Gene Expression Profiling Unravels Hepatitis C Virus (HCV) Infection-induced Temporal Alteration of Gene Expression in Hepatocellular Carcinoma (HCC)
S.R., A. (2023). Gene Expression Profiling Unravels Hepatitis C Virus (HCV) Infection-induced Temporal Alteration of Gene Expression in Hepatocellular Carcinoma (HCC). EKB Journal Management System, 15(1), 339-352. doi: 10.21608/eajbsc.2023.292391
Almalki, Shaia S.R.. "Gene Expression Profiling Unravels Hepatitis C Virus (HCV) Infection-induced Temporal Alteration of Gene Expression in Hepatocellular Carcinoma (HCC)". EKB Journal Management System, 15, 1, 2023, 339-352. doi: 10.21608/eajbsc.2023.292391
S.R., A. (2023). 'Gene Expression Profiling Unravels Hepatitis C Virus (HCV) Infection-induced Temporal Alteration of Gene Expression in Hepatocellular Carcinoma (HCC)', EKB Journal Management System, 15(1), pp. 339-352. doi: 10.21608/eajbsc.2023.292391
S.R., A. Gene Expression Profiling Unravels Hepatitis C Virus (HCV) Infection-induced Temporal Alteration of Gene Expression in Hepatocellular Carcinoma (HCC). EKB Journal Management System, 2023; 15(1): 339-352. doi: 10.21608/eajbsc.2023.292391

Gene Expression Profiling Unravels Hepatitis C Virus (HCV) Infection-induced Temporal Alteration of Gene Expression in Hepatocellular Carcinoma (HCC)

Egyptian Academic Journal of Biological Sciences. C, Physiology and Molecular Biology
Volume 15, Issue 1, June 2023, Page 339-352  XML PDF (885.33 K)
Document Type: Original Article
DOI: 10.21608/eajbsc.2023.292391
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Author
Almalki, Shaia S.R.orcid
Laboratory Medicine, Faculty of Applied Medical Sciences, Albaha University
Abstract
Hepatitis C virus-induced liver cirrhosis and hepatocellular Carcinoma (HCC) is a global health concern. Underlying molecular mechanism of HCV-induced-HCC by temporal expression mRNA profiling of mock and HCV-infected Huh7.5.1dif cells was unraveled. A catalogue of bio-markers of HCC was analyzed to interpret the clinical relevance of the bio-markers. The percentage of over-expression and co-occurrence for targeted bio-markers within The Cancer Genomic Atlas (TCGA) were mapped using cBioPortal for cancer genomics. Spotting of differentially expressed genes (DEGs) and related temporal pathways enrichment analysis was accomplished employing MATLAB functions (e.g. mattest). Module analysis of the designed co-expression network using Cytoscape software was carried out. The overall expression of targeted bio-markers was recorded in 60% of the cases. Significantly overexpressed biomarkers recognized were CLK2, E2F5, CDK5, E2F3, MCM3, PCNA and CDK4. CCNB2, CLK2, CDK4, CDC7, E2F3, PCNA, and MCM3 predominantly controlled the co-expression of the listed bio-markers. After the initial phase of infection with a detrimental expression changing pattern, stability in expression followed by consistency in the level of expression of a set of genes was observed. Over-expressed screened biomarkers encompass the potential to be the candidate molecular target for surveillance, diagnosis and therapy of fetal HCV- induced-HCC. 
Keywords
HCV; HCC; bio-markers; gene; expression profiling; co-expression
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