Integrated Analysis of lncRNA-Mediated ceRNA Network in Lung Adenocarcinoma

Xianxian Wu; Zhilin Sui; Hongdian Zhang; Ying Wang; Zhentao Yu

doi:10.3389/fonc.2020.554759

Integrated Analysis of lncRNA-Mediated ceRNA Network in Lung Adenocarcinoma

Front Oncol. 2020 Sep 15:10:554759. doi: 10.3389/fonc.2020.554759. eCollection 2020.

Authors

Xianxian Wu¹, Zhilin Sui¹, Hongdian Zhang¹, Ying Wang¹, Zhentao Yu¹

Affiliation

¹ Department of Esophageal Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China.

Abstract

Background: A growing body of evidence indicates that long non-coding RNAs (lncRNAs) can act as competitive endogenous RNAs (ceRNAs) to bind to microRNAs (miRNAs), thereby affecting and regulating the expression of target genes. The lncRNA-miRNA-mRNA ceRNA network has been theorized to play an indispensable role in many types of tumors. However, the role of the lncRNA-related ceRNA regulatory network in lung adenocarcinoma (LUAD) remains unclear.

Methods: We downloaded the RNAseq and miRNAseq data of LUAD from The Cancer Genome Atlas (TCGA) data portal and identified differentially expressed lncRNAs (DElncRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) between LUAD and corresponding paracancerous tissues by using the edgeR package of R software. We constructed the lncRNA-miRNA-mRNA ceRNA network by using Cytoscape (version 3.7.2) on the basis of the interaction generated from the miRcode, miRTarBase, miRDB, and TargetScan databases. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed with DAVID 6.8 bioinformatics resources and plotted by using the ggplot2 package in R. The effect of genes on LUAD prognosis was assessed by applying the survival package in R in accordance with the Kaplan-Meier curve.

Results: In total, 1645 DElncRNAs, 117 DEmiRNAs, and 2729 DEmRNAs were identified in LUAD. The LUAD-specific ceRNA network was composed of 157 nodes and 378 edges (329 DElncRNA-DEmiRNA interactions and 49 DEmiRNA-DEmRNA interactions). GO and KEGG pathway annotations suggested that the LUAD-specific ceRNA network was related to tumor-related molecular functions and pathways. Seven lncRNAs (DISC1-IT1, SYNPR-AS1, H19, LINC00460, LINC00518, DSCR10, and STEAP2-AS1), one miRNA (hsa-mir-31), and 16 mRNAs (ATAD2, OSCAR, KIF23, E2F7, PFKP, MCM4, CEP55, CBX2, CCNE1, CLSPN, CCNB1, CDC25A, EZH2, CHEK1, SLC7A11, and PBK) were revealed to be significantly correlated with overall survival.

Conclusion: In this study, we described the potential regulatory mechanism of the progression of LUAD. We proposed a new lncRNA-miRNA-mRNA ceRNA network that could help further explore the molecular mechanisms of LUAD.

Keywords: bioinformatics; competitive endogenous RNA; long non-coding RNAs; lung adenocarcinoma; prognosis.