N‐6 methylation‐related lncRNA is potential signature in lung adenocarcinoma and influences tumor microenvironment. Issue 11 (24th September 2021) - Zheng, Jian; Zhao, Zhuochen; Wan, Junhu; Guo, Manman; Wang, Yangxia; Yang, Zhengwu; Li, Zhuofang; Ming, Liang; Qin, Zhaobing
Abstract: Background: N‐6 methylation (m6A) pushes forward an immense influence on the occurrence and development of lung adenocarcinoma (LUAD). However, the methylation on non‐coding RNA in LUAD, especially long non‐coding RNA (lncRNA), has not been received sufficient attention. Methods: Spearman correlation analysis was used to screen lncRNA correlated with m6A regulators expression from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repositories, respectively. Then, the least absolute shrinkage and selection operator (LASSO) was applied to build a risk signature consisting m6A‐related lncRNA. Univariate and multivariate independent prognostic analysis were applied to evaluate the performance of signature in predicting patients' survival. Next, we applied Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) to conduct pathway enrichment analysis of 3344 different expression genes (DEGs). Finally, we set up a competing endogenous RNAs (ceRNA) network to this lncRNA. Results: A total of 85 common lncRNAs were selected to acquire the components related to prognosis. The final risk signature established by LASSO regression contained 11 lncRNAs: ARHGEF26‐AS1, COLCA1, CRNDE, DLGAP1‐AS2, FENDRR, LINC00968, TMPO‐AS1, TRG‐AS1, MGC32805, RPARP‐AS1, and TBX5‐AS1. M6A‐related lncRNA risk score could predict the prognostic of LUAD and was significantly associated with clinical pathological. And in the evaluation of lung adenocarcinoma tumor microenvironment (TME) by using ESTIMATE algorithm, we found a statistically significant correlation between risk score and stromal/immune cells. Conclusion: M6A‐related lncRNA was a potential prognostic and therapy target for lung adenocarcinoma. Abstract : In this study, we further explored the role of m6A‐related long non‐coding RNA in lung adenocarcinoma. First, we found the lncRNAs related to m6A from TCGA and GEO repositories by Pearson correlation analysis. Then, we established a risk model by using LASSO method and comprehensively expounded the potential role of m6A‐related lncRNAs in lung adenocarcinoma from the aspects of prognosis verification, clinical characteristics, tumor microenvironment, and molecular mechanism.