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      Extracellular Matrix Dynamics in Hepatocarcinogenesis: a Comparative Proteomics Study of PDGFC Transgenic and Pten Null Mouse Models

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          We are reporting qualitative and quantitative changes of the extracellular matrix (ECM) and associated receptor proteomes, occurring during the transition from liver fibrosis and steatohepatitis to hepatocellular carcinoma (HCC). We compared two mouse models relevant to human HCC: PDGFC transgenic (Tg) and Pten null mice, models of disease progression from fibrosis and steatohepatitis to HCC. Using mass spectrometry, we identified in the liver of both models proteins for 26 collagen-encoding genes, providing the first evidence of expression at the protein level for 16 collagens. We also identified post-transcriptional protein variants for six collagens and lysine hydroxylation modifications for 14 collagens. Tumor-associated collagen proteomes were similar in both models with increased expression of collagens type IV, VI, VII, X, XIV, XV, XVI, and XVIII. Splice variants for Col4a2, Col6a2, Col6a3 were co-upregulated while only the short form of Col18a1 increased in the tumors. We also identified tumor specific increases of nidogen 1, decorin, perlecan, and of six laminin subunits. The changes in these non-collagenous ECM proteins were similar in both models with the exception of laminin β3, detected specifically in the Pten null tumors. Pdgfa and Pdgfc mRNA expression was increased in the Pten null liver, a possible mechanism for the similarity in ECM composition observed in the tumors of both models. In contrast and besides the strong up-regulation of integrin α5 protein observed in the liver tumors of both models, the expression of the six other integrins identified was specific to each model, with integrins α2b, α3, α6, and β1 up-regulated in Pten null tumors and integrins α8 and β5 up-regulated in the PDGFC Tg tumors. In conclusion, HCC–associated ECM proteins and ECM–integrin networks, common or specific to HCC subtypes, were identified, providing a unique foundation to using ECM composition for HCC classification, diagnosis, prevention, or treatment.

          Author Summary

          The microenvironment can have a profound influence on cellular behavior and survival and on growth of developing tumor cells. We present the first comprehensive analysis of the extracellular matrix (ECM) and associated receptor proteomes, applied here to the study of hepatocellular carcinoma (HCC). This study demonstrates the utility of mass spectrometry-based approaches to characterize, at the protein level, gene families with extensive sequence homology, post-transcriptional regulations, and post-translational regulations. This is also the first study to analyze and compare liver proteome changes occurring during the transition from fibrosis and steatohepatitis, common preneoplastic conditions in humans, to HCC, using two mouse models. This approach identifies ECM and integrin components, which could play an important role in the early steps of hepatocarcinogenesis, and provides a path to identifying ECM–tumor cell networks that may contribute to the heterogeneous features of HCC.

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          Most cited references 31

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          Liver fibrosis.

          Liver fibrosis is the excessive accumulation of extracellular matrix proteins including collagen that occurs in most types of chronic liver diseases. Advanced liver fibrosis results in cirrhosis, liver failure, and portal hypertension and often requires liver transplantation. Our knowledge of the cellular and molecular mechanisms of liver fibrosis has greatly advanced. Activated hepatic stellate cells, portal fibroblasts, and myofibroblasts of bone marrow origin have been identified as major collagen-producing cells in the injured liver. These cells are activated by fibrogenic cytokines such as TGF-beta1, angiotensin II, and leptin. Reversibility of advanced liver fibrosis in patients has been recently documented, which has stimulated researchers to develop antifibrotic drugs. Emerging antifibrotic therapies are aimed at inhibiting the accumulation of fibrogenic cells and/or preventing the deposition of extracellular matrix proteins. Although many therapeutic interventions are effective in experimental models of liver fibrosis, their efficacy and safety in humans is unknown. This review summarizes recent progress in the study of the pathogenesis and diagnosis of liver fibrosis and discusses current antifibrotic strategies.
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            Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.

            We present a statistical model to estimate the accuracy of peptide assignments to tandem mass (MS/MS) spectra made by database search applications such as SEQUEST. Employing the expectation maximization algorithm, the analysis learns to distinguish correct from incorrect database search results, computing probabilities that peptide assignments to spectra are correct based upon database search scores and the number of tryptic termini of peptides. Using SEQUEST search results for spectra generated from a sample of known protein components, we demonstrate that the computed probabilities are accurate and have high power to discriminate between correctly and incorrectly assigned peptides. This analysis makes it possible to filter large volumes of MS/MS database search results with predictable false identification error rates and can serve as a common standard by which the results of different research groups are compared.
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              TANDEM: matching proteins with tandem mass spectra.

              Tandem mass spectra obtained from fragmenting peptide ions contain some peptide sequence specific information, but often there is not enough information to sequence the original peptide completely. Several proprietary software applications have been developed to attempt to match the spectra with a list of protein sequences that may contain the sequence of the peptide. The application TANDEM was written to provide the proteomics research community with a set of components that can be used to test new methods and algorithms for performing this type of sequence-to-data matching. The source code and binaries for this software are available at http://www.proteome.ca/opensource.html, for Windows, Linux and Macintosh OSX. The source code is made available under the Artistic License, from the authors.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                June 2011
                June 2011
                23 June 2011
                : 7
                : 6
                Affiliations
                [1 ]Molecular Diagnostics Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
                [2 ]Department of Pathology, University of Washington, Seattle, Washington, United States of America
                The University of North Carolina at Chapel Hill, United States of America
                Author notes

                ¤: Current address: Southern California Research Center for ALPD and Cirrhosis, Department of Pathology, University of Southern California, Los Angeles, California, United States of America

                Conceived and designed the experiments: KKYL SS NF JSC LB. Performed the experiments: KKYL SS NL GCB DJM. Analyzed the data: KKYL SS NL LB. Contributed reagents/materials/analysis tools: NF JSC. Wrote the paper: KKYL NF JSC LB.

                Article
                PGENETICS-D-11-00506
                10.1371/journal.pgen.1002147
                3121762
                21731504
                Lai et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Page count
                Pages: 16
                Categories
                Research Article
                Biology
                Biochemistry
                Proteins
                Extracellular Matrix Proteins
                Proteome
                Model Organisms
                Animal Models
                Mouse
                Proteomics
                Medicine
                Gastroenterology and Hepatology
                Liver Diseases
                Oncology
                Cancer Detection and Diagnosis
                Early Detection
                Cancers and Neoplasms
                Gastrointestinal Tumors
                Hepatocellular Carcinoma
                Basic Cancer Research

                Genetics

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