The study of competing endogenous RNAs regulatory network in hepatocellular carcinoma via bioinformatics

Abstract

Background Hepatocellular carcinoma (HCC) is among the most prevalent and lethal cancers globally and individuals diagnosed at advanced stages. The discovery of new diagnostic and prognostic markers in HCC is urgent. Circular RNAs (circRNAs) have emerged as key players in the intricate landscape of gene regulation through the competing endogenous RNA (ceRNA) mechanism. However, the ceRNA mechanism of circRNAs in HCC still remains unclear. Methods This study conducted a comprehensive HCC analysis using GEO database expression profiles for circRNAs, miRNAs, and mRNAs. Differentially expressed genes (DEGs) were revealed and visually presented through R-generated volcano plots and heatmaps. The STRING website and Cytoscape facilitated the construction of a protein-protein interaction (PPI) network. Functional enrichment analyses validated signaling pathways, and a circRNA-miRNA-mRNA network was constructed through Cytoscape. Results The study identified 86 differentially expressed mRNAs (33 upregulated, 43 downregulated) across GSE168852, GSE169289, and GSE202069 datasets. Volcano plots and Venn diagrams illustrated gene expression changes. Gene ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) analysis revealed functional insights. A PPI network identified 8 key genes (HMMR, EXO1, TOP2A, CCNB1, NUF2, CCNB2, BUB1, BUB1B) validated by GEPIA and Kaplan-Meier Plotter. The Cytoscape built ceRNA network unveiled regulatory modules involving 4 mRNAs, 9 miRNAs, and 31 circRNAs. Conclusions In summary, this study established circRNA-miRNA-mRNA regulatory modules, including 4 mRNAs, 9 miRNAs, and 31 circRNAs. This offers an effective bioinformatics strategy for studying HCC molecular mechanisms and prognosis. This might provide a realm of the molecular with diagnosis and prognosis biomarkers in HCC.