access icon free Identification and analysis of circRNA–miRNA–mRNA regulatory network in hepatocellular carcinoma

© The Institution of Engineering and Technology
Received 08/06/2020, Accepted 01/09/2020, Revised 28/08/2020, Published 16/09/2020

This study was to identify important circRNA–miRNA–mRNA (ceRNAs) regulatory mechanisms in hepatocellular carcinoma (HCC). The circRNA dataset GSE97332 and miRNA dataset GSE57555 were used for analyses. Functional enrichment analysis for miRNA and target gene was conducted using cluster Profiler. Survival analysis was conducted through R package Survival. The ceRNAs and drug–gene interaction networks were constructed. The ceRNAs network contained five miRNAs including hsa-miR-25-3p, hsa-miR-3692-5p, hsa-miR-4270, hsa-miR-331-3p, and hsa-miR-125a-3p. Among the network, hsa-miR-25-3p targeted the most genes, hsa-miR-3692-5p and hsa-miR-4270 were targeted by more circRNAs than other miRNAs, hsa-circ-0034326 and hsa-circ-0011950 interacted with three miRNAs. Furthermore, target genes, including NRAS, ITGA5, SLC7A1, SEC14L2, SLC12A5, and SMAD2 were obtained in drug–gene interaction network. Survival analysis showed NRAS, ITGA5, SLC7A1, SEC14L2, SLC12A5, and SMAD2 were significantly associated with prognosis of HCC. NRAS, ITGA5, and SMAD2 were significantly enriched in proteoglycans in cancer. Moreover, hsa-circ-0034326 and hsa-circ-0011950 might function as ceRNAs to play key roles in HCC. Furthermore, miR-25-3p, miR-3692-5p, and miR-4270 might be significant for HCC development. NRAS, ITGA5, SEC14L2, SLC12A5, and SMAD2 might be prognostic factors for HCC patients via proteoglycans in cancer pathway. Taken together, the findings will provide novel insight into pathogenesis, selection of therapeutic targets and prognostic factors for HCC.

Inspec keywords: RNA; patient diagnosis; genetics; biochemistry; molecular biophysics; cellular biophysics; bioinformatics; drugs; cancer; tumours

Other keywords: miRNAs; ITGA5; target gene; SMAD2; therapeutic targets; hsa-circ-0034326; survival analysis; hsa-circ-0011950; SLC7A1; SLC12A5; drug–gene interaction network; prognostic factors; pathogenesis; current 125.0 A; hsa-miR-3692-5p; hsa-miR-25-3p; hsa-miR-4270; hsa-miR-331-3p; hsa-miR-125a-3p; circRNA-miRNA-mRNA regulatory network; SEC14L2

Subjects: Probability theory, stochastic processes, and statistics; Physical chemistry of biomolecular solutions and condensed states; Biomolecular interactions, charge transfer complexes; Biology and medical computing; Biomolecular structure, configuration, conformation, and active sites; Physics of subcellular structures; Patient diagnostic methods and instrumentation; Macromolecular configuration (bonds, dimensions)

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