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Expression data of HCV-associated advance disease state

ABSTRACT: Introduction: Mechanisms that contribute to the pathogenesis of liver damage caused by hepatitis C virus (HCV) are not fully understood. Our previous work on liver biopsies from chronic HCV patients has shown modulation of the expression of certain cell cycle proteins indicating HCV-induced modifications of cell cycle events. We therefore hypothesize that HCV infection disrupts normal regulation of cell cycle that contributes to disease progression. Objective: To identify molecular disruptions during the course of HCV-associated disease progression, using liver biopsy specimens of chronic hepatitis C patients. Methods: Liver biopsy samples classified on histological basis as early (fibrosis stage 0-1) or advanced (fibrosis stage 3-4) disease stage were studied using oligonucleotide array ( HG U133 Plus 2.0, Affymetrix GeneChip™ System). For comparison, liver specimens from patients with non-viral hepatitis were also analyzed by microarray. Expression data was analyzed using Genespring (GX 7.2) and Ingenuity Pathway analysis (3.0). The differential expression of selected cell cycle genes (cyclin D2, KPNA2, HERC5 and Bcl-2) identified after microarray analysis was confirmed by quantitative real-time RT-PCR. Results: Microarray analysis revealed two-fold or greater transcriptional change in 792 genes of the total 38,500 known human genes in HCV-advance disease stage (HCV-A) as compared to HCV-early disease stage (HCV-E). Most of the genes have a defined role in immune response, extracellular matrix and cell cycle and apoptosis. Keywords: HCV-advance disease state

ORGANISM(S): Homo sapiens

PROVIDER: GSE7741 | GEO | 2007/11/01

SECONDARY ACCESSION(S): PRJNA99851

REPOSITORIES: GEO

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Project description:End stage liver disease due to Hepatitis C Virus (HCV) infection is a major health concern worldwide. Liver fibrosis following chronic HCV infection plays a pivotal role in loss of liver function and end stage liver disease. However the dynamics and molecular events that lead to fibrosis in HCV infection are poorly defined. Therefore, we determined the influence of HCV infection in altering the miRNA expression levels which can modulate immune responses to HCV leading to fibrosis. Analysis of the miRNA expression profiles of HCV infected liver biopsies revealed that 45 miRNAs were differentially expressed in the HCV infected liver when compared to normal livers. In silico target prediction of these differentially expressed miRNAs indicated that their targets include chemokine/cytokine signaling, cell cycle genes and extracellular matrix protein gene expression. Gene expression profiling using whole genome microarray demonstrated that 1320 genes were differentially expressed in chronic HCV liver when compared to normal. These genes could be functionally grouped into those involved in cell cycle regulation, cytokines and chemokines expression, cell adhesion, intracellular signaling and enzymes. Further pathway analysis using GeneGo software identified cell adhesion, cytoskeleton remodeling, cytokine signaling and metabolic pathways as the major pathways activated in chronic HCV. Combinatorial target prediction analysis of miRNA expression along with gene expression analysis indicated that differentially expressed microRNAs in HCV significantly impact transforming growth factor beta (TGF-β) signaling pathway, cell adhesion (integrin expression), chemokine signaling, Notch signaling and cell-cycle( Cyclin D,K) regulation. Overall these results demonstrate that chronic HCV infection induces specific miRNA signatures that will modulate genes involved in the cytoskeletal remodeling and cytokine signaling that can promote the development of fibrosis following HCV infection.

Project description:End stage liver disease due to Hepatitis C Virus (HCV) infection is a major health concern worldwide. Liver fibrosis following chronic HCV infection plays a pivotal role in loss of liver function and end stage liver disease. However the dynamics and molecular events that lead to fibrosis in HCV infection are poorly defined. Therefore, we determined the influence of HCV infection in altering the miRNA expression levels which can modulate immune responses to HCV leading to fibrosis. Analysis of the miRNA expression profiles of HCV infected liver biopsies revealed that 45 miRNAs were differentially expressed in the HCV infected liver when compared to normal livers. In silico target prediction of these differentially expressed miRNAs indicated that their targets include chemokine/cytokine signaling, cell cycle genes and extracellular matrix protein gene expression. Gene expression profiling using whole genome microarray demonstrated that 1320 genes were differentially expressed in chronic HCV liver when compared to normal. These genes could be functionally grouped into those involved in cell cycle regulation, cytokines and chemokines expression, cell adhesion, intracellular signaling and enzymes. Further pathway analysis using GeneGo software identified cell adhesion, cytoskeleton remodeling, cytokine signaling and metabolic pathways as the major pathways activated in chronic HCV. Combinatorial target prediction analysis of miRNA expression along with gene expression analysis indicated that differentially expressed microRNAs in HCV significantly impact transforming growth factor beta (TGF-?) signaling pathway, cell adhesion (integrin expression), chemokine signaling, Notch signaling and cell-cycle( Cyclin D,K) regulation. Overall these results demonstrate that chronic HCV infection induces specific miRNA signatures that will modulate genes involved in the cytoskeletal remodeling and cytokine signaling that can promote the development of fibrosis following HCV infection. Liver biopsies from chronic HCV patients and control liver biopsies from normal subjects (donor liver prior to transplantation) were used to analyze the miRNA and gene expression profile. Patients with HBV and/or HIV were excluded from the study. This Series represents the mRNA gene expression profiling data only.

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Expression data of HCV-associated advance disease state

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