>Couvelard,A.</Authors_Primary><Authors_Primary>O'Toole,D.</Authors_Primary><Authors_Primary>Ratouis,A.</Authors_Primary><Authors_Primary>Sauvanet,A.</Authors_Primary><Authors_Primary>Flejou,J.F.</Authors_Primary><Authors_Primary>Degott,C.</Authors_Primary><Authors_Primary>Belghiti,J.</Authors_Primary><Authors_Primary>Bernades,P.</Authors_Primary><Authors_Primary>Valla,D.</Authors_Primary><Authors_Primary>Ruszniewski,P.</Authors_Primary><Authors_Primary>Levy,P.</Authors_Primary><Date_Primary>2001/2/8</Date_Primary><Keywords>Adult</Keywords><Keywords>Alcoholism</Keywords><Keywords>analysis</Keywords><Keywords>Bile</Keywords><Keywords>Biopsy</Keywords><Keywords>Chronic Disease</Keywords><Keywords>Common Bile Duct</Keywords><Keywords>Common Bile Duct Diseases</Keywords><Keywords>complications</Keywords><Keywords>Constriction,Pathologic</Keywords><Keywords>Drainage</Keywords><Keywords>etiology</Keywords><Keywords>Fibrosis</Keywords><Keywords>Follow-Up Studies</Keywords><Keywords>Humans</Keywords><Keywords>Liver</Keywords><Keywords>Liver Cirrhosis</Keywords><Keywords>Liver Cirrhosis,Biliary</Keywords><Keywords>Male</Keywords><Keywords>methods</Keywords><Keywords>Middle Aged</Keywords><Keywords>Pancreatitis</Keywords><Keywords>pathology</Keywords><Keywords>surgery</Keywords><Reprint>Not in File</Reprint><Start_Page>418</Start_Page><End_Page>423</End_Page><Periodical>N.Engl.J.Med.</Periodical><Volume>344</Volume><Issue>6</Issue><Address>Federation Medico-Chirurgicale d'Hepato-Gastroenterologie, Service de Gastroenterologie, H pital Beaujon, Clichy, France</Address><Web_URL>PM:11172178</Web_URL><ZZ_JournalStdAbbrev><f name="System">N.Engl.J.Med.</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite><Cite><Author>Dufour</Author><Year>1997</Year><RecNum>60</RecNum><IDText>Reversibility of hepatic fibrosis in autoimmune hepatitis</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>60</Ref_ID><Title_Primary>Reversibility of hepatic fibrosis in autoimmune hepatitis</Title_Primary><Authors_Primary>Dufour,J.F.</Authors_Primary><Authors_Primary>DeLellis,R.</Authors_Primary><Authors_Primary>Kaplan,M.M.</Authors_Primary><Date_Primary>1997/12/1</Date_Primary><Keywords>Adolescent</Keywords><Keywords>Adult</Keywords><Keywords>Biopsy</Keywords><Keywords>Child</Keywords><Keywords>complications</Keywords><Keywords>Drug Therapy,Combination</Keywords><Keywords>Female</Keywords><Keywords>Fibrosis</Keywords><Keywords>Glucocorticoids</Keywords><Keywords>Hepatitis</Keywords><Keywords>Hepatitis,Autoimmune</Keywords><Keywords>Humans</Keywords><Keywords>Immunosuppressive Agents</Keywords><Keywords>Liver</Keywords><Keywords>Liver Cirrhosis</Keywords><Keywords>Liver Function Tests</Keywords><Keywords>Male</Keywords><Keywords>Middle Aged</Keywords><Keywords>pathology</Keywords><Keywords>physiopathology</Keywords><Keywords>Remission Induction</Keywords><Keywords>Research Support,Non-U.'t</Keywords><Keywords>Research Support,U.'t,P.H.S.</Keywords><Keywords>Retrospective Studies</Keywords><Keywords>Serum Albumin</Keywords><Keywords>therapeutic use</Keywords><Keywords>therapy</Keywords><Reprint>Not in File</Reprint><Start_Page>981</Start_Page><End_Page>985</End_Page><Periodical>Ann.Intern.Med.</Periodical><Volume>127</Volume><Issue>11</Issue><Address>Department of Pathology, New England Medical Center, Boston, MA 02111, USA</Address><Web_URL>PM:9412303</Web_URL><ZZ_JournalStdAbbrev><f name="System">Ann.Intern.Med.</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite><Cite><Author>Hammel</Author><Year>2001</Year><RecNum>59</RecNum><IDText>Regression of liver fibrosis after biliary drainage in patients with chronic pancreatitis and stenosis of the common bile duct</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>59</Ref_ID><Title_Primary>Regression of liver fibrosis after biliary drainage in patients with chronic pancreatitis and stenosis of the common bile duct</Title_Primary><Authors_Primary>Hammel,P.</Authors_Primary><Authors_Primary>Couvelard,A.</Authors_Primary><Authors_Primary>O'Toole,D.</Authors_Primary><Authors_Primary>Ratouis,A.</Authors_Primary><Authors_Primary>Sauvanet,A.</Authors_Primary><Authors_Primary>Flejou,J.F.</Authors_Primary><Authors_Primary>Degott,C.</Authors_Primary><Authors_Primary>Belghiti,J.</Authors_Primary><Authors_Primary>Bernades,P.</Authors_Primary><Authors_Primary>Valla,D.</Authors_Primary><Authors_Primary>Ruszniewski,P.</Authors_Primary><Authors_Primary>Levy,P.</Authors_Primary><Date_Primary>2001/2/8</Date_Primary><Keywords>Adult</Keywords><Keywords>Alcoholism</Keywords><Keywords>analysis</Keywords><Keywords>Bile</Keywords><Keywords>Biopsy</Keywords><Keywords>Chronic Disease</Keywords><Keywords>Common Bile Duct</Keywords><Keywords>Common Bile Duct Diseases</Keywords><Keywords>complications</Keywords><Keywords>Constriction,Pathologic</Keywords><Keywords>Drainage</Keywords><Keywords>etiology</Keywords><Keywords>Fibrosis</Keywords><Keywords>Follow-Up Studies</Keywords><Keywords>Humans</Keywords><Keywords>Liver</Keywords><Keywords>Liver Cirrhosis</Keywords><Keywords>Liver Cirrhosis,Biliary</Keywords><Keywords>Male</Keywords><Keywords>methods</Keywords><Keywords>Middle Aged</Keywords><Keywords>Pancreatitis</Keywords><Keywords>pathology</Keywords><Keywords>surgery</Keywords><Reprint>Not in File</Reprint><Start_Page>418</Start_Page><End_Page>423</End_Page><Periodical>N.Engl.J.Med.</Periodical><Volume>344</Volume><Issue>6</Issue><Address>Federation Medico-Chirurgicale d'Hepato-Gastroenterologie, Service de Gastroenterologie, H pital Beaujon, Clichy, France</Address><Web_URL>PM:11172178</Web_URL><ZZ_JournalStdAbbrev><f name="System">N.Engl.J.Med.</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite><Cite><Author>Dufour</Author><Year>1997</Year><RecNum>60</RecNum><IDText>Reversibility of hepatic fibrosis in autoimmune hepatitis</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>60</Ref_ID><Title_Primary>Reversibility of hepatic fibrosis in autoimmune hepatitis</Title_Primary><Authors_Primary>Dufour,J.F.</Authors_Primary><Authors_Primary>DeLellis,R.</Authors_Primary><Authors_Primary>Kaplan,M.M.</Authors_Primary><Date_Primary>1997/12/1</Date_Primary><Keywords>Adolescent</Keywords><Keywords>Adult</Keywords><Keywords>Biopsy</Keywords><Keywords>Child</Keywords><Keywords>complications</Keywords><Keywords>Drug Therapy,Combination</Keywords><Keywords>Female</Keywords><Keywords>Fibrosis</Keywords><Keywords>Glucocorticoids</Keywords><Keywords>Hepatitis</Keywords><Keywords>Hepatitis,Autoimmune</Keywords><Keywords>Humans</Keywords><Keywords>Immunosuppressive Agents</Keywords><Keywords>Liver</Keywords><Keywords>Liver Cirrhosis</Keywords><Keywords>Liver Function Tests</Keywords><Keywords>Male</Keywords><Keywords>Middle Aged</Keywords><Keywords>pathology</Keywords><Keywords>physiopathology</Keywords><Keywords>Remission Induction</Keywords><Keywords>Research Support,Non-U.'t</Keywords><Keywords>Research Support,U.'t,P.H.S.</Keywords><Keywords>Retrospective Studies</Keywords><Keywords>Serum Albumin</Keywords><Keywords>therapeutic use</Keywords><Keywords>therapy</Keywords><Reprint>Not in File</Reprint><Start_Page>981</Start_Page><End_Page>985</End_Page><Periodical>Ann.Intern.Med.</Periodical><Volume>127</Volume><Issue>11</Issue><Address>Department of Pathology, New England Medical Center, Boston, MA 02111, USA</Address><Web_URL>PM:9412303</Web_URL><ZZ_JournalStdAbbrev><f name="System">Ann.Intern.Med.</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite><Cite><Author>Kweon</Author><Year>2001</Year><RecNum>94</RecNum><IDText>Decreasing fibrogenesis: an immunohistochemical study of paired liver biopsies following lamivudine therapy for chronic hepatitis B</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>94</Ref_ID><Title_Primary>Decreasing fibrogenesis: an immunohistochemical study of paired liver biopsies following lamivudine therapy for chronic hepatitis B</Title_Primary><Authors_Primary>Kweon,Y.O.</Authors_Primary><Authors_Primary>Goodman,Z.D.</Authors_Primary><Authors_Primary>Dienstag,J.L.</Authors_Primary><Authors_Primary>Schiff,E.R.</Authors_Primary><Authors_Primary>Brown,N.A.</Authors_Primary><Authors_Primary>Burchardt,E.</Authors_Primary><Authors_Primary>Schoonhoven,R.</Authors_Primary><Authors_Primary>Brenner,D.A.</Authors_Primary><Authors_Primary>Fried,M.W.</Authors_Primary><Date_Primary>2001/12</Date_Primary><Keywords>Actins</Keywords><Keywords>Adult</Keywords><Keywords>Biopsy</Keywords><Keywords>Collagen</Keywords><Keywords>Collagen Type III</Keywords><Keywords>drug therapy</Keywords><Keywords>Female</Keywords><Keywords>Fibrosis</Keywords><Keywords>Hepatitis</Keywords><Keywords>Hepatitis B,Chronic</Keywords><Keywords>Humans</Keywords><Keywords>Immunohistochemistry</Keywords><Keywords>Lamivudine</Keywords><Keywords>Liver</Keywords><Keywords>Male</Keywords><Keywords>metabolism</Keywords><Keywords>methods</Keywords><Keywords>Middle Aged</Keywords><Keywords>Muscle,Smooth</Keywords><Keywords>pathology</Keywords><Keywords>Procollagen</Keywords><Keywords>Research Support,Non-U.'t</Keywords><Keywords>Research Support,U.'t,P.H.S.</Keywords><Keywords>Reverse Transcriptase Inhibitors</Keywords><Keywords>therapeutic use</Keywords><Keywords>therapy</Keywords><Keywords>Virus Replication</Keywords><Reprint>Not in File</Reprint><Start_Page>749</Start_Page><End_Page>755</End_Page><Periodical>J.Hepatol.</Periodical><Volume>35</Volume><Issue>6</Issue><Address>University of North Carolina, CB# 7080, Room 708, Burnett-Womack Building, Chapel Hill, NC 27599, USA</Address><Web_URL>PM:11738102</Web_URL><ZZ_JournalStdAbbrev><f name="System">J.Hepatol.</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite><Cite><Author>Iredale</Author><Year>2001</Year><RecNum>62</RecNum><IDText>Hepatic stellate cell behavior during resolution of liver injury</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>62</Ref_ID><Title_Primary>Hepatic stellate cell behavior during resolution of liver injury</Title_Primary><Authors_Primary>Iredale,J.P.</Authors_Primary><Date_Primary>2001/8</Date_Primary><Keywords>Apoptosis</Keywords><Keywords>Cell Division</Keywords><Keywords>Cell Proliferation</Keywords><Keywords>Collagen</Keywords><Keywords>Cytokines</Keywords><Keywords>cytology</Keywords><Keywords>Extracellular Matrix</Keywords><Keywords>Fibrosis</Keywords><Keywords>Gene Expression Regulation</Keywords><Keywords>Growth Substances</Keywords><Keywords>Humans</Keywords><Keywords>Inflammation</Keywords><Keywords>Liver</Keywords><Keywords>Liver Cirrhosis</Keywords><Keywords>metabolism</Keywords><Keywords>Necrosis</Keywords><Keywords>pathology</Keywords><Keywords>pharmacology</Keywords><Keywords>physiology</Keywords><Keywords>Receptors,Tumor Necrosis Factor</Keywords><Keywords>Remission,Spontaneous</Keywords><Keywords>therapy</Keywords><Reprint>Not in File</Reprint><Start_Page>427</Start_Page><End_Page>436</End_Page><Periodical>Semin.Liver Dis.</Periodical><Volume>21</Volume><Issue>3</Issue><Address>Liver Research Group, Infection, Inflammation and Repair Division, School of Medicine, University of Southampton, Tremona Road, Southampton, Hampshire SO16 6YD, United Kingdom. jpi@soton.ac.uk</Address><Web_URL>PM:11586470</Web_URL><ZZ_JournalStdAbbrev><f name="System">Semin.Liver Dis.</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite><Cite><Author>Iredale</Author><Year>1998</Year><RecNum>61</RecNum><IDText>Mechanisms of spontaneous resolution of rat liver fibrosis. Hepatic stellate cell apoptosis and reduced hepatic expression of metalloproteinase inhibitors</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>61</Ref_ID><Title_Primary>Mechanisms of spontaneous resolution of rat liver fibrosis. Hepatic stellate cell apoptosis and reduced hepatic expression of metalloproteinase inhibitors</Title_Primary><Authors_Primary>Iredale,J.P.</Authors_Primary><Authors_Primary>Benyon,R.C.</Authors_Primary><Authors_Primary>Pickering,J.</Authors_Primary><Authors_Primary>McCullen,M.</Authors_Primary><Authors_Primary>Northrop,M.</Authors_Primary><Authors_Primary>Pawley,S.</Authors_Primary><Authors_Primary>Hovell,C.</Authors_Primary><Authors_Primary>Arthur,M.J.</Authors_Primary><Date_Primary>1998/8/1</Date_Primary><Keywords>analysis</Keywords><Keywords>Animals</Keywords><Keywords>antagonists & inhibitors</Keywords><Keywords>Apoptosis</Keywords><Keywords>biosynthesis</Keywords><Keywords>Carbon Tetrachloride</Keywords><Keywords>Collagenases</Keywords><Keywords>complications</Keywords><Keywords>enzymology</Keywords><Keywords>Fibrosis</Keywords><Keywords>Gene Expression Regulation</Keywords><Keywords>genetics</Keywords><Keywords>Hepatitis,Toxic</Keywords><Keywords>Hydroxyproline</Keywords><Keywords>Interstitial Collagenase</Keywords><Keywords>Liver</Keywords><Keywords>Liver Cirrhosis,Experimental</Keywords><Keywords>Male</Keywords><Keywords>pathology</Keywords><Keywords>Procollagen</Keywords><Keywords>Proteins</Keywords><Keywords>Rats</Keywords><Keywords>Rats,Sprague-Dawley</Keywords><Keywords>Remission,Spontaneous</Keywords><Keywords>Research Support,Non-U.'t</Keywords><Keywords>RNA,Messenger</Keywords><Keywords>secretion</Keywords><Keywords>Tissue Inhibitor of Metalloproteinase-1</Keywords><Keywords>Tissue Inhibitor of Metalloproteinase-2</Keywords><Keywords>toxicity</Keywords><Reprint>Not in File</Reprint><Start_Page>538</Start_Page><End_Page>549</End_Page><Periodical>J.Clin.Invest</Periodical><Volume>102</Volume><Issue>3</Issue><Address>University Medicine, University of Southampton, Hampshire SO16 6YD, United Kingdom</Address><Web_URL>PM:9691091</Web_URL><ZZ_JournalStdAbbrev><f name="System">J.Clin.Invest</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite></Refman>(Dufour, DeLellis, & Kaplan 1997;Hammel et al. 2001;Iredale et al. 1998;Iredale 2001;Kweon et al. 2001;Poynard et al. 2002). Elucidation of the process of fibrogenesis enables markers of disease severity and potential targets for therapeutic intervention to be developed. The development of liver fibrosis is a complex process, which involves a number of mechanisms and pathways. HSCs have been shown to be integral to initiation and perpetuation of fibrosis through interaction with metabolites, growth factors, other cell types and ROS. Oxidative stress and consequent lipid peroxidation has been demonstrated to occur in a number of hepatic disease states and may represent a “common pathway” in fibrogenesis (REF).Given Inflammation, steatosis, fibrosis and fibrogenesis are complex multistep processes. It would be surprising if a single biomarker were able to describe liver disease completely. Accordingly, combinations of markers and modalities may describe disease more accurately and reproducibly than one marker alone. Studies of marker combinations should be performed to establish optimal combinations, in terms of numbers of tests, accuracy of combinations and the provision of complementary information from the test components. Candidate markers differ widely in the equipment and expertise required, so cost-benefit analyses compared to routine liver biopsy are warranted. Serum and urinary panel markers need to be investigated longitudinally in response to intervention in a number of disease states. As histological assessment of liver biopsy is itself a surrogate marker of liver disease, the challenge is to develop and validate protocols correlated to clinically meaningful outcome measures. Further research into non-invasive technologies for the assessment of chronic liver disease is required to optimise these techniques, to correlate with clinical outcomes and to incorporate them into validated management algorithms. Bile duct disordersLiver CancerHCC is the third commonest cause of cancer death worldwide. Most HCC occur on the background of chronic liver disease and while the majority arise in Africa and Asia, where chronic hepatitis B and C virus infection (HBV and HCV) are the most important risk factors, the additional problems of excess alcohol consumption amongst the young, and increasing obesity in the population means that even in the developed world, HCC is rising steadily on the background of an alarming rise in the numbers of patients who have cirrhosis (1). In many countries the prognosis for patients with HCC is poor, with 5-year survival rates of less than 5%. With early diagnosis, HCC is curable by liver transplantation, surgical resection, radiofrequency ablation or chemoembolisation (2). HCC survival rates are still low, even in the Europe and North America, because patients often present late, when tumours are too large for curative treatment. Current gold-standard screening tests for HCC diagnosis are 6-monthly ultrasound scanning and blood analysis for alpha fetoprotein (AFP) levels in patients with known liver disease. However, these tests are expensive, only have 75-80% sensitivity and specificity, and are not performed routinely in primary care in the UK. Furthermore, AFP analysis alone only picks up around 70% of HCC cases (3). A diagnostic urine test for HCC would be a paradigm shift in liver cancer screening. It would provide a practical and cost-effective test, easy to use in primary care, and help save thousands of lives. Clinically and economically such an approach would have a global impact, not only in the UK but also in severely resource limited settings, such as sub-Saharan Africa. Urinary metabolomics studies have shed light on potential discriminant biomarkers in an Egyptian population with hepatitis C and a West African population with hepatitis B, distinguishing those with mild liver disease from those with cirrhosis, from those with cancer (REFS). If borne out in larger studies, then this may hold promise for the ultimate development of a urinary test, such as a dipstick, that could be used at village level to screen for the complications of chronic liver disease, such as HCC, in order to reduce the burden of late presentation and improve outcomes. Hepatic EncephalopathyHepatic encephalopathy (HE) is characterized by neuropsychologic sequela that complicate the natural history of cirrhosis patients, as a result of essentially unfiltered blood reaching the brain owing to hepatocellular failure and/or portosystemic shunting. Diagnosis is currently achieved using psychometric tests (REFS). The main disadvantage is that they are time-consuming to perform in a busy liver clinic and there is debate about the applicability of some of these tests across cultural, linguistic and educational ranges. There is therefore an interest to determine objective biomarkers of HE in order to develop a rapid assessment of disease in terms of metabolic profile, rather than cognitive function. To date, most metabonomic studies have concentrated on changes to the urinary or plasma metabolic profile induced by hepatic encephalopathy treatment, which causes alteration to the gut microbiome (REFS).Phenotypically augmented patient stratificationThe use of spectroscopic techniques to extract deep phenotypic descriptors and to follow the progression of these features through time is unprecedented in the clinical environment and is a powerful approach to dynamic patient stratification based on enhanced diagnostics. This will be made possible via extension of approaches such as pharmacometabonomics{Clayton, 2009 #38}, novel high fidelity MS imaging techniques, and new statistical tools for spectral ADDIN EN.CITE <EndNote><Cite><Author>Robinette</Author><Year>2013</Year><RecNum>9</RecNum><record><rec-number>9</rec-number><foreign-keys><key app="EN" db-id="zwaxsp2zstvse2ee9wcpxe9srzz00txwfxwf">9</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Robinette, S. L.</author><author>Lindon, J. C.</author><author>Nicholson, J. K.</author></authors></contributors><auth-address>Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, UK.</auth-address><titles><title>Statistical spectroscopic tools for biomarker discovery and systems medicine</title><secondary-title>Analytical chemistry</secondary-title><alt-title>Anal Chem</alt-title></titles><periodical><full-title>Analytical chemistry</full-title><abbr-1>Anal Chem</abbr-1></periodical><alt-periodical><full-title>Analytical chemistry</full-title><abbr-1>Anal Chem</abbr-1></alt-periodical><pages>5297-303</pages><volume>85</volume><number>11</number><edition>2013/04/26</edition><keywords><keyword>Animals</keyword><keyword>Biological Markers/*analysis</keyword><keyword>*Biomedical Research</keyword><keyword>Humans</keyword><keyword>Metabolic Networks and Pathways</keyword><keyword>*Models, Statistical</keyword><keyword>Nuclear Magnetic Resonance, Biomolecular/*methods</keyword><keyword>Software</keyword><keyword>*Systems Biology</keyword></keywords><dates><year>2013</year><pub-dates><date>Jun 4</date></pub-dates></dates><isbn>1520-6882 (Electronic)
0003-2700 (Linking)</isbn><accession-num>23614579</accession-num><work-type>Research Support, Non-U.S. Gov't
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ADDIN EN.CITE.DATA {Veselkov, 2014 #2} analysis that facilitate enhanced biomarker recovery and identification of mechanistic pathways. The demand for improved monitoring and treatment of individual patients as they undergo a series of unique investigative and therapeutic procedures within the healthcare system is driven by a combination of scientific, social and economic factors. Biologically similar sub-populations of patients are likely to share similar post-interventional response trajectories that can be monitored in a dynamic environment. Combining the potential of advanced metabolic profiling technology with enhanced data processing capacity will enable the step change in ‘translation,’ to meet the growing demand for dynamic patient stratification to improve the delivery and sustainability of optimised healthcare. We envisage a model that permits sampling of patients throughout their entire patient journey from primary diagnosis through intervention and responseOne of the most effective approaches for understanding the pathogenesis of various chronic diseases is the longitudinal deep-phenotyping of patients at various stages of the disease or the clinical patient journey. Deep phenotyping encompasses the phenotypic analysis of all accessible biological fluid samples including blood, urine, saliva, mucosal smears etc. which may carry relevant information regarding the underlying disease. While the corresponding metabolic phenotyping includes the untargeted NMR spectroscopic and mass spectrometric methods already offeredPharmacogenomic and Pharmacometabonomic Approaches to “Dynamic” Stratification of Patient Populations: Pharmacogenomics, or the study of the impact of genomic variation on treatment response, has been used as framework on which to base patient stratification. For example, TrastuzumabTM is effective as a chemotherapeutic for only 30% of breast cancer patients, corresponding to those who overexpress the ERBB2 gene that encodes the human epidermal growth factor receptor (HER2) protein{Arteaga, 2012 #5}. The pharmacogenomic approach to selecting appropriate patients can be complemented by pharmacometabonomics, or prediction of an individual’s response to a drug based on a baseline profile, which can capture the influence of both genetic and environmental contributions and has been shown to be a useful tool in predicting adverse drug reactions{Kwon, 2011 #8}. We, and others have applied pharmacometabonomics in dynamic personalised medicine studies, for example in identifying colorectal cancer patients with high susceptibility to capacetabine toxicity based on NMR spectroscopic models of blood plasma composition taken prior to intervention{Backshall, 2011 #7}. WeHere we propose to apply deep metabolic phenotyping and integration of genomic and metagenomic data to extend this concept in order to select sub-populations of patients that would benefit from specific treatment regimens. The MCSMT presents a new dynamic national resource for stratified medicine that has potential to impact beneficially on current healthcare guidelines and practices by identifying more effective means of patient management for both acute and chronic conditions as well as rare diseases. An important role of the MCSMT will be to build upon current research and training programmes in Systems Medicine being undertaken at Imperial (IC), to increase the UK cadre of clinicians and scientists who can utilize multimodal data streams to improve clinical diagnostics and prognostics. Population phenotypingFor population studies of chronic conditions such as cardiovascular disease, metabolic syndrome, and neurodegenerative diseases we developed the metabolome-wide association study (MWAS) approach to identifying associations between metabolic patterns and risk / prevalence of disease based on spectral data{Holmes, 2008 #10}.Surgical MetabonomicsMore recently the applicants achieved a major breakthrough regarding the in-vivo metabolic profiling of living cells including human tissues, cell cultures, bacteria or protozoa. The underlying Rapid evaporative Ionization Mass Spectrometry (REIMS) technique is based on the thermal disintegration of cells followed by mass spectrometric analysis of ionized metabolic constituents. Since thermal tissue disintegration is widely used in interventional medicine as diathermy or ablation, the hyphenation of these medical technologies with on-line mass spectrometric detection results in a family of capable of the in-situ, in-vivo, real-time metabolic profiling of vital tissues or associated microorganisms. The REIMS technique has been demonstrated to provide a solution for the long-standing problem of intrasurgical tissue identification (cf. iKnife), for point of care characterisation of needle biopsy samples and for identification of mucosa-associated bacterial strains,{Balog, 2013 #34;Strittmatter, 2013 #37} and has the potential to transform many in situ analytical procedures such as endoscopy. Oncological surgery has remained largely unchanged for decades and clearance of tumour tissue is typically based on arbitrary and non-objective measurements of clearance, which are often inadequate with potentially serious implications for the patient. For example, 30% of breast cancers require re-excision for positive margins. Both NMR and MS technologies have been used to improve surgical diagnosis. Magic angle spinning NMR technology has been installed in the surgical unit at St Mary’s hospital (first in the world in 2009) and is able to robustly determine the difference between benign and malignant tissue in breast, and published in colon cancer with a high degree of sensitivity and specificity ADDIN EN.CITE <EndNote><Cite><Author>Mirnezami</Author><Year>2013</Year><RecNum>67</RecNum><record><rec-number>67</rec-number><foreign-keys><key app="EN" db-id="zwaxsp2zstvse2ee9wcpxe9srzz00txwfxwf">67</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Mirnezami, R.</author><author>Jimenez, B.</author><author>Li, J. V.</author><author>Kinross, J. M.</author><author>Veselkov, K.</author><author>Goldin, R. D.</author><author>Holmes, E.</author><author>Nicholson, J. K.</author><author>Darzi, A.</author></authors></contributors><auth-address>*Section of Biosurgery and Surgical Technology, Department of Surgery and Cancer, Faculty of Medicine, St Mary's Hospital, Imperial College London daggerSection of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London double daggerCentre for Pathology, Department of Medicine, Faculty of Medicine, St Mary's Hospital, Imperial College London, London, United Kingdom.</auth-address><titles><title>Rapid Diagnosis and Staging of Colorectal Cancer via High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HR-MAS NMR) Spectroscopy of Intact Tissue Biopsies</title><secondary-title>Annals of surgery</secondary-title><alt-title>Ann Surg</alt-title></titles><periodical><full-title>Annals of surgery</full-title><abbr-1>Ann Surg</abbr-1></periodical><alt-periodical><full-title>Annals of surgery</full-title><abbr-1>Ann Surg</abbr-1></alt-periodical><edition>2013/07/19</edition><dates><year>2013</year><pub-dates><date>Jul 15</date></pub-dates></dates><isbn>1528-1140 (Electronic)
0003-4932 (Linking)</isbn><accession-num>23860197</accession-num><urls><related-urls><url>;{Mirnezami, 2013 #67}. Mass spectrometric imaging (MSI), of tissues in-situ creates a new layer of detailed molecular information that can be overlaid onto traditional histopathological images and opens up exciting new avenues in molecular pathology. The MSI segment utilizes Desorption Electrospray Ionization (DESI) method for imaging, which is particularly well-suited for spatially resolved metabolic profiling of tissues. DESI was originally invented by Takats ADDIN EN.CITE <EndNote><Cite><Author>Takats</Author><Year>2004</Year><RecNum>29</RecNum><record><rec-number>29</rec-number><foreign-keys><key app="EN" db-id="zwaxsp2zstvse2ee9wcpxe9srzz00txwfxwf">29</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Takats, Z.</author><author>Wiseman, J. M.</author><author>Gologan, B.</author><author>Cooks, R. G.</author></authors></contributors><auth-address>Department of Chemistry, Purdue University, West Lafayette, IN 47907, USA.</auth-address><titles><title>Mass spectrometry sampling under ambient conditions with desorption electrospray ionization</title><secondary-title>Science</secondary-title><alt-title>Science</alt-title></titles><periodical><full-title>Science</full-title><abbr-1>Science</abbr-1></periodical><alt-periodical><full-title>Science</full-title><abbr-1>Science</abbr-1></alt-periodical><pages>471-3</pages><volume>306</volume><number>5695</number><edition>2004/10/16</edition><dates><year>2004</year><pub-dates><date>Oct 15</date></pub-dates></dates><isbn>1095-9203 (Electronic)
0036-8075 (Linking)</isbn><accession-num>15486296</accession-num><urls><related-urls><url>;{Takats, 2004 #29}, who has developed the approach further at IC improving spatial resolution, sensitivity and information recovery from frozen section material. The method currently allows the 10-500 ?m variable resolution imaging of frozen histological sections. The MSI metabolic profile can be interrogated by real-time multivariate statistical analysis of the data to achieve histopathological classificationPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5WZXNlbGtvdjwvQXV0aG9yPjxZZWFyPjIwMTQ8L1llYXI+
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ADDIN EN.CITE.DATA {Veselkov, 2014 #2}. However, the specificity of the spectral profiles exceeds the level of standard, morphology-based classification enhancing diagnostic capability and providing more refined guidelines for tumour resection etc. Information earlier accessible only by immunohistochemistry or DNA sequencing can also be obtained from metabolic imaging datasets as is shown in the example in in Figure 4 for determination of KRAS mutation status or HER status of colorectal adenocarcinoma and breast cancer, respectively. In principle, it should be possible to replace the complete histological processing of tumour samples including morphological staining, series of immunohistochemical stains and genetic assays with a single imaging MS assay. Furthermore, imaging mass spectrometry is capable of detecting changes not visible in histological segmentation (e.g. metabolic changes in the tumour environment), which give a new dimensionality to tissue analysis. Nevertheless, the limitations of metabolic tissue imaging are yet to be determined; one of the main goals of the proposal is to harmonize DESI imaging with other approaches of molecular pathology and develop an optimized workflow.Intelligent surgical device (or iKnife) technology that combines standard surgical dissection techniques with mass spectrometric analysis of the by-products (smoke, liquefied tissue) of the dissection is planned to be coupled with biopsy analysis and endoscopy. In the former case the main driving force is the instantaneous analysis of biopsy samples, which enables quick decision making based on a more detailed portfolio of information than the surgeon’s clinical scoring criteria and intuition. This improves potential for patient stratification and subsequent treatment. Spectral interconversion algorithms are being developed, bridging MSI and iKnife approaches in order to fully utilize the capabilities of ISD technologies. Briefly, the algorithm enables the use of high-resolution MSI data for the real-time identification of ISD data in the pathology laboratory or surgical environment, which further emphasizes the importance of a database featuring the metabolic fingerprints of human healthy and diseased tissue types. The combination of MSI and ISD technologies can lead to a general paradigm change in histopathology, when the tissue types are defined by their chemical topology based on concentration distributions of hundreds of well-defined chemical species) describing multidimensional data vectors. Although MS imaging has been used to demonstrate localisation of proteins in tumours{Le Faouder, 2014 #31} and for experimental studies in colon cancer{Pevsner, 2009 #32}, we have now moved towards translating this approach to direct clinical use using surgical gastrointestinal (GI) tissue analysis for exemplar studies mapping KRAS mutation status{Gerbig, 2012 #33}.Towards the Future metabolic phenotyping and molecular pathology to enrich stratified medicine research, through the development and integration of novel analytical technology hubs. This will involve the development of a suite of new high throughput technologies for population phenotyping, clinical image based diagnostics and patient journey modelling, each with potential to impact significantly on healthcare, building on and extending existing national facilities.Patient cohort stratification studies linking genes to deep metabolic phenotypes.Patient journey phenotyping to monitor and classify patient responses to therapy through time.Chemical image enhanced molecular pathology of tissues.Novel biomarker structure elucidation technologies and clinical biomarker database construction.Pathways to translation of integrative multi-omic stratification technologies, tools and models.The opportunity to create a paradigm shift in clinical capability leading to changes in practice afforded by the MCSMT is made possible by a combination of factors: i) the proven synergy of clinicians and physical scientists embedded in the Faculty of Medicine and the availability of large, well-defined ethically approved patient study groups as piloted in multiple BRC projects; ii) novel and innovative analytical technology and statistical information recovery tools developed in-house by the applicants; iii) the ability to capitalise on the analytical framework and data processing pipelines already established in the MRC-NIHR NPC; iv) the enhanced computational power afforded by the new MRC-funded MED BIO programme; v) the longstanding and productive strategic relationship between the applicants and the principal phenotyping technology providers (Bruker BioSpin and the Waters Corporation). Many of the current metabolic phenotyping approaches to stratified medicine worldwide are subjective, empirical, labour-intensive, unreliable and usually housed in disparate uncoordinated centres. A key goal will be to standardise upon reliable and robust protocols and applications that show statistically superior performance to existing pathology/clinical methods and to diffuse these internationally such that data can be efficiently and freely shared thereby increasing the statistical power of biomarker discovery studies. In terms of clinical adoption of the new technologies we propose in this review, it should be emphasised that new discoveries in the medical field have to overcome barriers of conservative attitudes that place a burden on new methodologies to be proven at least better or more cost effective. For this reason, the early excitement and promise of the new methods in metabolic profiling now need significant investment to broaden their application base, and to create a community of users who will collaborate to create exemplars of the uses and robustness of the new methods in a range of clinical areas. In addition, by the nature of the novelty of these approaches, exemplars as yet undetermined will emerge from the user community to explore how the basic science can be applied to many areas of patient stratification (frameworks for stratification of therapeutic response, diagnostics, prognostics and improved mechanistic understanding of disease aetiologies) and it is difficult at this early stage to determine where the biggest impacts will lie.References(1) Shariff et al. Hepatocellular carcinoma: current trends in worldwide epidemiology, risk factors, diagnosis and therapeutics. Expert Rev Gastroenterol Hepatol 2009; 3(4), 353-367. (2) Patel M, et al. Hepatocellular carcinoma: diagnostics and screening. J Eval Clin Pract. 2010;10: 1365-2753(3) Farinati F et al. Diagnostic and prognostic role of alpha-fetoprotein in hepatocellular carcinoma: both or neither? Am J Gastroenterol 2006; 101:524-532.Fathi F, Majari-Kasmaee L, Mani-Varnosfaderani A, Kyani A, Rostami-Nejad M,Sohrabzadeh K, Naderi N, Zali MR, Rezaei-Tavirani M, Tafazzoli M, Arefi-OskouieA. 1H NMR based metabolic profiling in Crohn's disease by random forestmethodology. Magn Reson Chem. 2014 Jul;52(7):370-6. doi: 10.1002/mrc.4074. Epub2014 Apr 22. PubMed PMID: 24757065.Dawiskiba T, Deja S, Mulak A, Z?bek A, Jawień E, Pawe?ka D, Banasik M,Mastalerz-Migas A, Balcerzak W, Kaliszewski K, Skóra J, Bar? P, Korta K,Pormańczuk K, Szyber P, Litarski A, M?ynarz P. Serum and urine metabolomicfingerprinting in diagnostics of inflammatory bowel diseases. World JGastroenterol. 2014 Jan 7;20(1):163-74. doi: 10.3748/wjg.v20.i1.163. PubMed PMID:24415869; PubMed Central PMCID: PMC3886005.Williams HR, Willsmore JD, Cox IJ, Walker DG, Cobbold JF, Taylor-Robinson SD, Orchard TR. Serum metabolic profiling in inflammatory bowel disease. Dig Dis Sci.2012 Aug;57(8):2157-65. doi: 10.1007/s10620-012-2127-2. Epub 2012 Apr 10. PubMed PMID: 22488632.72009014859000Figure 1: Relationships between Research Programmes (A-D) and underpinning technology and informatics systems (E-G): Bridging the gap between stratified medicine and public healthcare research paradigms in an integrative technology and computational framework. Requested infrastructure key: FT-MS – Fourier Transform Ion Cyclotron Resonance Mass Spectrometer, Q-IMS-ToF MS – quadrupole ion mobility time-of-flight mass spectrometer, NMR – nuclear magnetic resonance spectrometer, UPLC- ultra performance liquid chromatograph, IHC – immunohistochemistry, FISH – fluorescent in-situ hybridization, SFC-MS – supercritical fluid chromatograph-mass spectrometer.{Jimenez, 2013 #23}; Other examples of metabolic phenotyping enhancements of contributions to understanding of disease mechanisms include the identification of the toxic mechanisms responsible for melamine toxicity in baby milk{Zheng, 2013 #24}, ifosfamide toxicity{Foxall, 1997 #25}, Hirmi Valley liver disease{Robinson, 2014 #27} and in the characterisation of metabolic associations with genetic mutations (missense mutation in EHHADH) underlying mitochondrial dysfunction in a subset of renal Fanconi patients{Klootwijk, 2014 #28}. That said, a number of applications, such as tissue pathology using hyperspectral mass spectrometric imaging{Fonville, 2013 #1;Veselkov, 2014 #2} have been identified that could offer significant benefit and be immediately translatable to UK clinical environmentsWe have used NMR, which is an inherently extremely reproducible technology, as a sentinel technology to screen every sample prior to MS analysis to identify and remove contaminated outlier samples (e.g. blood contaminated plasma) that can comprise up to 2% in epidemiology sets and disrupt UPLC-MS analytical procedures. Coupled with dedicated instrumentation for specific analytical jobs and highly trained technicians results in extreme reliability in the field that cannot easily be replicated with multipurpose instruments with multi-user bases. ................
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