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Integrative analysis of microRNAs and mRNAs in liver tissue and exosomes from blood of hepatitis C virus (HCV) related hepatocellular carcinoma (HCC) patient to identify biomarker and regulators of HCC [Total RNA-Seq]

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE140845 | GEO | 2019/11/23

REPOSITORIES: GEO

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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.

Dataset Information

Integrative analysis of microRNAs and mRNAs in liver tissue and exosomes from blood of hepatitis C virus (HCV) related hepatocellular carcinoma (HCC) patient to identify biomarker and regulators of HCC [Total RNA-Seq]

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