Characterization of m 6 A RNA Methylation Regulators Predicts Survival and Immunotherapy in Lung Adenocarcinoma

• Published in: Frontiers in immunology Vol. 12; p. 782551
• Main Authors: Zhu, Minggao, Cui, Yachao, Mo, Qi, Zhang, Junwei, Zhao, Ting, Xu, Yujie, Wu, Zhenpeng, Sun, Donglin, Zhang, Xiaoren, Li, Yingchang, You, Qiang
• Format: Journal Article
• Language: English
• Published: Switzerland 2021
• Subjects: Adenocarcinoma of Lung - diagnosis; Adenocarcinoma of Lung - genetics; Adenocarcinoma of Lung - mortality; Adenocarcinoma of Lung - therapy; Adenosine - analogs & derivatives; Biomarkers, Tumor; Computational Biology - methods; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Humans; Immunomodulation; Immunotherapy; Kaplan-Meier Estimate; Methylation; Models, Biological; Mutation; Neoplasm Grading; Neoplasm Staging; Prognosis; RNA, Messenger - genetics; RNA, Messenger - metabolism; Treatment Outcome; tumor mutation burden; immunotherapy; lung adenocarcinoma; radiotherapy; tumor-infiltrating immune cells; m6A; tumor microenvironment
• ISSN: 1664-3224

N
-methyladenosine (m
A) RNA modification is a reversible mechanism that regulates eukaryotic gene expression. Growing evidence has demonstrated an association between m
A modification and tumorigenesis and response to immunotherapy. However, the overall influence of m
A regulators on the tumor microenvironment and their effect on the response to immunotherapy in lung adenocarcinoma remains to be explored. Here, we comprehensively analyzed the m
A modification patterns of 936 lung adenocarcinoma samples based on 24 m
A regulators. First, we described the features of genetic variation in these m
A regulators. Many m
A regulators were aberrantly expressed in tumors and negatively correlated with most tumor-infiltrating immune cell types. Furthermore, we identified three m
A modification patterns using a consensus clustering method. m
A cluster B was preferentially associated with a favorable prognosis and enriched in metabolism-associated pathways. In contrast, m
A cluster A was associated with the worst prognosis and was enriched in the process of DNA repair. m
A cluster C was characterized by activation of the immune system and a higher stromal cell score. Surprisingly, patients who received radiotherapy had a better prognosis than patients without radiotherapy only in the m
A cluster C group. Subsequently, we constructed an m
A score model that qualified the m
A modification level of individual samples by using principal component analysis algorithms. Patients with high m
A score were characterized by enhanced immune cell infiltration and prolonged survival time and were associated with lower tumor mutation burden and PD-1/CTLA4 expression. The combination of the m
A score and tumor mutation burden could accurately predict the prognosis of patients with lung adenocarcinoma. Furthermore, patients with high m
A score exhibited greater prognostic benefits from radiotherapy and immunotherapy. This study demonstrates that m
A modification is significantly associated with tumor microenvironment diversity and prognosis. A comprehensive evaluation of m
A modification patterns in single tumors will expand our understanding of the tumor immune landscape. In addition, our m
A score model demonstrated that the level of immune cell infiltration plays a significant role in cancer immunotherapy and provides a basis to increase the efficiency of current immune therapies and promote the clinical success of immunotherapy.