Abstract

BackgroundHepatocellular carcinoma (HCC) has a poor long-term prognosis. The competition of circular RNAs (circRNAs) with endogenous RNA is a novel tool for predicting HCC prognosis. Based on the alterations of circRNA regulatory networks, the analysis of gene modules related to HCC is feasible. MethodsMultiple expression datasets and RNA element targeting prediction tools were used to construct a circRNA-microRNA-mRNA network in HCC. Gene function, pathway, and protein interaction analyses were performed for the differentially expressed genes (DEGs) in this regulatory network. In the protein-protein interaction network, hub genes were identified and subjected to regression analysis, producing an optimized four-gene signature for prognostic risk stratification in HCC patients. Anti-HCC drugs were excavated by assessing the DEGs between the low- and high-risk groups. A circRNA-microRNA-hub gene subnetwork was constructed, in which three hallmark genes, KIF4A, CCNA2, and PBK, were subjected to functional enrichment analysis. ResultsA four-gene signature (KIF4A, CCNA2, PBK, and ZWINT) that effectively estimated the overall survival and aided in prognostic risk assessment in the The Cancer Genome Atlas (TCGA) cohort and International Cancer Genome Consortium (ICGC) cohort was developed. CDK inhibitors, PI3K inhibitors, HDAC inhibitors, and EGFR inhibitors were predicted as four potential mechanisms of drug action (MOA) in high-risk HCC patients. Subsequent analysis has revealed that PBK, CCNA2, and KIF4A play a crucial role in regulating the tumor microenvironment by promoting immune cell invasion, regulating microsatellite instability (MSI), and exerting an impact on HCC progression. ConclusionsThe present study highlights the role of the circRNA-related regulatory network, identifies a four-gene prognostic signature and biomarkers, and further identifies novel therapy for HCC.

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