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Genomics and Prognosis Analysis of N(6)-Methyladenosine Regulators in Lung Adenocarcinoma

Objective: N(6)-methyladenosine (m(6)A) modification is involved in modulating various biological processes in human cancers. But the implication of m(6)A modification in lung adenocarcinoma (LUAD) is still unclear. Hence, this study conducted a comprehensive analysis of the expression and clinical...

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Detalles Bibliográficos
Autores principales: Ma, Yanpin, Zhang, Huping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8697852/
https://www.ncbi.nlm.nih.gov/pubmed/34956315
http://dx.doi.org/10.3389/fgene.2021.746666
Descripción
Sumario:Objective: N(6)-methyladenosine (m(6)A) modification is involved in modulating various biological processes in human cancers. But the implication of m(6)A modification in lung adenocarcinoma (LUAD) is still unclear. Hence, this study conducted a comprehensive analysis of the expression and clinical implication of m(6)A regulators in LUAD. Methods: Consensus clustering analysis of 502 LUAD samples in the TCGA dataset was presented based on the expression profiles of 20 m(6)A 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 m(6)A modification patterns. The m(6)A-related genes between patterns were identified and prognostic m(6)A-related genes were imported into LASSO-cox regression analysis. The m(6)A 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 m(6)A modification patterns were clustered across LUAD based on the expression similarity of the m(6)A regulators via consensus clustering analysis, with distinct OS, activation of signaling pathways and tumor immunity. Totally, 213 m(6)A-related genes that were identified by comparing two patterns were significantly related to LUAD prognosis. By LASSO method, we constructed the m(6)A risk score that was a reliable and independent prognostic factor for LUAD. Patients with low m(6)A 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.