Genomics and Prognosis Analysis of N6-Methyladenosine Regulators in Lung Adenocarcinoma

Objective: N6-methyladenosine (m6A) modification is involved in modulating various biological processes in human cancers. But the implication of m6A modification in lung adenocarcinoma (LUAD) is still unclear. Hence, this study conducted a comprehensive analysis of the expression and clinical implication of m6A regulators in LUAD.

Methods: Consensus clustering analysis of 502 LUAD samples in the TCGA dataset was presented based on the expression profiles of 20 m6A regulators using ConsensusClusterPlus package. Overall survival (OS), activation of signaling pathways and tumor immunity (immune/stromal score, tumor purity, expression of HLA and immune checkpoints, and immune cell infiltration) were compared between m6A modification patterns. The m6A-related genes between patterns were identified and prognostic m6A-related genes were imported into LASSO-cox regression analysis. The m6A risk score was developed and its prognostic implication was evaluated and externally verified in the GSE30219 and GSE72094 dataset. Furthermore, a nomogram that contained independent prognostic indicators was established, followed by external verification.

Results: Two m6A modification patterns were clustered across LUAD based on the expression similarity of the m6A regulators via consensus clustering analysis, with distinct OS, activation of signaling pathways and tumor immunity. Totally, 213 m6A-related genes that were identified by comparing two patterns were significantly related to LUAD prognosis. By LASSO method, we constructed the m6A risk score that was a reliable and independent prognostic factor for LUAD. Patients with low m6A risk score displayed a prominent survival advantage. After incorporating independent clinical features, we developed the prognostic nomogram that exhibited high predictive accuracy and the best clinical net benefit for OS.

Conclusion: Collectively, our study may provide a clinically useful tool for precise prognostic management and optimization of immunotherapeutic strategies for LUAD patients.