Identification and integrated analysis of hepatocellular carcinoma-related circular RNA signature

Circular RNAs (circRNAs), a novel type of non-coding RNA, play a vital role in the pathogenesis and development of cancer. CircRNAs signatures may be useful as prognostic and predictive factors as well as clinical tools for evaluating disease status and prognosis. This study was carried out to explore novel circRNA signatures in hepatocellular carcinoma (HCC).

The expression profiles of circRNAs were retrieved from the Gene Expression Omnibus (GEO). The expression profiles of miRNAs and mRNAs were obtained from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database. The results of the microarray were validated by quantitative real-time RCR (qPCR). Based on circRNA-miRNA pairs and miRNA-mRNA pairs, a competitive endogenous RNA (ceRNA) network was constructed. Functional analysis was performed via Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA). Furthermore, survival analysis was carried out using the Kaplan-Meier curve and the log-rank test.

Differentially expressed circRNAs in HCC from GEO databases (GSE94508 and GSE97332) were screened and analyzed using the bioinformatics method. We detected a total of 26 differentially expressed circRNAs by qPCR and then selected 6 circRNAs to construct the circRNA-miRNA-mRNA networks. Through prognostic analysis, 3 target hub genes (AURKA, KIF5B, and RHOA) of circRNAs were discovered. Moreover, GSEA and GSVA were used to reveal the functions of AURKA, KIF5B, and RHOA in HCC.

We identified three hub genes, and our results suggest that the circHMGCS1/miR-581/AURKA, circHMGCS1/miR-892a/KIF5B, and circTMCO3/miR-577/RHOA axes may play a vital role in HCC progression.