Yongfei Fan1, Yong Zhou1, Ming Lou1, Xinwei Li2, Xudong Zhu1, Kai Yuan1,3. 1. Department of Thoracic Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, People's Republic of China. 2. Department of Gastroenterology, Affiliated Cancer Hospital of Bengbu Medical College, Bengbu, People's Republic of China. 3. Heart and Lung Disease Laboratory, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, People's Republic of China.
Abstract
Purpose: The role of RNA N6-methyladenosine (m6A) modification in the progression of multiple tumours and the tumour microenvironment (TME) has been progressively demonstrated and promises a new direction for tumour therapy. However, there have been no reports on systematic analyses of RNA m6A modification in TME in non-small cell lung cancer (NSCLC). Patients and Methods: In this study, we used unsupervised cluster analysis to identify three m6A modification patterns of 28 m6A regulators and three m6A gene signature subgroups of commonly differentially expressed genes (co-DEGs) in the three m6A modification patterns. Quantifying these subtypes using the ssGSEA and ESTIMATE algorithms to characterise the tumour immune microenvironment (TIME) in NSCLC. Based on the principal component analysis (PCA), we used co-DEGs to construct m6A scores to analyse the characteristics of m6A modifications in individual patients and assessed the practical clinical utility of m6A scores using a nomogram for survival prediction. Results: A total of 28 m6A regulators in 1210 NSCLC samples were mainly enriched in RNA modification and metabolic biological processes. The three following m6A modification patterns were identified based on the role of the 28 m6A regulators in TME: immune inflammation, immune evasion and immune desert. The m6A scores calculated based on co-DEGs in these modification patterns were significantly positively correlated with immune infiltration and significantly negatively correlated with tumour mutational burden (TMB). Survival was significantly better in the high-m6A-score group than in the low-m6A-score group, and the m6A score could be used as an independent favourable prognostic factor. In addition, assessment of both immune checkpoint inhibitors (ICIs) and immunophenoscore (IPS) revealed a better immunotherapeutic effect in the high-m6A-score group. Conclusion: The modification characteristics of 28 m6A regulators in the TIME of NSCLC were analysed from a comprehensive to an individual basis, which may facilitate the development of more effective clinical immunotherapeutic strategies.
Purpose: The role of RNA N6-methyladenosine (m6A) modification in the progression of multiple tumours and the tumour microenvironment (TME) has been progressively demonstrated and promises a new direction for tumour therapy. However, there have been no reports on systematic analyses of RNA m6A modification in TME in non-small cell lung cancer (NSCLC). Patients and Methods: In this study, we used unsupervised cluster analysis to identify three m6A modification patterns of 28 m6A regulators and three m6A gene signature subgroups of commonly differentially expressed genes (co-DEGs) in the three m6A modification patterns. Quantifying these subtypes using the ssGSEA and ESTIMATE algorithms to characterise the tumour immune microenvironment (TIME) in NSCLC. Based on the principal component analysis (PCA), we used co-DEGs to construct m6A scores to analyse the characteristics of m6A modifications in individual patients and assessed the practical clinical utility of m6A scores using a nomogram for survival prediction. Results: A total of 28 m6A regulators in 1210 NSCLC samples were mainly enriched in RNA modification and metabolic biological processes. The three following m6A modification patterns were identified based on the role of the 28 m6A regulators in TME: immune inflammation, immune evasion and immune desert. The m6A scores calculated based on co-DEGs in these modification patterns were significantly positively correlated with immune infiltration and significantly negatively correlated with tumour mutational burden (TMB). Survival was significantly better in the high-m6A-score group than in the low-m6A-score group, and the m6A score could be used as an independent favourable prognostic factor. In addition, assessment of both immune checkpoint inhibitors (ICIs) and immunophenoscore (IPS) revealed a better immunotherapeutic effect in the high-m6A-score group. Conclusion: The modification characteristics of 28 m6A regulators in the TIME of NSCLC were analysed from a comprehensive to an individual basis, which may facilitate the development of more effective clinical immunotherapeutic strategies.
Authors: Denise R Aberle; Amanda M Adams; Christine D Berg; William C Black; Jonathan D Clapp; Richard M Fagerstrom; Ilana F Gareen; Constantine Gatsonis; Pamela M Marcus; JoRean D Sicks Journal: N Engl J Med Date: 2011-06-29 Impact factor: 91.245
Authors: Freddie Bray; Jacques Ferlay; Isabelle Soerjomataram; Rebecca L Siegel; Lindsey A Torre; Ahmedin Jemal Journal: CA Cancer J Clin Date: 2018-09-12 Impact factor: 508.702
Authors: Dali Han; Jun Liu; Chuanyuan Chen; Lihui Dong; Yi Liu; Renbao Chang; Xiaona Huang; Yuanyuan Liu; Jianying Wang; Urszula Dougherty; Marc B Bissonnette; Bin Shen; Ralph R Weichselbaum; Meng Michelle Xu; Chuan He Journal: Nature Date: 2019-02-06 Impact factor: 49.962