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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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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. |
format | Online Article Text |
id | pubmed-9133907 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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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