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Integrated bioinformatics reveals potential drug targets in hepatocellular carcinoma
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Abstract
Introduction: Amongst the most prevalent cancers, hepatocellular carcinoma (HCC) is one of the cancers with high mortality rate due to limitation in diagnosis and treatment. In recent years, bioinformatics has become an effective tool, contributing significantly to the discovery and development of new drug. Objective: This study was carried out to evaluate prospective drug targets for the therapy of this illness by using bioinformatics tools. Methods: Microarray data from the dataset GSE147888, GSE101685, GSE62232 showing the gene expression in HCC patients was downloaded from the Gene Expression Omnibus. GEO2R was exploited to screen differentially expressed genes (DEGs) in HCC and normal counterparts. To identify possible drug targets, the protein-protein interaction network was investigated using Cytoscape, and the potential drug targets were validated using Gene Expression Profiling Interactive Analysis (GEPIA), Human Protein Atlas (HPA) and Kaplan-Meier plotter. Results: The study identified 538 DEGs comprising 227 up-regulated genes and 311 down-regulated genes. Among those genes, CDK1, CCNB1, CCNA2, CDC20, TOP2A, CCNB2 and MAD2L1 were confirmed as hub genes, which can serve as the important factors for the development of new targeted drugs. Conclusion: This study utilized an in-silico model to identify potential therapeutic targets for HCC, thereby highlighting the practical value of bioinformatics in discovering and developing novel treatment strategies for HCC.
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Keywords
Bioinformatics, drug target, HCC, liver cancer.
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