Background: The mortality rate of hepatocellular carcinoma（HCC）is the third highest worldwide. Infection with hepatitis B virus (HBV）is an important risk factor for the development of HCC. The fact that there is no available target drug for the HCC highlights the necessity to further explore its underlying mechanism.
Methods: Gene expression profiles of GSE121248, GSE55092 and GSE62232 were accessible from GEO database. From 129 HCC tissues and 138 normal tissues in the three profile datasets, we picked out differentially expressed genes (DEGs) using GEO2R and Venn diagram software，analyzed Gene and Genome (KEGG) pathway and gene ontology (GO) in DEGs through DAVID software, and simulated the interactions between DEGs using the plotting function of STRING database, as well as constructed a protein-protein interaction (PPI) network by Cytoscape software Consequently significant genes with potential poor prognosis were selected using UALCAN and validated in Gene Expression Profiling Interactive Analysis.
Results: In total of 103 DEGs in the three datasets, there were 26 up-regulated genes rich in regulation of attachment of spindle microtubules to kinetochore, protein localization to kinetochore, mitotic cytokinesis, cytokinesis, positive regulation of cytokinesis, Cell cycle and p53 signaling pathway while 77 down-regulated genes enriched in Retinol metabolism, Caffeine metabolism, Drug metabolism - cytochrome P450, Metabolism of xenobiotics by cytochrome P450, Chemical carcinogenesis, oxidation-reduction process, exogenous drug catabolic process, xenobiotic metabolic process, monocarboxylic acid metabolic process, epoxygenase P450 pathway and drug metabolic process. PPI network analyzed by Molecular Complex Detection (MCODE) plug-in, we found 14 hub genes including TOP2A, CCNB1, RACGAP1, DTL, PBK, NEK2, PRC1, CDK1, RRM2, BUB1B, ECT2, ANLN, HMMR, ASPM, among which demonstrated 13 genes (except PRC1) had a significantly worse prognosis based on UALCAN analysis. All of the 13 genes were highly expressed in HBV related HCC tissues compared to normal tissues through GEPIA analysis.
Conclusion: The significant up-regulated DEGs found by using integrated bioinformatical methods could be potential therapeutic targets for HBV related HCC patients.