Comprehensive Analysis of the Function, Immune Profiles, and Clinical Implication of m1A Regulators in Lung Adenocarcinoma - Bao, Guangyao; Li, Tian; Guan, Xiaojiao; Yao, Yao; Liang, Jie; Xiang, Yifang; Zhong, Xinwen (Frontiers in Oncology, 2022)
Background Previous studies have demonstrated that transcriptional RNA methyladenosine modification significantly affects tumor initiation and progression. However, clinical implications of N1-methyladenosine (m1A) regulators and their effect on tumor immunity in lung adenocarcinoma (LUAD) are still poorly elucidated. Methods Herein, the characteristics of somatic mutation, copy number variation (CNV), DNA methylation, and expression levels of m1A regulators were thoroughly analyzed. We classified 955 lung adenocarcinoma patients into different m1A modification patterns based on an unsupervised consensus clustering algorithm. We then calculated the differences in gene expression, prognosis outcomes, and immune profiles among different m1A clusters. Subsequently, we screened differently expressed genes (DEGs) related to prognosis among different m1A clusters. We identified m1A related gene clusters according to the prognosis-related different expressed genes. We further constructed a scoring standard named the m1A score and comprehensively analyzed the survival outcomes, clinical-pathological features, immune microenvironment, treatment responses of immunotherapy, and drug susceptibility in different m1A score groups. Results In total, three different m1A modification patterns were identified, which contained cluster A, B, and C. Among them, cluster A processed the poorest clinical outcomes, the lowest immune cell infiltration rate, and the highest tumor purity score. Then, three m1A gene clusters (gene cluster A, B, C) were speculated. Subsequently, we combined m1A modification patterns and m1A gene cluster to classify lung adenocarcinoma patients into high and low m1A score groups. The low m1A score group was accompanied by higher mortality, higher tumor mutation burden (TMB) and genome mutation frequency, and lower programmed cell death-Ligand 1 (PD-L1) expression and tumor immune dysfunction and exclusion (TIDE) expression. Moreover, the m1A score exhibited positive correlation with almost all immune cells. Finally, common chemotherapeutic and targeted therapy agents exhibited obvious differences in drug susceptibility in different m1A score groups. Conclusions Collectively, we explored the potential value of m1A regulators in the prognosis and treatment of lung adenocarcinoma in multiple dimensions and provided some preliminary basis for the follow-up study of m1A regulators in lung adenocarcinoma.