Author/Authors :
Poortahmasebi، Vahdat نويسنده Hepatitis B Molecular Laboratory, Department of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, IR Iran , , Poorebrahim، Mansour نويسنده Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, I.R. Iran. , , Najafi، Saeideh نويسنده Department of Microbiology, Tonekabon Branch, Islamic Azad University, Tonekabon, IR Iran , , Jazayeri، Seyed Mohammad نويسنده Hepatitis B Molecular Laboratory-Department of Virology-School of Public Health-Tehran University of Medical Sciences, Tehran , , Alavian، Seyed-Moayed نويسنده , , Arab، Seyed Shahriar نويسنده Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, IR Iran , , Ghavami، Saeid نويسنده Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, Canada , , Alavian، Seyed Ehsan نويسنده Middle East Liver Diseases (MELD) Center, Tehran, IR Iran , , Rezaei-Moghadam، Adel نويسنده Young Researchers Club, Ardabil Branch, Islamic Azad University, Ardabil, Iran , , Amiri، Mehdi نويسنده Department of Cell Biology and Anatomy, Schulich School of Medicine and Dentistry, Western University, London, Canada ,
Abstract :
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. 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. 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. 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. Our results revealed the possible crucial genes and miRNAs involved in the initiation and progression of HCC cells infected with HCV.
