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How Hepatitis C Virus Leads to Hepatocellular Carcinoma: A Network-Based Study Publisher



Poortahmasebi V1 ; Poorebrahim M2 ; Najafi S3 ; Jazayeri SM1 ; Alavian SM4 ; Arab SS5 ; Ghavami S6 ; Alavian SE4 ; Moghadam AR6 ; Amiri M7
Authors
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Authors Affiliations
  1. 1. Hepatitis B Molecular Laboratory, Department of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  2. 2. Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. Department of Microbiology, Tonekabon Branch, Islamic Azad University, Tonekabon, Iran
  4. 4. Middle East Liver Diseases (MELD) Center, Tehran, Iran
  5. 5. Department of Biophysics, Tarbiat Modares University, Tehran, Iran
  6. 6. Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, Canada
  7. 7. Department of Cell Biology and Anatomy, Schulich School of Medicine and Dentistry, Western University, London, Canada

Source: Hepatitis Monthly Published:2016


Abstract

Background: Hepatitis C virus (HCV) has been known as a major cause of hepatocellular carcinoma (HCC) worldwide. However, the distinct molecular mechanisms underlying the effects of HCV proteins on the HCC progression have remained unclear. Objectives: In the present study, we studied the possible role of HCV in the HCC initiation and invasion using topological analysis of protein-protein interaction (PPI) networks. Materials and Methods: After analysis with GEO2R, a PPI network of differentially expressed genes (DEGs) was constructed for both chronic HCV and HCC samples. The STRING and GeneMANIA databases were used to determine the putative interactions between DEGs. In parallel, the functional annotation of DEGs was performed using g: Profiler web tool. The topological analysis and network visualization was carried outperformed using Cytoscape software and the top hub genes were identified. We determined the hub genes-related miRNAs using miRTarBase server and reconstructed a miRNA-Hubgene network. Results: Based on the topological analysis of miRNA-Hubgene network, we identified the key hub miRNAs. In order to identify the most important common sub-network, we aligned two PPI networks using NETAL tool. The c-Jun gene was identified as the most important hub gene in both HCV and HCC networks. Furthermore, the hsa-miR-34a, hsa-miR-155, hsa-miR-24, hsa-miR-744 and hsa-miR-92a were recognized as the most important hub miRNAs with positive correlation in the chronic HCV and HCC samples. Functional annotation of differentially expressed miRNAs (DEMs) using the tool for annotations of human miRNAs (TAM) revealed that there is a considerable overlap between miRNA gene expression profiles of HCV-infected and HCC cells. Conclusions: Our results revealed the possible crucial genes and miRNAs involved in the initiation and progression of HCC cells infected with HCV. © 2016, Kowsar Corp.