Bioinformatics analysis of core differentially expressed genes in hepatitis B virus-related hepatocellular carcinoma

Abstract

To identify the core genes associated with the development and progression of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), so as to provide insights into the elucidation of pathogenesis of HBV-related HCC. GSE55092 and GSE121248 datasets were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between HCC and peri-cancer tissues were screened using the R package, and the volcano map of DEGs were plotted. The DEGs were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and a protein-protein interaction (PPI) network was created. The hub DEGs were screened using Molecular Complex Detection (MCODE) and cytoHubba plugins in the open-access platform Cytoscape 3.9.0. Then, the screened hub DEGs were validated for differential expression and survival analysis using clinical sample data captured from the UALCAN and Kaplan Meier-plotter databases. A total of 1 148 and 686 DEGs were screened between HCC and peri-cancer tissues in GSE55092 and GSE121248 datasets, including 703 and 477 down-regulated genes and 445 and 209 up-regulated genes, respectively. A total of 557 common DEGs were screened between GSE55092 and GSE121248 datasets, including 384 down-regulated genes and 173 up-regulated genes. GO enrichment analysis showed that these DEGs were significantly enriched in biological processes of cell division, cell proliferation, redox process, immune response and proteolysis, cellular components of cell nucleus, cytoplasm, extracellular vesicle and endoplasmic reticulum membrane, and molecular functions of binding to calcium ion, protein kinase, DNA and heme. KEGG pathway analysis revealed that these DEGs were significantly enriched in pathways of cell cycle, oocyte meiosis, metabolic pathway, antibiotic biosynthesis and p53 signaling. PPI network analysis identified 10 DEGs, including CDK1, CCNB1, CCNA2, TOP2A, AURKA, CCNB2, KIF11, CDC20, KIF20A and BUB1B, and CDK1, KIF11 and KIF20A were found to be differentially expressed and correlate with poor prognosis among HBV-related HCC patients following clinical sample data validation. CDK1, KIF11 and KIF20A may play a critical role in the development and progression of HBV-related HCC, which may be potential diagnostic biomarkers and therapeutic targets of HBV-related HCC.