Construction of a circRNA-miRNA-mRNA Network and Prognostic Model to Unveil Prognosis and Immunotherapy Prospects of Hepatocellular Carcinoma

Background: This study aimed at understanding the mechanisms underlying the pathogenesis of hepatocellular carcinoma (HCC) and to provide biomarkers for prognosis as well as immunotherapy and chemotherapy by constructing a circular (circ)RNA-micro (mi)RNA-mRNA ceRNA network and risk model. Methods:High-throughput sequencing data including circRNA, miRNA, and mRNA expression profiles for HCC were downloaded from the Gene Expression Omnibus (GEO) database.Differentially expressed circRNAs, miRNAs, and mRNAs were identified and screened by Limma package in R language.Based on circRNA-miRNA pairs and miRNA-mRNA pairs, a ceRNA network was constructed.The potential functions of differentially expressed circRNAs were analyzed using gene ontology (GO) and the Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis.mRNAs with a significant prognosis were screened using Univariate COX regression analysis, and were used to construct a prognosis model using Lasso regression.The prognostic value of the model was then evaluated by performing a survival analysis and establishing a ROC curve.Finally, the predictive ability of the model for immunotherapy and sensitivity to chemotherapy was analyzed.Results: A total of 72 up-regulated circRNAs, 49 down-regulated circRNAs, 8 up-regulated miRNAs, 5 downregulated miRNAs, 772 up-regulated mRNAs, and 929 down-regulated mRNAs were differentially expressed in HCC.A ceRNA network composed of target genes was constructed, incorporating 7 circRNAs, 4 miRNAs, and 10 differently expressed genes (mRNAs).A prognostic model was constructed based on 4 prognosisrelated mRNAs (PSMD10, RAB15, ESR1, and PPARGC1A) and tested in HCC patients divided into training and validation groups, with AUC = 0.704 in the training group and AUC = 0.661 in the validation group.Univariate and multivariate COX regression demonstrated that the proposed model could be used as an independent prognostic model in HCC.The expression of PD-1 in the high-risk group was found to be higher than that in the low-risk group.Moreover, the IC50 of cisplatin and paclitaxel was lower in the high-risk group. Conclusions:Our study provides a rationale for the circRNA-miRNA-mRNA regulatory network as a promising tool for mechanism research and biomarker identification of occurrence and prognosis of HCC patients.The constructed prognostic model based on 4 prognosis-related mRNAs (PSMD10, RAB15, ESR1, and PPARGC1A) is proposed as a new indicator in guiding immunotherapy and chemotherapy management in HCC.