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Classification of pediatric gliomas based on immunological profiling: implications for immunotherapy strategies

Pediatric gliomas (PGs) are the most common brain tumors in children and the leading cause of childhood cancer-related death. The understanding of the immune microenvironment is essential for developing effective antitumor immunotherapies. Transcriptomic data from 495 PGs were analyzed in this study...

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Autores principales: Wang, Zihao, Guo, Xiaopeng, Gao, Lu, Wang, Yu, Guo, Yi, Xing, Bing, Ma, Wenbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society of Gene & Cell Therapy 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7851498/
https://www.ncbi.nlm.nih.gov/pubmed/33575469
http://dx.doi.org/10.1016/j.omto.2020.12.012
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author Wang, Zihao
Guo, Xiaopeng
Gao, Lu
Wang, Yu
Guo, Yi
Xing, Bing
Ma, Wenbin
author_facet Wang, Zihao
Guo, Xiaopeng
Gao, Lu
Wang, Yu
Guo, Yi
Xing, Bing
Ma, Wenbin
author_sort Wang, Zihao
collection PubMed
description Pediatric gliomas (PGs) are the most common brain tumors in children and the leading cause of childhood cancer-related death. The understanding of the immune microenvironment is essential for developing effective antitumor immunotherapies. Transcriptomic data from 495 PGs were analyzed in this study, with 384 as a training cohort and 111 as a validation cohort. Macrophages were the most common immune infiltrates in the PG microenvironment, followed by T cells. PGs were classified into 3 immune subtypes (ISs) based on immunological profiling: “immune hot” (IS-I), “immune altered” (IS-II), and “immune cold” (IS-III). IS-I tumors, characterized by substantial immune infiltration and high immune checkpoint molecule (ICM) expression, had a favorable prognosis and were more likely to respond to anti-PD1 and anti-CTLA4 immunotherapies, whereas IS-III tumors, characterized by weak immune infiltration and low ICM expression, had a dismal prognosis and poor immunotherapy responsiveness. IS-II tumors represented a transitional stage. Immune classification was also correlated with somatic mutations, copy number alterations, and molecular pathways related to tumorigenesis, metabolism, and immune responses. Three predictive classifiers using eight representative genes were generated by machine learning methods for immune classification. This study established a reliable immunological profile-based classification system for PGs, providing implications for further immunotherapy strategies.
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spelling pubmed-78514982021-02-10 Classification of pediatric gliomas based on immunological profiling: implications for immunotherapy strategies Wang, Zihao Guo, Xiaopeng Gao, Lu Wang, Yu Guo, Yi Xing, Bing Ma, Wenbin Mol Ther Oncolytics Original Article Pediatric gliomas (PGs) are the most common brain tumors in children and the leading cause of childhood cancer-related death. The understanding of the immune microenvironment is essential for developing effective antitumor immunotherapies. Transcriptomic data from 495 PGs were analyzed in this study, with 384 as a training cohort and 111 as a validation cohort. Macrophages were the most common immune infiltrates in the PG microenvironment, followed by T cells. PGs were classified into 3 immune subtypes (ISs) based on immunological profiling: “immune hot” (IS-I), “immune altered” (IS-II), and “immune cold” (IS-III). IS-I tumors, characterized by substantial immune infiltration and high immune checkpoint molecule (ICM) expression, had a favorable prognosis and were more likely to respond to anti-PD1 and anti-CTLA4 immunotherapies, whereas IS-III tumors, characterized by weak immune infiltration and low ICM expression, had a dismal prognosis and poor immunotherapy responsiveness. IS-II tumors represented a transitional stage. Immune classification was also correlated with somatic mutations, copy number alterations, and molecular pathways related to tumorigenesis, metabolism, and immune responses. Three predictive classifiers using eight representative genes were generated by machine learning methods for immune classification. This study established a reliable immunological profile-based classification system for PGs, providing implications for further immunotherapy strategies. American Society of Gene & Cell Therapy 2020-12-25 /pmc/articles/PMC7851498/ /pubmed/33575469 http://dx.doi.org/10.1016/j.omto.2020.12.012 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Wang, Zihao
Guo, Xiaopeng
Gao, Lu
Wang, Yu
Guo, Yi
Xing, Bing
Ma, Wenbin
Classification of pediatric gliomas based on immunological profiling: implications for immunotherapy strategies
title Classification of pediatric gliomas based on immunological profiling: implications for immunotherapy strategies
title_full Classification of pediatric gliomas based on immunological profiling: implications for immunotherapy strategies
title_fullStr Classification of pediatric gliomas based on immunological profiling: implications for immunotherapy strategies
title_full_unstemmed Classification of pediatric gliomas based on immunological profiling: implications for immunotherapy strategies
title_short Classification of pediatric gliomas based on immunological profiling: implications for immunotherapy strategies
title_sort classification of pediatric gliomas based on immunological profiling: implications for immunotherapy strategies
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7851498/
https://www.ncbi.nlm.nih.gov/pubmed/33575469
http://dx.doi.org/10.1016/j.omto.2020.12.012
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