Project description:We aimed to identify epigenetic regulators of transcription that may be involved in the development and the progression of HCV-associated HCC. Using HELP-tagging, we performed the highest resolution DNA methylation profiling of HCV-associated HCC to date, testing ~2 million loci throughout the human genome in liver biopsies from 30 patients, identifying changes starting in infected liver and maintained through carcinogenesis. We identified loci at which DNA methylation is consistently altered, beginning earlier in the course of neoplastic disease and progressing with disease advancement.
Project description:The role of chronic hepatitis C virus (HCV) in the pathogenesis of HCV-associated hepatocellular carcinoma (HCC) is not completely understood, particularly at the molecular level. We studied gene expression in normal, pre-malignant (cirrhosis), and tumor (HCC) liver tissues using Affymetrix GeneChips. Keywords: cross-sectional
Project description:The role of chronic hepatitis C virus (HCV) in the pathogenesis of HCV-associated hepatocellular carcinoma (HCC) is not completely understood, particularly at the molecular level. We studied gene expression in normal, pre-malignant (cirrhosis), and tumor (HCC) liver tissues using Affymetrix GeneChips. Experiment Overall Design: Liver tissue samples were obtained from patients waiting for liver transplantation at one of the GR2HCC Centers. Additionally, normal liver and tumor samples were also obtained from the Liver Tissue Cell Distribution System. For each sample, RNA was extracted and hybridized to an Affymetrix GeneChip.
Project description:We performed miRNA array analysis for S-HCV (short-term HCV), L-HCV (long-term HCV) and control (uninfected Huh751), total for 3 samples to identify miRNA candidates in HCV-related HCC.
Project description:Background: Several studies have investigated the association of miRNAs with hepatocellular carcinoma (HCC) but the data are not univocal. Methods: We performed a microarray study of miRNAs in hepatitis C virus (HCV)-associated HCC and other liver diseases and healthy conditions. Results and Conclusions: The simultaneous comparison of different liver diseases and normal livers allowed the identification of 18 miRNAs exclusively expressed in HCV-associated HCC, with sensitivity and specificity values of diagnostic-grade. A total number of 76 liver specimens obtained from 43 patients were analyzed: 26 liver specimens obtained from 10 patients with HCV-associated HCC, including 9 specimens from the tumor area (HCC) and 17 specimens from the surrounding non-tumorous tissue affected by cirrhosis (HCC-CIR); 18 specimens from 10 patients with HCV-associated cirrhosis without HCC (CIR); 13 specimens from 4 patients with HBV-associated acute liver failure (ALF); 12 specimens from 12 liver donors (LD); and 7 from normal liver of 7 subjects who underwent hepatic resection for liver angioma (NL).
Project description:Background/Aims: Recurrence-free survival (RFS) following curative resection of hepatocellular carcinoma (HCC) in subjects with hepatitis C virus (HCV) infection is highly variable. Traditional clinico-pathological endpoints are recognized as weak predictors of RFS. It has been suggested that gene expression profiling of HCC and nontumoral liver tissue may improve prediction of RFS, aid in understanding of the underlying liver disease, and guide individualized therapy. The goal of this study was to create a gene expression predictor of HCC recurrence in subjects with HCV. Methods: Frozen samples of the tumors and nontumoral liver were obtained from 47 subjects with HCV-associated HCC. Additional nontumoral liver samples were obtained from HCV-free subjects with metastatic liver tumors. Gene expression profiling data was used to determine the molecular signature of HCV-associated HCC and to develop a predictor of RFS. Results: The molecular profile of the HCV-associated HCC confirmed central roles for MYC and TGF-beta1 in liver tumor development. Gene expression in tumors was found to have poor predictive power with regards to RFS, but analysis of nontumoral tissues yielded a strong predictor for RFS in late-recurring (>1 year) subjects. Importantly, nontumoral tissue-derived gene expression predictor of RFS was highly significant in both univariable and multivariable Cox proportional hazard model analyses. Conclusions: Microarray analysis of the nontumoral tissues from subjects with HCV-associated HCC delivers novel molecular signatures of RFS, especially among the late-recurrence subjects. The gene expression signature of the predictor gives important insights into the pathobiology of HCC recurrence and used in design of the individualized therapy. 43 tumor (JT) and 44 non-tumor (JNT) liver tissues surgically resected from patients with HCV-associated hepatocellular carcinoma; 8 non-tumor liver tissues (control samples, JC) surgically resected from HCV- or HBV-free patients with metastatic liver tumor. Inter-batch normalization was carried out using Distance Weighted Discrimination procedure. The supplementary file 'GSE17856_Readme.txt' contains a description of the replicates used for normalization. The 'GSE17856_US14702406_2514850*' files are the raw data files for the replicates.
Project description:Chronic hepatitis C (CHC) is one of the major risk factor for the progressive development of end stage liver diseases including liver cirrhosis (LC) and HCC worldwide. A deep insight into the molecular mechanism of development and progression of liver fibrosis into cirrhosis and HCC following chronic HCV infection leads to characterization of multiple cellular processes and the underlying regulatory mechanisms. Non-coding RNAs (sncRNAs) including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are found to be the prime regulators of multiple cellular pathways. Using such tools several studies have identified myriads of differentially regulated non-coding RNAs and genes in HCV disease progression to HCC. Our study attempted to look into the integrative network of regulatory non-coding RNAs and target genes involved in HCV related HCC and thereby identify a potential diagnostic molecule as well as therapeutic target for HCC surveillance and management.
