Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

Abstract

Objective: The objective was to identify potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma (HCC). Methods: Gene expression profile datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between HCC and normal samples were identified via an integrated analysis. A protein–protein interaction network was constructed and analyzed using the STRING database and Cytoscape software, and enrichment analyses were carried out through DAVID. Gene Expression Profiling Interactive Analysis and Kaplan–Meier plotter were used to determine expression and prognostic values of hub genes. Results: We identified 11 hub genes (CDK1, CCNB2, CDC20, CCNB1, TOP2A, CCNA2, MELK, PBK, TPX2, KIF20A, and AURKA) that might be closely related to the pathogenesis and prognosis of HCC. Enrichment analyses indicated that the DEGs were significantly enriched in metabolism-associated pathways, and hub genes and module 1 were highly associated with cell cycle pathway. Conclusions: In this study, we identified key genes of HCC, which indicated directions for further research into diagnostic and prognostic biomarkers that could facilitate targeted molecular therapy for HCC.