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Identification of a Prognosis-Related Risk Signature for Bladder Cancer to Predict Survival and Immune Landscapes

BACKGROUND: Bladder cancer is the tenth most common cancer worldwide. Valuable biomarkers in the field of diagnostic bladder cancer are urgently required. METHOD: Here, the gene expression matrix and clinical data were obtained from The Cancer Genome Atlas (TCGA), GSE13507, GSE32894, and Mariathasan...

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Autores principales: Wang, Linhui, Wang, Yutao, Wang, Jianfeng, Li, Luanfeng, Bi, Jianbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545590/
https://www.ncbi.nlm.nih.gov/pubmed/34708131
http://dx.doi.org/10.1155/2021/3236384
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author Wang, Linhui
Wang, Yutao
Wang, Jianfeng
Li, Luanfeng
Bi, Jianbin
author_facet Wang, Linhui
Wang, Yutao
Wang, Jianfeng
Li, Luanfeng
Bi, Jianbin
author_sort Wang, Linhui
collection PubMed
description BACKGROUND: Bladder cancer is the tenth most common cancer worldwide. Valuable biomarkers in the field of diagnostic bladder cancer are urgently required. METHOD: Here, the gene expression matrix and clinical data were obtained from The Cancer Genome Atlas (TCGA), GSE13507, GSE32894, and Mariathasan et al. Five prognostic genes were identified by the univariate, robust, and multivariate Cox's regression and were used to develop a prognosis-related model. The Kaplan–Meier survival curves and receiver operating characteristics were used to evaluate the model's effectiveness. The potential biological functions of the selected genes were analyzed using CIBERSORT and ESTIMATE algorithms. Cancer Therapeutics Response Portal (CTRP) and PRISM datasets were used to identify drugs with high sensitivity. Subsequently, using the bladder cancer (BLCA) cell lines, the role of TNFRSF14 was determined by Western blotting, cell proliferation assay, and 5-ethynyl-20-deoxyuridine assay. RESULTS: GSDMB, CLEC2D, APOL2, TNFRSF14, and GBP2 were selected as prognostic genes in bladder cancer patients. The model's irreplaceable reliability was validated by the training and validation cohorts. CD8+ T cells were highly infiltrated in the high-TNFRSF14-expression group, and M2 macrophages were the opposite. Higher expression of TNFRSF14 was associated with higher expression levels of LCK, interferon, MHC-I, and MHC-II, while risk score was the opposite. Many compounds with higher sensitivity for treating bladder cancer patients in the low-TNFRSF14-expression group were identified, with obatoclax being a potential drug most likely to treat patients in the low-TNFRSF14-expression group. Finally, the proliferation of BLCA cell lines was increased in the TNFRSF14-reduced group, and the differential expression was identified. TNFRSF14 plays a role in bladder cancer progression through the Wnt/β-catenin-dependent pathway. TNFRSF14 is a potential protective biomarker involved in cell proliferation in BLCA. CONCLUSION: We conducted a study to establish a 5-gene score model, providing reliable prediction for the outcome of bladder cancer patients and therapeutic drugs to individualize therapy. Our findings provide a signature that might help determine the optimal treatment for individual patients with bladder cancer.
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spelling pubmed-85455902021-10-26 Identification of a Prognosis-Related Risk Signature for Bladder Cancer to Predict Survival and Immune Landscapes Wang, Linhui Wang, Yutao Wang, Jianfeng Li, Luanfeng Bi, Jianbin J Immunol Res Research Article BACKGROUND: Bladder cancer is the tenth most common cancer worldwide. Valuable biomarkers in the field of diagnostic bladder cancer are urgently required. METHOD: Here, the gene expression matrix and clinical data were obtained from The Cancer Genome Atlas (TCGA), GSE13507, GSE32894, and Mariathasan et al. Five prognostic genes were identified by the univariate, robust, and multivariate Cox's regression and were used to develop a prognosis-related model. The Kaplan–Meier survival curves and receiver operating characteristics were used to evaluate the model's effectiveness. The potential biological functions of the selected genes were analyzed using CIBERSORT and ESTIMATE algorithms. Cancer Therapeutics Response Portal (CTRP) and PRISM datasets were used to identify drugs with high sensitivity. Subsequently, using the bladder cancer (BLCA) cell lines, the role of TNFRSF14 was determined by Western blotting, cell proliferation assay, and 5-ethynyl-20-deoxyuridine assay. RESULTS: GSDMB, CLEC2D, APOL2, TNFRSF14, and GBP2 were selected as prognostic genes in bladder cancer patients. The model's irreplaceable reliability was validated by the training and validation cohorts. CD8+ T cells were highly infiltrated in the high-TNFRSF14-expression group, and M2 macrophages were the opposite. Higher expression of TNFRSF14 was associated with higher expression levels of LCK, interferon, MHC-I, and MHC-II, while risk score was the opposite. Many compounds with higher sensitivity for treating bladder cancer patients in the low-TNFRSF14-expression group were identified, with obatoclax being a potential drug most likely to treat patients in the low-TNFRSF14-expression group. Finally, the proliferation of BLCA cell lines was increased in the TNFRSF14-reduced group, and the differential expression was identified. TNFRSF14 plays a role in bladder cancer progression through the Wnt/β-catenin-dependent pathway. TNFRSF14 is a potential protective biomarker involved in cell proliferation in BLCA. CONCLUSION: We conducted a study to establish a 5-gene score model, providing reliable prediction for the outcome of bladder cancer patients and therapeutic drugs to individualize therapy. Our findings provide a signature that might help determine the optimal treatment for individual patients with bladder cancer. Hindawi 2021-10-18 /pmc/articles/PMC8545590/ /pubmed/34708131 http://dx.doi.org/10.1155/2021/3236384 Text en Copyright © 2021 Linhui Wang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wang, Linhui
Wang, Yutao
Wang, Jianfeng
Li, Luanfeng
Bi, Jianbin
Identification of a Prognosis-Related Risk Signature for Bladder Cancer to Predict Survival and Immune Landscapes
title Identification of a Prognosis-Related Risk Signature for Bladder Cancer to Predict Survival and Immune Landscapes
title_full Identification of a Prognosis-Related Risk Signature for Bladder Cancer to Predict Survival and Immune Landscapes
title_fullStr Identification of a Prognosis-Related Risk Signature for Bladder Cancer to Predict Survival and Immune Landscapes
title_full_unstemmed Identification of a Prognosis-Related Risk Signature for Bladder Cancer to Predict Survival and Immune Landscapes
title_short Identification of a Prognosis-Related Risk Signature for Bladder Cancer to Predict Survival and Immune Landscapes
title_sort identification of a prognosis-related risk signature for bladder cancer to predict survival and immune landscapes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545590/
https://www.ncbi.nlm.nih.gov/pubmed/34708131
http://dx.doi.org/10.1155/2021/3236384
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