Contributions and prognostic values of m6A RNA methylation regulators in non‐small‐cell lung cancer. Issue 9 (13th February 2020)

• Record Type: Journal Article
• Authors: Liu, Yang; Guo, Xiuchen; Zhao, Meng; Ao, Haijiao; Leng, Xue; Liu, Mingdong; Wu, Caixia; Ma, Jianqun; Zhu, Jinhong
• Is Part Of: Journal of cellular physiology. Volume 235:Issue 9(2020:Sep.)
• Page Start: 6043
• Page End: 6057
• Publication Date: 2020-02-13
• Subjects: consensus clustering -- gene signature -- m6A RNA methylation -- NSCLC -- prognosis; Physiology -- Periodicals; Cell physiology -- Periodicals; 571.6
• DOI: 10.1002/jcp.29531
• Languages: English
• ISSNs: 0021-9541

Abstract

Abstract: N6‐methyladenosine (m 6 A) RNA modification can alter gene expression and function by regulating RNA splicing, stability, translocation, and translation. Deregulation of m 6 A has been involved in various types of cancer. However, its implications in non‐small‐cell lung cancer (NSCLC) are mostly unknown. This posttranscriptional modification is dynamically and reversibly mediated by different regulators, including methyltransferase, demethylases, and m 6 A binding proteins. In this study, we comprehensively investigated the contributions and prognostic values of 13 common m 6 A RNA modification regulators using The Cancer Genome Atlas database. We found that the expression levels of most of the studied genes were significantly altered in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Using consensus clustering, the gene‐expression profiles of 13 m 6 A regulators could classify patients with LUAD into two subgroups with significantly distinct clinical outcomes, but not the LUSC cohort or the combination of the two cohorts. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analysis were applied to explore differential signaling pathways and cellular processes between the two LUAD subgroups. Moreover, we found that this gene‐expression signature could better predict prognosis in the late‐stage (III + IV) than in the early‐stage (I + II) LUAD. Finally, we developed an optimal prognostic gene signature by using the least absolute shrinkage and selection operator Cox regression algorithm and compute risk score. In conclusion, our study unveiled the implication of m 6 A RNA modification regulators in NSCLC and identified the m 6 A gene expression classifiers for predicting the prognosis of NSCLC. Abstract : In this study, we comprehensively investigated the contribution and prognostic values of 13 common N6‐methyladenosine (m 6 A) RNA modification regulators using The Cancer Genome Atlas database. Using consensus clustering, the gene‐expression profiles of 13 m 6 A regulators could classify patients with lung adenocarcinoma into two subgroups with significantly distinct clinical outcomes. Moreover, we further optimized the prognostic model by using the least absolute shrinkage and selection operator Cox regression algorithm to compute risk score.