Construction of a ceRNA Network and Comprehensive Analysis of lncRNA in Hepatocellular Carcinoma

Genes (Basel). 2022 Apr 28;13(5):785. doi: 10.3390/genes13050785.

Abstract

To explore the RNA biomolecular marker associated with hepatocellular carcinoma (HCC) prognosis, we constructed a regulatory network of competitive endogenous RNAs (ceRNAs), which provides favorable conditions for the early diagnosis, prognostic monitoring, and personalized treatment of HCC. In this study, the differentially expressed genes (DEGs) of patients with HCC were obtained from the Gene Expression Omnibus. We identified 574 upregulated genes and 274 downregulated genes relevant to HCC occurrence (p < 0.05). Subsequently, we constructed the protein−protein interaction (PPI) network using these DEGs and identified the hub genes from the PPI. We then determined the expression and prognostic values of the hub genes from the GEPIA and Kaplan−Meier plotter databases. After the upstream microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) were respectively identified by miRTarBase and miRNet, we validated the expression of the key miRNAs in the serum using qPCR experiments. Moreover, we identified a two-lncRNA (LINC01184 and ADORA2A-AS1) signature from the upstream lncRNA that effectively predicted overall survival and had promotive effects for HCC. To verify the clinical significance of the signature, we validated the expression of the lncRNA in HCC tissues. Finally, we discovered and identified four mRNAs, four miRNAs, and five lncRNAs associated with the prognosis of HCC and constructed a new ceRNA regulatory network, which will be beneficial for the accurate diagnosis and treatment of HCC.

Keywords: bioinformatics analysis; competing endogenous RNA; hepatocellular carcinoma; mRNA–miRNA–lncRNA.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Carcinoma, Hepatocellular* / pathology
  • Gene Expression Regulation, Neoplastic
  • Gene Regulatory Networks
  • Humans
  • Liver Neoplasms* / pathology
  • MicroRNAs* / genetics
  • MicroRNAs* / metabolism
  • RNA, Long Noncoding* / genetics
  • RNA, Long Noncoding* / metabolism

Substances

  • MicroRNAs
  • RNA, Long Noncoding

Grants and funding

This research was funded by the Natural Science Foundation of Anhui Province of China (2108085QC96), the Youth Innovation Promotion Association of the Chinese Academy of Sciences (No. 2018489).