Comprehensive Analysis of Competing Endogenous RNA (ceRNA) Network Based on RNAs Differentially Expressed in Lung Adenocarcinoma Using The Cancer Genome Atlas (TCGA) Database

BACKGROUND: The aim of this study was to explore a comprehensive analysis of the competing endogenous (ceRNA) network of lung adenocarcinoma and predict its regulatory mechanism and prognosis correlation based on The Cancer Genome Atlas (TCGA) database. MATERIAL/METHODS: The genes expression data from 535 lung adenocarcinoma cases and 59 normal tissue cases were acquired and downloaded from TCGA database, and differentially expressed messenger RNA (mRNA), long noncoding RNA (lncRNA) and microRNA (miRNA) were selected primarily by “edgeR” package in R software, which further constructs lncRNA-miRNA-mRNA ceRNA network. We then proceed to carry out Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and Kaplan-Meier survival analysis of the mRNAs involved in the ceRNA network. RESULTS: There are 3 mRNAs (ANLN, IGFBP1, and TFAP2A) in differentially expressed genes, 4 lncRNAs (AC015923.1, FGF12-AS2, LINC00211, and MED4-AS1), and 2 miRNAs (miR-31 and miR-490) associated with the prognostic of lung adenocarcinoma. Besides, LINC00461 and has-mir-139 as key nodes were found in the ceRNA network. Significantly, miR-31 shows the greatest prognostic value related to the adverse effect of the prognostic of lung adenocarcinoma (P<0.001). CONCLUSIONS: By analyzing the expression data of lung adenocarcinoma in TCGA database, we found that 3 mRNAs, 4 lncRNAs, and 2 miRNAs were screened as potential prognostic factors for lung adenocarcinoma. In addition, LINC00461 and has-mir-139 are 2 important regulatory network nodes in lung adenocarcinoma ceRNA.