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Positive regulators of T cell functions as predictors of prognosis and microenvironment characteristics of low-grade gliomas

BACKGROUND: Low-grade gliomas (LGG) are one of the most prevalent types of brain cancers. The efficacy of immunotherapy in LGG is limited compared to other cancers. Immunosuppression in the tumor microenvironment (TME) of LGG is one of the main reasons for the low efficacy of immunotherapy. Recent s...

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Autores principales: Li, Yang, Feng, Yabo, Luo, Fushu, Peng, Gang, Li, Yueran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885161/
https://www.ncbi.nlm.nih.gov/pubmed/36726969
http://dx.doi.org/10.3389/fimmu.2022.1089792
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author Li, Yang
Feng, Yabo
Luo, Fushu
Peng, Gang
Li, Yueran
author_facet Li, Yang
Feng, Yabo
Luo, Fushu
Peng, Gang
Li, Yueran
author_sort Li, Yang
collection PubMed
description BACKGROUND: Low-grade gliomas (LGG) are one of the most prevalent types of brain cancers. The efficacy of immunotherapy in LGG is limited compared to other cancers. Immunosuppression in the tumor microenvironment (TME) of LGG is one of the main reasons for the low efficacy of immunotherapy. Recent studies have identified 33 positive regulators of T cell functions (TPRs) that play a critical role in promoting the proliferation, activity, and functions of multiple immunocytes. However, their role in the TME of LGG has not been investigated. This study aimed to construct a risk model based on these TPRs and to detect the significance of immunotypes in predicting LGG prognosis and immunotherapy efficacy. METHODS: A total of 688 LGGs and 202 normal brain tissues were extracted from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Genotype-Tissue Expression (GTEx) databases. The NMF R package was used to identify TRP-related subtypes. The TPR prognostic model was established using the least absolute shrinkage and selection operator (LASSO) algorithm to predict the overall survival of LGG samples. RESULTS: The Subtype 2 patients had worse survival outcomes, suppressed immune function, and higher immune cell infiltration. A risk regression model consisting of 14 TPRs was established, and its performance was validated in CGGA325 cohorts. The low-risk group exhibited better overall survival, immune microenvironment, and immunotherapy response, as determined via the TIDE algorithm, indicating that increasing the level of immune infiltration can effectively improve the response to immunotherapy in the low-risk group. The risk score was determined to be an independent hazard factor (p<0.001) although other clinical features (age, sex, grade, IDH status, 1p19q codel status, MGMT status, and accepted radiotherapy) were considered. Lastly, high-risk groups in both cohorts revealed optimal drug responses to rapamycin, paclitaxel, JW-7-52-1, and bortezomib. CONCLUSIONS: Our study identified two distinct TPR subtypes and built a TPR signature to elucidate the characteristics of T cell proliferation in LGG and its association with immune status and prognosis. These findings shed light on possible immunotherapeutic strategies for LGGs.
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spelling pubmed-98851612023-01-31 Positive regulators of T cell functions as predictors of prognosis and microenvironment characteristics of low-grade gliomas Li, Yang Feng, Yabo Luo, Fushu Peng, Gang Li, Yueran Front Immunol Immunology BACKGROUND: Low-grade gliomas (LGG) are one of the most prevalent types of brain cancers. The efficacy of immunotherapy in LGG is limited compared to other cancers. Immunosuppression in the tumor microenvironment (TME) of LGG is one of the main reasons for the low efficacy of immunotherapy. Recent studies have identified 33 positive regulators of T cell functions (TPRs) that play a critical role in promoting the proliferation, activity, and functions of multiple immunocytes. However, their role in the TME of LGG has not been investigated. This study aimed to construct a risk model based on these TPRs and to detect the significance of immunotypes in predicting LGG prognosis and immunotherapy efficacy. METHODS: A total of 688 LGGs and 202 normal brain tissues were extracted from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Genotype-Tissue Expression (GTEx) databases. The NMF R package was used to identify TRP-related subtypes. The TPR prognostic model was established using the least absolute shrinkage and selection operator (LASSO) algorithm to predict the overall survival of LGG samples. RESULTS: The Subtype 2 patients had worse survival outcomes, suppressed immune function, and higher immune cell infiltration. A risk regression model consisting of 14 TPRs was established, and its performance was validated in CGGA325 cohorts. The low-risk group exhibited better overall survival, immune microenvironment, and immunotherapy response, as determined via the TIDE algorithm, indicating that increasing the level of immune infiltration can effectively improve the response to immunotherapy in the low-risk group. The risk score was determined to be an independent hazard factor (p<0.001) although other clinical features (age, sex, grade, IDH status, 1p19q codel status, MGMT status, and accepted radiotherapy) were considered. Lastly, high-risk groups in both cohorts revealed optimal drug responses to rapamycin, paclitaxel, JW-7-52-1, and bortezomib. CONCLUSIONS: Our study identified two distinct TPR subtypes and built a TPR signature to elucidate the characteristics of T cell proliferation in LGG and its association with immune status and prognosis. These findings shed light on possible immunotherapeutic strategies for LGGs. Frontiers Media S.A. 2023-01-16 /pmc/articles/PMC9885161/ /pubmed/36726969 http://dx.doi.org/10.3389/fimmu.2022.1089792 Text en Copyright © 2023 Li, Feng, Luo, Peng and Li 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
Li, Yang
Feng, Yabo
Luo, Fushu
Peng, Gang
Li, Yueran
Positive regulators of T cell functions as predictors of prognosis and microenvironment characteristics of low-grade gliomas
title Positive regulators of T cell functions as predictors of prognosis and microenvironment characteristics of low-grade gliomas
title_full Positive regulators of T cell functions as predictors of prognosis and microenvironment characteristics of low-grade gliomas
title_fullStr Positive regulators of T cell functions as predictors of prognosis and microenvironment characteristics of low-grade gliomas
title_full_unstemmed Positive regulators of T cell functions as predictors of prognosis and microenvironment characteristics of low-grade gliomas
title_short Positive regulators of T cell functions as predictors of prognosis and microenvironment characteristics of low-grade gliomas
title_sort positive regulators of t cell functions as predictors of prognosis and microenvironment characteristics of low-grade gliomas
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885161/
https://www.ncbi.nlm.nih.gov/pubmed/36726969
http://dx.doi.org/10.3389/fimmu.2022.1089792
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