ArticleHepatitis monthly2016
How Hepatitis C Virus Leads to Hepatocellular Carcinoma: A Network-Based Study.
Article in Hepatitis monthly, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 19 citations in OpenAlex.
- Review
- IL6-mediated HCoV-host interactome regulatory network and GO/Pathway enrichment analysis.PLoS computational biology · 2020Article
- microRNAs: Key players in virus-associated hepatocellular carcinoma.Journal of cellular physiology · 2019Review
- Association between the expression of carbonic anhydrase II and clinicopathological features of hepatocellular carcinoma.Oncology letters · 2019Article
- Zerumbone suppresses the potential of growth and metastasis in hepatoma HepG2 cells via the MAPK signaling pathway.Oncology letters · 2018Article
- Leveraging Experimental Details for an Improved Understanding of Host-Pathogen Interactome.Current protocols in bioinformatics · 2018Article
- Key genes and regulatory networks involved in the initiation, progression and invasion of colorectal cancer.Future science OA · 2018Article
- Causal role of infectious agents in cancer: An overview.Caspian journal of internal medicine · 2017Review
Corrections and comments
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Authors and funding
10 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHepatitis 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.
objectivesIn 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
methodsAfter 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.
resultsBased 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.
conclusionsOur results revealed the possible crucial genes and miRNAs involved in the initiation and progression of HCC cells infected with HCV.
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