Bioinformatics analysis of the interactions among lncRNA, miRNA and mRNA expression, genetic mutations and epigenetic modifications in hepatocellular carcinoma.

The present study aimed to investigate the regulatory networks involving long noncoding RNA (lncRNA), microRNA (miRNA), mRNA, genetic mutations and epigenetic modifications in hepatocellular carcinoma (HCC) by analyzing datasets from The Cancer Genome Atlas (TCGA) database. TCGA was mined, and miRNAs, lncRNAs and mRNAs that were differentially expressed in HCC were identified using R software. A gene regulatory network was constructed using Cytoscape software. Representative genes were selected for functional enrichment analysis using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. The associations among various proteins and protein networks were identified using the online software Search Tool for the Retrieval of Interacting Genes/Proteins. The cBioPortal database was used to analyze the association between genetic mutations and epigenetic modification, and the development of HCC. A total of 35 mRNAs were predicted to be targeted by 77 lncRNAs and 16 miRNAs, establishing a lncRNA‑miRNA‑mRNA regulatory network for HCC. Multivariable Cox regression analysis suggested that long intergenic non‑protein coding RNA 200, miRNA‑137, PDZ binding kinase and DNA polymerase θ were independent prognostic factors. In a regulatory network centered on miRNA‑424, six mRNA target genes were associated with HCC survival rates. Protein‑protein interaction analysis suggested that cell division cycle 25A (CDC25A) interacted with centrosomal protein 55 (CEP55), claspin, E2F transcription factor 7 and cyclin E1 (CCNE1. Mutations in CEP55 affected overall survival and disease‑free survival in HCC, whereas, mutations in CDC25A affected overall survival, and mutations in E2F7 affected disease‑free survival. Decreased methylation levels of CEP55, CDC25A and CCNE1 were associated with vascular invasion. The survival rate of patients with hypermethylation of CCNE1 and CEP55 was significantly associated with the rate of methylation of these loci. The present study provides an integrated bioinformatics analysis of gene expression, genetic mutations and epigenetic modifications that may be associated with the development of HCC.