Revealing potential long non-coding RNA biomarkers in lung adenocarcinoma using long non-coding RNA-mediated competitive endogenous RNA network.

ABSTRACT: In our study, we aimed to reveal potential long non-coding RNAs (lncRNA) biomarkers in lung adenocarcinoma (LAD) using lncRNA-mediated competing endogenous RNAs (ceRNAs) network (LMCN). Competing lncRNA-mRNA interactions were identified using the hypergeometric test. Co-expression analysis for the competing lncRNA-mRNA interactions was implemented, and relying on the weight value >0.8, a highly competitive LMCN was further constructed. Degree distribution, betweenness and closeness for LMCN were carried out to analyze the network structure. Functional analyses of mRNAs in LMCN were carried out to further explore the biological functions of lncRNAs. Biclique algorithm was utilized to extract competing modules from the LMCN. Finally, we verified our findings in an independent sample set usin

SUBMITTER: Zhu TG 

PROVIDER: S-EPMC5572850 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature