Identification of Hub Genes and Analysis of Prognostic Values in Hepatocellular Carcinoma by Bioinformatics Analysis

Abstract

Background: Hepatocellular carcinoma (HCC) is one of the most frequent cancers in the world. In this study, differentially expressed genes (DEGs) between tumor tissues and normal tissues were identified using the comprehensive analysis method in bioinformatics.

Materials and methods: We downloaded 3 mRNA expression profiles from the Gene Expression Omnibus database to identify DEGs between tumor tissues and adjacent normal tissues. The Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway analysis, protein-protein interaction network was performed to understand the function of DEGs. OncoLnc, which was linked to The Cancer Genome Atlas survival data, was used to investigate the prognostic values of hub genes. The expression of selected hub genes was validated by the quantitative real-time polymerase chain reaction.

Results: A total of 235 DEGs, consisting of 36 upregulated and 199 downregulated genes, were identified between tumor tissue and normal tissue. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis results showed the upregulated DEGs to be significantly enriched in cell division, mid-body, ATP binding and oocyte meiosis pathways. The downregulated DEGs were mainly involved in epoxygenase P450 pathway, extracellular region, oxidoreductase activity and metabolic pathways. Ten hub genes, including Aurora kinase A, Cell division cycle 20, formiminotransferase cyclodeaminase, UBE2C, Cyclin B2, pituitary tumor-transforming gene 1, CDKN3, CKS1B, Topoisomerase-II alpha and KIF20A, were identified as the key genes in HCC. Survival analysis found the expression of hub genes to be significantly correlated with the survival of patients with HCC.

Conclusions: The present study identified hub genes and pathways in HCC that may be potential targets for diagnosis, treatment and prognostic prediction.

Keywords: Bioinformatics; Gene; Hepatocellular carcinoma.