Objective
An increasing number of circular RNAs (circRNAs) have been identified as emerging competing endogenous RNAs (ceRNAs) that play important roles in hepatocellular carcinoma (HCC), but numerous circRNAs remain unexplored. The aim of this study was to explore the mechanism of action of differentially expressed circRNAs and their ceRNA networks in HCC.
Methods
Second-generation sequencing technology was used to analyse the expression of circRNAs in cancerous and paired paraneoplastic tissues from five patients with HCC. The circRNAs with a P value of less than 0.01, with an original signal value greater than 100 and ranked among the top ten upregulated circRNAs were selected and validated by quantitative reverse transcription polymerase chain reaction (qRT‒PCR) in paired cancer and paraneoplastic tissues from another 34 HCC patients. The downstream miRNAs and mRNAs of the circRNAs were explored through database analysis, and finally, the ceRNA networks and circRNA–miRNA–mRNA axes based on these ten circRNAs were constructed.
Results
By sequencing, we identified 9658 differentially expressed circRNAs on all chromosomes, of which 3862 were significantly upregulated and 5796 were significantly downregulated. RT-qPCR was performed to validate the top ten upregulated circRNAs, and the results were generally consistent with the sequencing results. After qRT‒PCR validation, five circRNAs (hsa_circ_0079875, hsa_circ0091580, hsa_circ0091581, hsa_circ0004788 and hsa_circ_0059730) were selected for further analysis. First, the downstream miRNAs and mRNAs of these five circRNAs were predicted to construct circRNA-miRNA‒mRNA network diagrams. The 1482 upregulated mRNAs identified in the GEPIA database overlapped with the 278 mRNAs in the ceRNA networks, and 14 overlapping genes were identified. Further bioinformatics analysis revealed four mRNAs (ADSL, AP3B1, MAPRE1, and TRNP1) and five circRNA–miRNA–mRNA axes that were negatively correlated with HCC prognosis.
Conclusions
Numerous differentially expressed circRNAs exist in HCC, and most can regulate the biological behaviour of HCC through circRNA-miRNA‒mRNA networks. Bioinformatics analysis showed that the ceRNA regulatory axes in HCC have high diagnostic and prognostic value and deserve further exploration. This study aims to provide new research ideas related to HCC pathogenesis and treatment options.