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Identification and validation of a novel prognostic model based on platinum resistance-related genes in bladder cancer

BACKGROUND: The depth of response to platinum in urothelial neoplasm tissues varies greatly. Biomarkers that have practical value in prognosis stratification are increasingly needed. Our study aimed to select a set of BC (bladder cancer)-related genes involved in both platinum resistance and surviva...

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Autores principales: Hao, Yining, Wang, Chenghe, Xu, Danfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sociedade Brasileira de Urologia 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9881817/
https://www.ncbi.nlm.nih.gov/pubmed/36512456
http://dx.doi.org/10.1590/S1677-5538.IBJU.2022.0373
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author Hao, Yining
Wang, Chenghe
Xu, Danfeng
author_facet Hao, Yining
Wang, Chenghe
Xu, Danfeng
author_sort Hao, Yining
collection PubMed
description BACKGROUND: The depth of response to platinum in urothelial neoplasm tissues varies greatly. Biomarkers that have practical value in prognosis stratification are increasingly needed. Our study aimed to select a set of BC (bladder cancer)-related genes involved in both platinum resistance and survival, then use these genes to establish the prognostic model. MATERIALS AND METHODS: Platinum resistance-related DEGs (differentially expressed genes) and tumorigenesis-related DEGs were identified. Ten most predictive co-DEGs were acquired followed by building a risk score model. Survival analysis and ROC (receiver operating characteristic) plot were used to evaluate the predictive accuracy. Combined with age and tumor stages, a nomogram was generated to create a graphical representation of survival rates at 1-, 3-, 5-, and 8-year in BC patients. The prognostic performance was validated in three independent BC datasets with platinum-based chemotherapy. The potential mechanism was explored by enrichment analysis. RESULTS: PPP2R2B, TSPAN7, ATAD3C, SYT15, SAPCD1, AKR1B1, TCHH, AKAP12, AGLN3, and IGF2 were selected for our prognostic model. Patients in high- and low-risk groups exhibited a significant survival difference with HR (hazard ratio) = 2.7 (p < 0.0001). The prognostic nomogram of predicting 3-year OS (overall survival) for BC patients could yield an AUC (area under the curve) of 0.819. In the external validation dataset, the risk score also has a robust predictive ability. CONCLUSION: A prognostic model derived from platinum resistance-related genes was constructed, we confirmed its value in predicting platinum-based chemotherapy benefits and overall survival for BC patients. The model might assist in therapeutic decisions for bladder malignancy.
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spelling pubmed-98818172023-01-29 Identification and validation of a novel prognostic model based on platinum resistance-related genes in bladder cancer Hao, Yining Wang, Chenghe Xu, Danfeng Int Braz J Urol Original Article BACKGROUND: The depth of response to platinum in urothelial neoplasm tissues varies greatly. Biomarkers that have practical value in prognosis stratification are increasingly needed. Our study aimed to select a set of BC (bladder cancer)-related genes involved in both platinum resistance and survival, then use these genes to establish the prognostic model. MATERIALS AND METHODS: Platinum resistance-related DEGs (differentially expressed genes) and tumorigenesis-related DEGs were identified. Ten most predictive co-DEGs were acquired followed by building a risk score model. Survival analysis and ROC (receiver operating characteristic) plot were used to evaluate the predictive accuracy. Combined with age and tumor stages, a nomogram was generated to create a graphical representation of survival rates at 1-, 3-, 5-, and 8-year in BC patients. The prognostic performance was validated in three independent BC datasets with platinum-based chemotherapy. The potential mechanism was explored by enrichment analysis. RESULTS: PPP2R2B, TSPAN7, ATAD3C, SYT15, SAPCD1, AKR1B1, TCHH, AKAP12, AGLN3, and IGF2 were selected for our prognostic model. Patients in high- and low-risk groups exhibited a significant survival difference with HR (hazard ratio) = 2.7 (p < 0.0001). The prognostic nomogram of predicting 3-year OS (overall survival) for BC patients could yield an AUC (area under the curve) of 0.819. In the external validation dataset, the risk score also has a robust predictive ability. CONCLUSION: A prognostic model derived from platinum resistance-related genes was constructed, we confirmed its value in predicting platinum-based chemotherapy benefits and overall survival for BC patients. The model might assist in therapeutic decisions for bladder malignancy. Sociedade Brasileira de Urologia 2022-11-20 /pmc/articles/PMC9881817/ /pubmed/36512456 http://dx.doi.org/10.1590/S1677-5538.IBJU.2022.0373 Text en https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Hao, Yining
Wang, Chenghe
Xu, Danfeng
Identification and validation of a novel prognostic model based on platinum resistance-related genes in bladder cancer
title Identification and validation of a novel prognostic model based on platinum resistance-related genes in bladder cancer
title_full Identification and validation of a novel prognostic model based on platinum resistance-related genes in bladder cancer
title_fullStr Identification and validation of a novel prognostic model based on platinum resistance-related genes in bladder cancer
title_full_unstemmed Identification and validation of a novel prognostic model based on platinum resistance-related genes in bladder cancer
title_short Identification and validation of a novel prognostic model based on platinum resistance-related genes in bladder cancer
title_sort identification and validation of a novel prognostic model based on platinum resistance-related genes in bladder cancer
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9881817/
https://www.ncbi.nlm.nih.gov/pubmed/36512456
http://dx.doi.org/10.1590/S1677-5538.IBJU.2022.0373
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