Hub gene identification and prognostic model establishment for patients with HBV-related hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is associated with poor 5-year survival. Chronic infection with hepatitis B virus (HBV) contributes to ~50% of HCC cases. Identification of biomarkers is pivotal for the therapy of HBV-related HCC (HBV–HCC). We downloaded gene-expression profiles from Gene expression omnibus (GEO) datasets with HBV-HCC patients and the corresponding controls. Integration of these differentially expressed genes (DEGs) was achieved with the Robustrankaggreg (RRA) method. DEGs functional analyses and pathway analyses was performed using the Gene ontology (GO) database, and the Kyoto encyclopedia of genes and genomes (KEGG) database respectively. Cyclin-dependent kinase 1 (CDK1), Cyclin B1 (CCNB1), Forkhead box M1 (FOXM1), Aurora kinase A (AURKA), Cyclin B2 (CCNB2), Enhancer of zeste homolog 2 (EZH2), Cell division cycle 20 (CDC20), DNA topoisomerase II alpha (TOP2A), BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B), and ZW10 interactor (ZWINT), were identified as the top-ten hub genes. The expression of hub-genes was verified in the liver cancer-riken, JP project from international cancer genome consortium (ICGC-LIRI-JP), the cancer genome atlas (TCGA) HCC cohort, and Human protein profiles dataset. A four-gene prognostic related model based on the expression of ZWINT, EZH2, FOXM1 and CDK1 were established through Cox regression analysis in ICGC-LIRI-JP project, and verified in TCGA-HCC cohort. Furthermore, a nomogram model based on pathology stage, gender and four-genes prognostic model was built to predict the prognosis for HBV–HCC patients. In conclusion, ZWINT, EZH2, FOXM1 and CDK1 play a pivotal role in HBV-HCC, and are potential therapeutic targets of HBV HCC.