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Comprehensive analyses of a tumor-infiltrating lymphocytes-related gene signature regarding the prognosis and immunologic features for immunotherapy in bladder cancer on the basis of WGCNA
Tumor-infiltrating lymphocyte (TIL) is a class of cells with important immune functions and plays a crucial role in bladder cancer (BCa). Several studies have shown the clinical significance of TIL in predicting the prognosis and immunotherapy efficacy. TIL-related gene module was screened utilizing...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9540212/ https://www.ncbi.nlm.nih.gov/pubmed/36211333 http://dx.doi.org/10.3389/fimmu.2022.973974 |
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author | He, Zexi Gu, Jun Luan, Ting Li, Haihao Li, Charles Chen, Zhenjie Luo, Enxiu Wang, Jiansong Huang, Yinglong Ding, Mingxia |
author_facet | He, Zexi Gu, Jun Luan, Ting Li, Haihao Li, Charles Chen, Zhenjie Luo, Enxiu Wang, Jiansong Huang, Yinglong Ding, Mingxia |
author_sort | He, Zexi |
collection | PubMed |
description | Tumor-infiltrating lymphocyte (TIL) is a class of cells with important immune functions and plays a crucial role in bladder cancer (BCa). Several studies have shown the clinical significance of TIL in predicting the prognosis and immunotherapy efficacy. TIL-related gene module was screened utilizing weighted gene coexpression network analysis. We screened eight TIL-related genes utilizing univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) Cox regression analysis, and multivariate Cox regression analysis. Then, we established a TIL-related signature model containing the eight selected genes and subsequently classified all patients into two groups, that is, the high-risk as well as low-risk groups. Gene mutation status, prognosis, immune cell infiltration, immune subtypes, TME, clinical features, and immunotherapy response were assessed among different risk subgroups. The results affirmed that the TIL-related signature model was a reliable predictor of overall survival (OS) for BCa and was determined as an independent risk factor for BCa patients in two cohorts. Moreover, the risk score was substantially linked to age, tumor staging, TNM stage, and pathological grade. And there were different mutational profiles, biological pathways, immune scores, stromal scores, and immune cell infiltration in the tumor microenvironment (TME) between the two risk groups. In particular, immune checkpoint genes’ expression was remarkably different between the two risk groups, with patients belonging to the low-risk group responding better to immune checkpoint inhibition (ICI) therapy. In conclusion, our study demonstrates that the TIL-related model was a reliable signature in anticipating prognosis, immune status, and immunotherapy response, which can help in screening patients who respond to immunotherapy. |
format | Online Article Text |
id | pubmed-9540212 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95402122022-10-08 Comprehensive analyses of a tumor-infiltrating lymphocytes-related gene signature regarding the prognosis and immunologic features for immunotherapy in bladder cancer on the basis of WGCNA He, Zexi Gu, Jun Luan, Ting Li, Haihao Li, Charles Chen, Zhenjie Luo, Enxiu Wang, Jiansong Huang, Yinglong Ding, Mingxia Front Immunol Immunology Tumor-infiltrating lymphocyte (TIL) is a class of cells with important immune functions and plays a crucial role in bladder cancer (BCa). Several studies have shown the clinical significance of TIL in predicting the prognosis and immunotherapy efficacy. TIL-related gene module was screened utilizing weighted gene coexpression network analysis. We screened eight TIL-related genes utilizing univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) Cox regression analysis, and multivariate Cox regression analysis. Then, we established a TIL-related signature model containing the eight selected genes and subsequently classified all patients into two groups, that is, the high-risk as well as low-risk groups. Gene mutation status, prognosis, immune cell infiltration, immune subtypes, TME, clinical features, and immunotherapy response were assessed among different risk subgroups. The results affirmed that the TIL-related signature model was a reliable predictor of overall survival (OS) for BCa and was determined as an independent risk factor for BCa patients in two cohorts. Moreover, the risk score was substantially linked to age, tumor staging, TNM stage, and pathological grade. And there were different mutational profiles, biological pathways, immune scores, stromal scores, and immune cell infiltration in the tumor microenvironment (TME) between the two risk groups. In particular, immune checkpoint genes’ expression was remarkably different between the two risk groups, with patients belonging to the low-risk group responding better to immune checkpoint inhibition (ICI) therapy. In conclusion, our study demonstrates that the TIL-related model was a reliable signature in anticipating prognosis, immune status, and immunotherapy response, which can help in screening patients who respond to immunotherapy. Frontiers Media S.A. 2022-09-20 /pmc/articles/PMC9540212/ /pubmed/36211333 http://dx.doi.org/10.3389/fimmu.2022.973974 Text en Copyright © 2022 He, Gu, Luan, Li, Li, Chen, Luo, Wang, Huang and Ding 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 He, Zexi Gu, Jun Luan, Ting Li, Haihao Li, Charles Chen, Zhenjie Luo, Enxiu Wang, Jiansong Huang, Yinglong Ding, Mingxia Comprehensive analyses of a tumor-infiltrating lymphocytes-related gene signature regarding the prognosis and immunologic features for immunotherapy in bladder cancer on the basis of WGCNA |
title | Comprehensive analyses of a tumor-infiltrating lymphocytes-related gene signature regarding the prognosis and immunologic features for immunotherapy in bladder cancer on the basis of WGCNA |
title_full | Comprehensive analyses of a tumor-infiltrating lymphocytes-related gene signature regarding the prognosis and immunologic features for immunotherapy in bladder cancer on the basis of WGCNA |
title_fullStr | Comprehensive analyses of a tumor-infiltrating lymphocytes-related gene signature regarding the prognosis and immunologic features for immunotherapy in bladder cancer on the basis of WGCNA |
title_full_unstemmed | Comprehensive analyses of a tumor-infiltrating lymphocytes-related gene signature regarding the prognosis and immunologic features for immunotherapy in bladder cancer on the basis of WGCNA |
title_short | Comprehensive analyses of a tumor-infiltrating lymphocytes-related gene signature regarding the prognosis and immunologic features for immunotherapy in bladder cancer on the basis of WGCNA |
title_sort | comprehensive analyses of a tumor-infiltrating lymphocytes-related gene signature regarding the prognosis and immunologic features for immunotherapy in bladder cancer on the basis of wgcna |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9540212/ https://www.ncbi.nlm.nih.gov/pubmed/36211333 http://dx.doi.org/10.3389/fimmu.2022.973974 |
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