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Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with Wilms tumour

Wilms tumour (WT) is the most common kidney malignancy in children. Chemoresistance is the leading cause of tumour recurrence and poses a substantial therapeutic challenge. Increasing evidence has underscored the role of the tumour immune microenvironment (TIM) in cancers and the potential for immun...

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Autores principales: Tian, Xiao-Mao, Xiang, Bin, Jin, Li-Ming, Mi, Tao, Wang, Jin-Kui, Zhanghuang, Chenghao, Zhang, Zhao-Xia, Chen, Mei-Ling, Shi, Qin-Lin, Liu, Feng, Lin, Tao, Wei, Guang-Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9510599/
https://www.ncbi.nlm.nih.gov/pubmed/36172369
http://dx.doi.org/10.3389/fimmu.2022.920666
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author Tian, Xiao-Mao
Xiang, Bin
Jin, Li-Ming
Mi, Tao
Wang, Jin-Kui
Zhanghuang, Chenghao
Zhang, Zhao-Xia
Chen, Mei-Ling
Shi, Qin-Lin
Liu, Feng
Lin, Tao
Wei, Guang-Hui
author_facet Tian, Xiao-Mao
Xiang, Bin
Jin, Li-Ming
Mi, Tao
Wang, Jin-Kui
Zhanghuang, Chenghao
Zhang, Zhao-Xia
Chen, Mei-Ling
Shi, Qin-Lin
Liu, Feng
Lin, Tao
Wei, Guang-Hui
author_sort Tian, Xiao-Mao
collection PubMed
description Wilms tumour (WT) is the most common kidney malignancy in children. Chemoresistance is the leading cause of tumour recurrence and poses a substantial therapeutic challenge. Increasing evidence has underscored the role of the tumour immune microenvironment (TIM) in cancers and the potential for immunotherapy to improve prognosis. There remain no reliable molecular markers for reflecting the immune landscape and predicting patient survival in WT. Here, we examine differences in gene expression by high-throughput RNA sequencing, focused on differentially expressed immune-related genes (IRGs) based on the ImmPort database. Via univariate Cox regression analysis and Lasso-penalized Cox regression analysis, IRGs were screened out to establish an immune signature. Kaplan-Meier curves, time-related ROC analysis, univariate and multivariate Cox regression studies, and nomograms were used to evaluate the accuracy and prognostic significance of this signature. Furthermore, we found that the immune signature could reflect the immune status and the immune cell infiltration character played in the tumour microenvironment (TME) and showed significant association with immune checkpoint molecules, suggesting that the poor outcome may be partially explained by its immunosuppressive TME. Remarkably, TIDE, a computational method to model tumour immune evasion mechanisms, showed that this signature holds great potential for predicting immunotherapy responses in the TARGET-wt cohort. To decipher the underlying mechanism, GSEA was applied to explore enriched pathways and biological processes associated with immunophenotyping and Connectivity map (CMap) along with DeSigN analysis for drug exploration. Finally, four candidate immune genes were selected, and their expression levels in WT cell lines were monitored via qRT-PCR. Meanwhile, we validated the function of a critical gene, NRP2. Taken together, we established a novel immune signature that may serve as an effective prognostic signature and predictive biomarker for immunotherapy response in WT patients. This study may give light on therapeutic strategies for WT patients from an immunological viewpoint.
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spelling pubmed-95105992022-09-27 Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with Wilms tumour Tian, Xiao-Mao Xiang, Bin Jin, Li-Ming Mi, Tao Wang, Jin-Kui Zhanghuang, Chenghao Zhang, Zhao-Xia Chen, Mei-Ling Shi, Qin-Lin Liu, Feng Lin, Tao Wei, Guang-Hui Front Immunol Immunology Wilms tumour (WT) is the most common kidney malignancy in children. Chemoresistance is the leading cause of tumour recurrence and poses a substantial therapeutic challenge. Increasing evidence has underscored the role of the tumour immune microenvironment (TIM) in cancers and the potential for immunotherapy to improve prognosis. There remain no reliable molecular markers for reflecting the immune landscape and predicting patient survival in WT. Here, we examine differences in gene expression by high-throughput RNA sequencing, focused on differentially expressed immune-related genes (IRGs) based on the ImmPort database. Via univariate Cox regression analysis and Lasso-penalized Cox regression analysis, IRGs were screened out to establish an immune signature. Kaplan-Meier curves, time-related ROC analysis, univariate and multivariate Cox regression studies, and nomograms were used to evaluate the accuracy and prognostic significance of this signature. Furthermore, we found that the immune signature could reflect the immune status and the immune cell infiltration character played in the tumour microenvironment (TME) and showed significant association with immune checkpoint molecules, suggesting that the poor outcome may be partially explained by its immunosuppressive TME. Remarkably, TIDE, a computational method to model tumour immune evasion mechanisms, showed that this signature holds great potential for predicting immunotherapy responses in the TARGET-wt cohort. To decipher the underlying mechanism, GSEA was applied to explore enriched pathways and biological processes associated with immunophenotyping and Connectivity map (CMap) along with DeSigN analysis for drug exploration. Finally, four candidate immune genes were selected, and their expression levels in WT cell lines were monitored via qRT-PCR. Meanwhile, we validated the function of a critical gene, NRP2. Taken together, we established a novel immune signature that may serve as an effective prognostic signature and predictive biomarker for immunotherapy response in WT patients. This study may give light on therapeutic strategies for WT patients from an immunological viewpoint. Frontiers Media S.A. 2022-09-12 /pmc/articles/PMC9510599/ /pubmed/36172369 http://dx.doi.org/10.3389/fimmu.2022.920666 Text en Copyright © 2022 Tian, Xiang, Jin, Mi, Wang, Zhanghuang, Zhang, Chen, Shi, Liu, Lin and Wei 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
Tian, Xiao-Mao
Xiang, Bin
Jin, Li-Ming
Mi, Tao
Wang, Jin-Kui
Zhanghuang, Chenghao
Zhang, Zhao-Xia
Chen, Mei-Ling
Shi, Qin-Lin
Liu, Feng
Lin, Tao
Wei, Guang-Hui
Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with Wilms tumour
title Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with Wilms tumour
title_full Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with Wilms tumour
title_fullStr Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with Wilms tumour
title_full_unstemmed Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with Wilms tumour
title_short Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with Wilms tumour
title_sort immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with wilms tumour
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9510599/
https://www.ncbi.nlm.nih.gov/pubmed/36172369
http://dx.doi.org/10.3389/fimmu.2022.920666
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