AUTHOR=Yuan Baowen , Qin Hao , Zhang Jingyao , Zhang Min , Yang Yunkai , Teng Xu , Yu Hefen , Huang Wei , Wang Yan TITLE=m6A regulators featured by tumor immune microenvironment landscapes and correlated with immunotherapy in non-small cell lung cancer (NSCLC) JOURNAL=Frontiers in Oncology VOLUME=12 YEAR=2022 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.1087753 DOI=10.3389/fonc.2022.1087753 ISSN=2234-943X ABSTRACT=Introduction

Recent research has confirmed the critical role that epigenetic factors play in regulating the immune response. Nonetheless, what role m6A methylation modification might play in the immune response of non-small cell lung cancer (NSCLC) remains vague.

Methods

Herein, the gene expression, copy number variations (CNVs), and somatic mutations of 31 m6A regulators in NSCLC and adjacent control samples from the GEO and TCGA databases were comprehensively explored. Using consensus clustering, m6A modification patterns were identified. Correlations between m6A modification patterns and immune cell infiltration traits in the tumor immune microenvironment (TME) were systematically analyzed. Differentially expressed genes were verified and screened by random forest and cox regression analysis by comparing different m6A modification patterns. Based on the retained gene panel, a risk model was built, and m6Ascore for each sample was calculated. The function of m6Ascore in NSCLC prognosis, tumor somatic mutations, and chemotherapy/immunotherapy response prediction were evaluated.

Results

Consensus clustering classified all NSCLC samples into two m6A clusters (m6A_clusterA and m6A_clusterB) according to the expression levels of 25 m6A regulator genes. Hierarchical clustering further divides the NSCLC samples into two m6A gene clusters: m6AgeneclusterA and m6AgeneclusterB. A panel of 83 genes was screened from the 194 differentially expressed genes between m6A gene clusters. Based on this, a risk score model was established. m6A modification clusters, m6A gene clusters, and m6Ascore calculated from the risk model were able to predict tumor stages, immune cell infiltration, clinical prognosis, and tumor somatic mutations. NSCLC patients with high m6Ascore have poor drug resistance to chemotherapy drugs (Cisplatin and Gemcitabine) and exhibit considerable therapeutic benefits and favorable clinical responses to anti-PD1 or anti-CTLA4 immunotherapy.

Discussion

In conclusion, methylation modification patterns mediated by the m6A regulators in individuals play a non-negligible role in prognosis prediction and immunotherapy response, which will facilitate personalized treatment and immunotherapeutic strategies for NSCLC patients in the future.