Comprehensive Analysis of Gene Signatures of m6ARNA Methylation Regulators in Lung Adenocarcinoma and Development of a Risk Scoring System. (23rd August 2022)

• Record Type: Journal Article
• Authors: Gao, Chundi; Li, Huayao; Ma, Wenzhe; Zhang, Qiming; Liu, Cun; Liu, Lijuan; Zhuang, Jing; Sun, Changgang
• Other Names: Shang An-Quan Academic Editor.
• Is Part Of: Journal of immunology research. Volume 2022(2022)
• Publication Date: 2022-08-23
• Subjects: Immunology -- Periodicals; Immunology -- Research -- Periodicals; 616.07905
• DOI: 10.1155/2022/7519838
• Languages: English
• ISSNs: 2314-8861

Abstract

Abstract : The recent application of targeted immunotherapy has greatly improved the clinical outcomes of patients with lung adenocarcinoma (LUAD), but drug resistance continues to emerge, and to evaluate and to improve patient prognosis are arduous. The diagnostic and prognostic value of N6-methyladenosine (M6A) in LUAD has attracted increasing attention. We systematically studied correlations among important M6A methylation regulators, tumor mutational burden (TMB), and immune infiltration in clinical and sequencing data from the LUAD cohort of the cancer genome map (TCGA). The molecular subtype clusters 1 and 2 were identified by the consensus clustering of 16 M6A regulatory factors. Clinical prognosis, M6A regulatory factor expression, TMB, pathway enrichment, and immune cell infiltration significantly differed between clusters 1 and 2. Compared with other clinical traits, a prognostic risk score system constructed using the M6A regulatory factors HNRNPA2B1 and HNRNPC can serve as an independent prognostic method for LUAD, with higher predictive sensitivity and specificity. Risk scores were significantly higher for cluster 2 than 1, which was consistent with the trend towards a better prognosis in cluster 1. Overall, our findings revealed an important role of M6A methylation regulators in LUAD, and our risk scoring system involving these regulators might help to screen groups at high risk for LUAD and provide important theoretical bioinformatic support for evaluating the prognosis of such patients.