Identification of Hub Genes Associated with Hepatocellular Carcinoma Prognosis by Bioinformatics Analysis

Objective: This study aimed to identify hub genes that are associated with hepatocellular carcinoma (HCC) prognosis by bioinformatics analysis. Methods: Data were collected from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) liver HCC datasets. robust rank aggregation algorithm was used in integrating data on differentially expressed (DEGs). Online databases DAVID 6.8 REACTOME for gene ontology pathway enrichment R software version 3.5.1, Cytoscape, Kaplan-Meier plotter genes. Results: Six GEO datasets TCGA dataset included this A total of 151 upregulated 245 downregulated DEGs identified. most significantly enriched functional categories cell division, chromosomes, centromeric regions, protein binding, whereas epoxygenase P450 pathway, extracellular region, heme respect biological process, cellular component, molecular function analysis, respectively. Upregulated DEGS cycle metabolism pathway. Finally, 88 40 identified as top 10 CDK1, CCNB1, CCNB2, CDC20, CCNA2, AURKA, MAD2L1, TOP2A, BUB1B BUB1. ESR1, IGF1, FTCD, CYP3A4, SPP2, C8A, CYP2E1, TAT, F9 CYP2C9. Conclusions: several patients. Verification these results using vitro vivo studies is warranted.