Screening of hepatocellular carcinoma hub genes and construction of a control network

Background: Hepatocellular carcinoma (HCC) is a malignant tumor that threatens human life and health. However, the molecular mechanisms of hepatocarcinogenesis remain unclear. Aim: The current study aimed to explore the molecular mechanisms of HCC through screening and functional analysis of differentially-expressed genes of HCC, providing a new method for diagnosis and treatment of HCC. Methods: Gene expression arrays of 14 pairs of HCC tissues and corresponding non-cancerous tissues were obtained from the GEO database. Next, this study identified differentially-expressed genes using the R program. The gene function and protein-protein interaction (PPI) network of DEGs was analyzed using the DAVID website and STRING database. Visualization was conducted with Cytoscape 3.7.0 software. An MCC algorithm was used to screen high connectivity hub genes. At the same time, a hub gene-miRNA regulatory network was constructed. Finally, verification of the hub genes was conducted using Kaplan-Meier and UALCAN websites. Results: A total of 285 DEGs were identified to be significantly associated with HCC tissues, including 56 upregulated and 229 downregulated genes. Gene ontology analysis revealed that downregulated genes were mainly involved in Redox and metabolic processes. Furthermore, 20 hub genes were screened. Five genes, including RRM2, CCNB1, CDK1, NCAPG, and KIF20A, were found to be highly regulated by miRNAs. Validation results showed that expression of 20 hub genes was significantly higher in HCC tissues and closely related to prognosis of HCC patients. Conclusion: Through bioinformatics analysis, the roles of DEGs in HCC were examined. Thus study may provide a new molecular target for diagnosis and treatment of HCC, providing a theoretical basis for further study of the molecular mechanisms of HCC.