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A novel gene signature combination improves the prediction of overall survival in urinary bladder cancer

Objectives: Bladder carcinoma is a clinical heterogeneous disease, which is with significant variability of the prognosis and high risk of death. This revealed prominently the need to identify high-efficiency cancer characteristics to predict clinical prognosis. Methods: Gene expression profiles of...

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Autores principales: Chen, Siteng, Zhang, Ning, Shao, Jialiang, Wang, Tao, Wang, Xiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6843883/
https://www.ncbi.nlm.nih.gov/pubmed/31737111
http://dx.doi.org/10.7150/jca.30307
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author Chen, Siteng
Zhang, Ning
Shao, Jialiang
Wang, Tao
Wang, Xiang
author_facet Chen, Siteng
Zhang, Ning
Shao, Jialiang
Wang, Tao
Wang, Xiang
author_sort Chen, Siteng
collection PubMed
description Objectives: Bladder carcinoma is a clinical heterogeneous disease, which is with significant variability of the prognosis and high risk of death. This revealed prominently the need to identify high-efficiency cancer characteristics to predict clinical prognosis. Methods: Gene expression profiles of 93 bladder tumor patients from Gene Expression Omnibus data sets was performed in this study, along with 408 bladder tumor patients retrieved from The Cancer Genome Atlas database. The relationship of gene signature and overall survival was analyzed in the training cohort (n = 46). The validation for that was performed in an internal validation cohort (n = 47) and an external validation cohort (n = 408). Results: Four genes (TMPRSS11E, SCEL, KRT78, TMEM185A) were identified by univariable and multivariable Cox regression analysis. According to a risk score on the bases on the four-gene signature, we grouped these patients in high-risk group and low-risk group with significantly different overall survival in the training series and successfully validated it in both the internal and external validation cohorts. Subsequent studies demonstrated that the four-gene expression risk score was independent of radical cystectomy stage, chemotherapy and lymph node status. Higher rates of FAT4 mutation and MACF1 mutation in bladder tumors with high risk score were found compared with tumors with low risk score. Gene set enrichment analysis revealed high-risk score was associated with some tumor progression and recurrence associated pathways. Conclusions: This four-gene risk score might have potential clinical implications in the selection of high-risk urinary bladder cancer patients for aggressive therapy. The selected four genes might become potential therapeutic targets and diagnostic markers for urinary bladder cancer.
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spelling pubmed-68438832019-11-15 A novel gene signature combination improves the prediction of overall survival in urinary bladder cancer Chen, Siteng Zhang, Ning Shao, Jialiang Wang, Tao Wang, Xiang J Cancer Research Paper Objectives: Bladder carcinoma is a clinical heterogeneous disease, which is with significant variability of the prognosis and high risk of death. This revealed prominently the need to identify high-efficiency cancer characteristics to predict clinical prognosis. Methods: Gene expression profiles of 93 bladder tumor patients from Gene Expression Omnibus data sets was performed in this study, along with 408 bladder tumor patients retrieved from The Cancer Genome Atlas database. The relationship of gene signature and overall survival was analyzed in the training cohort (n = 46). The validation for that was performed in an internal validation cohort (n = 47) and an external validation cohort (n = 408). Results: Four genes (TMPRSS11E, SCEL, KRT78, TMEM185A) were identified by univariable and multivariable Cox regression analysis. According to a risk score on the bases on the four-gene signature, we grouped these patients in high-risk group and low-risk group with significantly different overall survival in the training series and successfully validated it in both the internal and external validation cohorts. Subsequent studies demonstrated that the four-gene expression risk score was independent of radical cystectomy stage, chemotherapy and lymph node status. Higher rates of FAT4 mutation and MACF1 mutation in bladder tumors with high risk score were found compared with tumors with low risk score. Gene set enrichment analysis revealed high-risk score was associated with some tumor progression and recurrence associated pathways. Conclusions: This four-gene risk score might have potential clinical implications in the selection of high-risk urinary bladder cancer patients for aggressive therapy. The selected four genes might become potential therapeutic targets and diagnostic markers for urinary bladder cancer. Ivyspring International Publisher 2019-10-03 /pmc/articles/PMC6843883/ /pubmed/31737111 http://dx.doi.org/10.7150/jca.30307 Text en © The author(s) This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
spellingShingle Research Paper
Chen, Siteng
Zhang, Ning
Shao, Jialiang
Wang, Tao
Wang, Xiang
A novel gene signature combination improves the prediction of overall survival in urinary bladder cancer
title A novel gene signature combination improves the prediction of overall survival in urinary bladder cancer
title_full A novel gene signature combination improves the prediction of overall survival in urinary bladder cancer
title_fullStr A novel gene signature combination improves the prediction of overall survival in urinary bladder cancer
title_full_unstemmed A novel gene signature combination improves the prediction of overall survival in urinary bladder cancer
title_short A novel gene signature combination improves the prediction of overall survival in urinary bladder cancer
title_sort novel gene signature combination improves the prediction of overall survival in urinary bladder cancer
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6843883/
https://www.ncbi.nlm.nih.gov/pubmed/31737111
http://dx.doi.org/10.7150/jca.30307
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