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New Prognostic Gene Signature and Immune Escape Mechanisms of Bladder Cancer

Background: The immune microenvironment profoundly affects tumor prognosis and therapy. The present study aimed to reveal potential immune escape mechanisms and construct a novel prognostic signature via systematic bioinformatic analysis of the bladder cancer (BLCA) immune microenvironment. Patients...

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Autores principales: Jiang, Yi, Zeng, Zhenhao, Xiong, Situ, Jiang, Ming, Huang, Gaomin, Zhang, Chiyu, Xi, Xiaoqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9133907/
https://www.ncbi.nlm.nih.gov/pubmed/35646934
http://dx.doi.org/10.3389/fcell.2022.775417
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author Jiang, Yi
Zeng, Zhenhao
Xiong, Situ
Jiang, Ming
Huang, Gaomin
Zhang, Chiyu
Xi, Xiaoqing
author_facet Jiang, Yi
Zeng, Zhenhao
Xiong, Situ
Jiang, Ming
Huang, Gaomin
Zhang, Chiyu
Xi, Xiaoqing
author_sort Jiang, Yi
collection PubMed
description Background: The immune microenvironment profoundly affects tumor prognosis and therapy. The present study aimed to reveal potential immune escape mechanisms and construct a novel prognostic signature via systematic bioinformatic analysis of the bladder cancer (BLCA) immune microenvironment. Patients and Methods: The transcriptomic data and clinicopathological information for patients with BLCA were obtained from The Cancer Genome Atlas (TCGA). Consensus clustering analysis based on the CIBERSORT and ESTIMATE algorithms was performed with patients with BLCA, which divided them into two clusters. Subsequently, the differentially expressed genes (DEGs) in the two were subjected to univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses to identify prognostic genes, which were used to construct a prognostic model. The predictive performance of the model was verified by receiver operating characteristic (ROC) and Kaplan–Meier (K-M) analyses. In addition, we analyzed the differentially altered immune cells, mutation burden, neoantigen load, and subclonal genome fraction between the two clusters to reveal the immune escape mechanism. Results: Based on the ESTIMATE and clustering analyses, patients with BLCA were classified into two heterogeneous clusters: ImmuneScoreH and ImmuneScoreL. Univariate Cox and LASSO regression analyses identified CD96 (HR = 0.83) and IBSP (HR = 1.09), which were used to construct a prognostic gene signature with significant predictive accuracy. Regarding potential immune escape mechanisms, ImmuneScoreH and ImmuneScoreL were characterized by inactivation of innate immune cell chemotaxis. In ImmuneScoreL, a low tumor antigen load might contribute to immune escape. ImmuneScoreH featured high expression of immune checkpoint molecules. Conclusion: CD96 and IBSP were considered prognostic factors for BLCA. Innate immune inactivation and a low tumor antigen load may be associated with immune escape mechanisms in both clusters. Our research complements the exploration of the immune microenvironment in BLCA.
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spelling pubmed-91339072022-05-27 New Prognostic Gene Signature and Immune Escape Mechanisms of Bladder Cancer Jiang, Yi Zeng, Zhenhao Xiong, Situ Jiang, Ming Huang, Gaomin Zhang, Chiyu Xi, Xiaoqing Front Cell Dev Biol Cell and Developmental Biology Background: The immune microenvironment profoundly affects tumor prognosis and therapy. The present study aimed to reveal potential immune escape mechanisms and construct a novel prognostic signature via systematic bioinformatic analysis of the bladder cancer (BLCA) immune microenvironment. Patients and Methods: The transcriptomic data and clinicopathological information for patients with BLCA were obtained from The Cancer Genome Atlas (TCGA). Consensus clustering analysis based on the CIBERSORT and ESTIMATE algorithms was performed with patients with BLCA, which divided them into two clusters. Subsequently, the differentially expressed genes (DEGs) in the two were subjected to univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses to identify prognostic genes, which were used to construct a prognostic model. The predictive performance of the model was verified by receiver operating characteristic (ROC) and Kaplan–Meier (K-M) analyses. In addition, we analyzed the differentially altered immune cells, mutation burden, neoantigen load, and subclonal genome fraction between the two clusters to reveal the immune escape mechanism. Results: Based on the ESTIMATE and clustering analyses, patients with BLCA were classified into two heterogeneous clusters: ImmuneScoreH and ImmuneScoreL. Univariate Cox and LASSO regression analyses identified CD96 (HR = 0.83) and IBSP (HR = 1.09), which were used to construct a prognostic gene signature with significant predictive accuracy. Regarding potential immune escape mechanisms, ImmuneScoreH and ImmuneScoreL were characterized by inactivation of innate immune cell chemotaxis. In ImmuneScoreL, a low tumor antigen load might contribute to immune escape. ImmuneScoreH featured high expression of immune checkpoint molecules. Conclusion: CD96 and IBSP were considered prognostic factors for BLCA. Innate immune inactivation and a low tumor antigen load may be associated with immune escape mechanisms in both clusters. Our research complements the exploration of the immune microenvironment in BLCA. Frontiers Media S.A. 2022-05-12 /pmc/articles/PMC9133907/ /pubmed/35646934 http://dx.doi.org/10.3389/fcell.2022.775417 Text en Copyright © 2022 Jiang, Zeng, Xiong, Jiang, Huang, Zhang and Xi. 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 Cell and Developmental Biology
Jiang, Yi
Zeng, Zhenhao
Xiong, Situ
Jiang, Ming
Huang, Gaomin
Zhang, Chiyu
Xi, Xiaoqing
New Prognostic Gene Signature and Immune Escape Mechanisms of Bladder Cancer
title New Prognostic Gene Signature and Immune Escape Mechanisms of Bladder Cancer
title_full New Prognostic Gene Signature and Immune Escape Mechanisms of Bladder Cancer
title_fullStr New Prognostic Gene Signature and Immune Escape Mechanisms of Bladder Cancer
title_full_unstemmed New Prognostic Gene Signature and Immune Escape Mechanisms of Bladder Cancer
title_short New Prognostic Gene Signature and Immune Escape Mechanisms of Bladder Cancer
title_sort new prognostic gene signature and immune escape mechanisms of bladder cancer
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9133907/
https://www.ncbi.nlm.nih.gov/pubmed/35646934
http://dx.doi.org/10.3389/fcell.2022.775417
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