Construction of a disease-specific lncRNA-miRNA-mRNA regulatory network reveals potential regulatory axes and prognostic biomarkers for hepatocellular carcinoma

Cancer Med. 2020 Dec;9(24):9219-9235. doi: 10.1002/cam4.3526. Epub 2020 Nov 24.

Abstract

Hepatocellular carcinoma (HCC) is a heterogeneous malignancy with a high incidence and poor prognosis. Exploration of the underlying mechanisms and effective prognostic indicators is conducive to clinical management and optimization of treatment. The RNA-seq and clinical phenotype data of HCC were retrieved from The Cancer Genome Atlas (TCGA), and differential expression analysis was performed. Then, a differential lncRNA-miRNA-mRNA regulatory network was constructed, and the key genes were further identified and validated. By integrating this network with the online tool-based ceRNA network, an HCC-specific ceRNA network was obtained, and lncRNA-miRNA-mRNA regulatory axes were extracted. RNAs associated with prognosis were further obtained, and multivariate Cox regression models were established to identify the prognostic signature and nomogram. As a result, 198 DElncRNAs, 120 DEmiRNAs, and 2827 DEmRNAs were identified, and 30 key genes identified from the differential network were enriched in four cancer-related pathways. Four HCC-specific lncRNA-miRNA-mRNA regulatory axes were extracted, and SNHG11, CRNDE, MYLK-AS1, E2F3, and CHEK1 were found to be related with HCC prognosis. Multivariate Cox regression analysis identified a prognostic signature, comprised of CRNDE, MYLK-AS1, and CHEK1, for overall survival (OS) of HCC. A nomogram comprising the prognostic signature and pathological stage was established and showed some net clinical benefits. The AUC of the prognostic signature and nomogram for 1-year, 3-year, and 5-year survival was 0.777 (0.657-0.865), 0.722 (0.640-0.848), and 0.630 (0.528-0.823), and 0.751 (0.664-0.870), 0.773 (0.707-0.849), and 0.734 (0.638-0.845), respectively. These results provided clues for the study of potential biomarkers and therapeutic targets for HCC. In addition, the obtained 30 key genes and 4 regulatory axes might also help elucidate the underlying mechanism of HCC.

Keywords: CeRNA network; differential network analysis; hepatocellular carcinoma; nomogram; prognostic signature.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers, Tumor / genetics
  • Carcinoma, Hepatocellular / genetics*
  • Carcinoma, Hepatocellular / metabolism
  • Carcinoma, Hepatocellular / pathology
  • Computational Biology / methods
  • Databases, Genetic
  • Gene Expression Regulation, Neoplastic
  • Gene Regulatory Networks
  • Humans
  • Liver Neoplasms / genetics*
  • Liver Neoplasms / metabolism
  • Liver Neoplasms / pathology
  • MicroRNAs / genetics*
  • Nomograms
  • Prognosis
  • RNA, Long Noncoding / genetics*
  • RNA, Messenger / genetics*
  • Survival Rate

Substances

  • Biomarkers, Tumor
  • MicroRNAs
  • RNA, Long Noncoding
  • RNA, Messenger