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Comprehensive analysis of m(6)A/m(5)C/m(1)A-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma

This research aims to develop a prognostic glioma marker based on m(6)A/m(5)C/m(1)A genes and investigate the potential role in the tumor immune microenvironment. Data for patients with glioma were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). The expression...

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Autores principales: Zhao, Kai, Li, Wenhu, Yang, Yongtao, Hu, Xinyue, Dai, Ying, Huang, Minhao, Luo, Ji, Zhang, Kui, Zhao, Ninghui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9530704/
https://www.ncbi.nlm.nih.gov/pubmed/36203569
http://dx.doi.org/10.3389/fimmu.2022.955848
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author Zhao, Kai
Li, Wenhu
Yang, Yongtao
Hu, Xinyue
Dai, Ying
Huang, Minhao
Luo, Ji
Zhang, Kui
Zhao, Ninghui
author_facet Zhao, Kai
Li, Wenhu
Yang, Yongtao
Hu, Xinyue
Dai, Ying
Huang, Minhao
Luo, Ji
Zhang, Kui
Zhao, Ninghui
author_sort Zhao, Kai
collection PubMed
description This research aims to develop a prognostic glioma marker based on m(6)A/m(5)C/m(1)A genes and investigate the potential role in the tumor immune microenvironment. Data for patients with glioma were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). The expression of genes related to m(6)A/m(5)C/m(1)A was compared for normal and glioma groups. Gene Ontology and Kyoto Encyclopedia of Genes and Gene enrichment analysis of differentially expressed genes were conducted. Consistent clustering analysis was performed to obtain glioma subtypes and complete the survival analysis and immune analysis. Based on TCGA, Lasso regression analysis was used to obtain a prognostic model, and the CGGA database was used to validate the model. The model-based risk scores and the hub genes with the immune microenvironment, clinical features, and antitumor drug susceptibility were investigated. The clinical glioma tissues were collected to verify the expression of hub genes via immunohistochemistry. Twenty genes were differentially expressed, Consensus cluster analysis identified two molecular clusters. Overall survival was significantly higher in cluster 2 than in cluster 1. Immunological analysis revealed statistically significant differences in 26 immune cells and 17 immune functions between the two clusters. Enrichment analysis detected multiple meaningful pathways. We constructed a prognostic model that consists of WTAP, TRMT6, DNMT1, and DNMT3B. The high-risk and low-risk groups affected the survival prognosis and immune infiltration, which were related to grade, gender, age, and survival status. The prognostic value of the model was validated using another independent cohort CGGA. Clinical correlation and immune analysis revealed that four hub genes were associated with tumor grade, immune cells, and antitumor drug sensitivity, and WTAP was significantly associated with microsatellite instability(MSI). Immunohistochemistry confirmed the high expression of WTAP, DNMT1, and DNMT3B in tumor tissue, but the low expression of TRMT6. This study established a strong prognostic marker based on m(6)A/m(5)C/m(1)A methylation regulators, which can accurately predict the prognosis of patients with gliomas. m(6)A/m(5)C/m(1)A modification mode plays an important role in the tumor microenvironment, can provide valuable information for anti-tumor immunotherapy, and have a profound impact on the clinical characteristics.
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spelling pubmed-95307042022-10-05 Comprehensive analysis of m(6)A/m(5)C/m(1)A-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma Zhao, Kai Li, Wenhu Yang, Yongtao Hu, Xinyue Dai, Ying Huang, Minhao Luo, Ji Zhang, Kui Zhao, Ninghui Front Immunol Immunology This research aims to develop a prognostic glioma marker based on m(6)A/m(5)C/m(1)A genes and investigate the potential role in the tumor immune microenvironment. Data for patients with glioma were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). The expression of genes related to m(6)A/m(5)C/m(1)A was compared for normal and glioma groups. Gene Ontology and Kyoto Encyclopedia of Genes and Gene enrichment analysis of differentially expressed genes were conducted. Consistent clustering analysis was performed to obtain glioma subtypes and complete the survival analysis and immune analysis. Based on TCGA, Lasso regression analysis was used to obtain a prognostic model, and the CGGA database was used to validate the model. The model-based risk scores and the hub genes with the immune microenvironment, clinical features, and antitumor drug susceptibility were investigated. The clinical glioma tissues were collected to verify the expression of hub genes via immunohistochemistry. Twenty genes were differentially expressed, Consensus cluster analysis identified two molecular clusters. Overall survival was significantly higher in cluster 2 than in cluster 1. Immunological analysis revealed statistically significant differences in 26 immune cells and 17 immune functions between the two clusters. Enrichment analysis detected multiple meaningful pathways. We constructed a prognostic model that consists of WTAP, TRMT6, DNMT1, and DNMT3B. The high-risk and low-risk groups affected the survival prognosis and immune infiltration, which were related to grade, gender, age, and survival status. The prognostic value of the model was validated using another independent cohort CGGA. Clinical correlation and immune analysis revealed that four hub genes were associated with tumor grade, immune cells, and antitumor drug sensitivity, and WTAP was significantly associated with microsatellite instability(MSI). Immunohistochemistry confirmed the high expression of WTAP, DNMT1, and DNMT3B in tumor tissue, but the low expression of TRMT6. This study established a strong prognostic marker based on m(6)A/m(5)C/m(1)A methylation regulators, which can accurately predict the prognosis of patients with gliomas. m(6)A/m(5)C/m(1)A modification mode plays an important role in the tumor microenvironment, can provide valuable information for anti-tumor immunotherapy, and have a profound impact on the clinical characteristics. Frontiers Media S.A. 2022-09-20 /pmc/articles/PMC9530704/ /pubmed/36203569 http://dx.doi.org/10.3389/fimmu.2022.955848 Text en Copyright © 2022 Zhao, Li, Yang, Hu, Dai, Huang, Luo, Zhang and Zhao 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 Immunology
Zhao, Kai
Li, Wenhu
Yang, Yongtao
Hu, Xinyue
Dai, Ying
Huang, Minhao
Luo, Ji
Zhang, Kui
Zhao, Ninghui
Comprehensive analysis of m(6)A/m(5)C/m(1)A-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma
title Comprehensive analysis of m(6)A/m(5)C/m(1)A-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma
title_full Comprehensive analysis of m(6)A/m(5)C/m(1)A-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma
title_fullStr Comprehensive analysis of m(6)A/m(5)C/m(1)A-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma
title_full_unstemmed Comprehensive analysis of m(6)A/m(5)C/m(1)A-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma
title_short Comprehensive analysis of m(6)A/m(5)C/m(1)A-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma
title_sort comprehensive analysis of m(6)a/m(5)c/m(1)a-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9530704/
https://www.ncbi.nlm.nih.gov/pubmed/36203569
http://dx.doi.org/10.3389/fimmu.2022.955848
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