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m(6)A regulators featured by tumor immune microenvironment landscapes and correlated with immunotherapy in non-small cell lung cancer (NSCLC)

INTRODUCTION: Recent research has confirmed the critical role that epigenetic factors play in regulating the immune response. Nonetheless, what role m(6)A methylation modification might play in the immune response of non-small cell lung cancer (NSCLC) remains vague. METHODS: Herein, the gene express...

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Autores principales: Yuan, Baowen, Qin, Hao, Zhang, Jingyao, Zhang, Min, Yang, Yunkai, Teng, Xu, Yu, Hefen, Huang, Wei, Wang, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9800857/
https://www.ncbi.nlm.nih.gov/pubmed/36591468
http://dx.doi.org/10.3389/fonc.2022.1087753
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author Yuan, Baowen
Qin, Hao
Zhang, Jingyao
Zhang, Min
Yang, Yunkai
Teng, Xu
Yu, Hefen
Huang, Wei
Wang, Yan
author_facet Yuan, Baowen
Qin, Hao
Zhang, Jingyao
Zhang, Min
Yang, Yunkai
Teng, Xu
Yu, Hefen
Huang, Wei
Wang, Yan
author_sort Yuan, Baowen
collection PubMed
description INTRODUCTION: Recent research has confirmed the critical role that epigenetic factors play in regulating the immune response. Nonetheless, what role m(6)A 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 m(6)A regulators in NSCLC and adjacent control samples from the GEO and TCGA databases were comprehensively explored. Using consensus clustering, m(6)A modification patterns were identified. Correlations between m(6)A 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 m(6)A modification patterns. Based on the retained gene panel, a risk model was built, and m(6)Ascore for each sample was calculated. The function of m(6)Ascore in NSCLC prognosis, tumor somatic mutations, and chemotherapy/immunotherapy response prediction were evaluated. RESULTS: Consensus clustering classified all NSCLC samples into two m(6)A clusters (m(6)A_clusterA and m(6)A_clusterB) according to the expression levels of 25 m(6)A regulator genes. Hierarchical clustering further divides the NSCLC samples into two m(6)A gene clusters: m(6)AgeneclusterA and m(6)AgeneclusterB. A panel of 83 genes was screened from the 194 differentially expressed genes between m(6)A gene clusters. Based on this, a risk score model was established. m(6)A modification clusters, m(6)A gene clusters, and m(6)Ascore calculated from the risk model were able to predict tumor stages, immune cell infiltration, clinical prognosis, and tumor somatic mutations. NSCLC patients with high m(6)Ascore 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 m(6)A 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.
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spelling pubmed-98008572022-12-31 m(6)A regulators featured by tumor immune microenvironment landscapes and correlated with immunotherapy in non-small cell lung cancer (NSCLC) Yuan, Baowen Qin, Hao Zhang, Jingyao Zhang, Min Yang, Yunkai Teng, Xu Yu, Hefen Huang, Wei Wang, Yan Front Oncol Oncology INTRODUCTION: Recent research has confirmed the critical role that epigenetic factors play in regulating the immune response. Nonetheless, what role m(6)A 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 m(6)A regulators in NSCLC and adjacent control samples from the GEO and TCGA databases were comprehensively explored. Using consensus clustering, m(6)A modification patterns were identified. Correlations between m(6)A 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 m(6)A modification patterns. Based on the retained gene panel, a risk model was built, and m(6)Ascore for each sample was calculated. The function of m(6)Ascore in NSCLC prognosis, tumor somatic mutations, and chemotherapy/immunotherapy response prediction were evaluated. RESULTS: Consensus clustering classified all NSCLC samples into two m(6)A clusters (m(6)A_clusterA and m(6)A_clusterB) according to the expression levels of 25 m(6)A regulator genes. Hierarchical clustering further divides the NSCLC samples into two m(6)A gene clusters: m(6)AgeneclusterA and m(6)AgeneclusterB. A panel of 83 genes was screened from the 194 differentially expressed genes between m(6)A gene clusters. Based on this, a risk score model was established. m(6)A modification clusters, m(6)A gene clusters, and m(6)Ascore calculated from the risk model were able to predict tumor stages, immune cell infiltration, clinical prognosis, and tumor somatic mutations. NSCLC patients with high m(6)Ascore 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 m(6)A 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. Frontiers Media S.A. 2022-12-16 /pmc/articles/PMC9800857/ /pubmed/36591468 http://dx.doi.org/10.3389/fonc.2022.1087753 Text en Copyright © 2022 Yuan, Qin, Zhang, Zhang, Yang, Teng, Yu, Huang and Wang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Yuan, Baowen
Qin, Hao
Zhang, Jingyao
Zhang, Min
Yang, Yunkai
Teng, Xu
Yu, Hefen
Huang, Wei
Wang, Yan
m(6)A regulators featured by tumor immune microenvironment landscapes and correlated with immunotherapy in non-small cell lung cancer (NSCLC)
title m(6)A regulators featured by tumor immune microenvironment landscapes and correlated with immunotherapy in non-small cell lung cancer (NSCLC)
title_full m(6)A regulators featured by tumor immune microenvironment landscapes and correlated with immunotherapy in non-small cell lung cancer (NSCLC)
title_fullStr m(6)A regulators featured by tumor immune microenvironment landscapes and correlated with immunotherapy in non-small cell lung cancer (NSCLC)
title_full_unstemmed m(6)A regulators featured by tumor immune microenvironment landscapes and correlated with immunotherapy in non-small cell lung cancer (NSCLC)
title_short m(6)A regulators featured by tumor immune microenvironment landscapes and correlated with immunotherapy in non-small cell lung cancer (NSCLC)
title_sort m(6)a regulators featured by tumor immune microenvironment landscapes and correlated with immunotherapy in non-small cell lung cancer (nsclc)
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9800857/
https://www.ncbi.nlm.nih.gov/pubmed/36591468
http://dx.doi.org/10.3389/fonc.2022.1087753
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