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Development and External Validation of a Novel 12-Gene Signature for Prediction of Overall Survival in Muscle-Invasive Bladder Cancer

Purpose: We aimed to develop and validate a novel gene signature from published data and improve the prediction of survival in muscle-invasive bladder cancer (MIBC). Methods: We searched the published gene signatures associated with the overall survival (OS) of MIBC and compiled all 274 genes to dev...

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Autores principales: Abudurexiti, MierXiati, Xie, Huyang, Jia, Zhongwei, Zhu, Yiping, Zhu, Yao, Shi, Guohai, Zhang, Hailiang, Dai, Bo, Wan, Fangning, Shen, Yijun, Ye, Dingwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743371/
https://www.ncbi.nlm.nih.gov/pubmed/31552180
http://dx.doi.org/10.3389/fonc.2019.00856
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author Abudurexiti, MierXiati
Xie, Huyang
Jia, Zhongwei
Zhu, Yiping
Zhu, Yao
Shi, Guohai
Zhang, Hailiang
Dai, Bo
Wan, Fangning
Shen, Yijun
Ye, Dingwei
author_facet Abudurexiti, MierXiati
Xie, Huyang
Jia, Zhongwei
Zhu, Yiping
Zhu, Yao
Shi, Guohai
Zhang, Hailiang
Dai, Bo
Wan, Fangning
Shen, Yijun
Ye, Dingwei
author_sort Abudurexiti, MierXiati
collection PubMed
description Purpose: We aimed to develop and validate a novel gene signature from published data and improve the prediction of survival in muscle-invasive bladder cancer (MIBC). Methods: We searched the published gene signatures associated with the overall survival (OS) of MIBC and compiled all 274 genes to develop a novel gene signature. RNAseq data of TCGA (the Cancer Genome Atlas) bladder cohort were downloaded. All genes were included in a univariate Cox hazard ratio model. We then used a reduced multivariate Cox regression model, which included only genes achieving P < 0.05 in the univariate model. A total of 172 patients at Fudan University Shanghai Cancer Center (FUSCC) and 61 patients from GEO datasets were used as an external validation set. Results: A total of 327 patients in the TCGA cohort were enrolled. We identified 274 genes from eight published papers on the OS of MIBC. Using the TCGA database, we identified 12 genes that correlated with OS (P < 0.05 in both univariate and multivariate analyses). By integrating these genes with the RT-qPCR data in our validation dataset and GEO datasets, we confirmed that the power for predicting OS of the 12-gene panel (AUC of 0.741 and 0.727, respectively) was higher than just clinical data (including gender, age, T stage, grade, and N stage) alone in the TCGA and FUSCC cohort (AUC of 0.667 and 0.631, respectively). Additionally, upon combining the clinical data and 12-gene panel together, the AUC increased to 0.768, 0.757, and 0.88 in the TCGA, FUSCC and GSE13507 cohorts, respectively. Conclusions: Applying published gene signatures and TCGA data, we successfully built and externally validated a novel 12-gene signature for the survival of MIBC. BRIEF EXPLANATION: We systemically reviewed all published prognostic gene signatures of muscle-invasive bladder cancer (MIBC) and integrated the genes in the TCGA MIBC cohort. This new gene panel was validated in a newly established MIBC cohort in GEO and FUSCC. This method can help update the previous established panels in a new way.
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spelling pubmed-67433712019-09-24 Development and External Validation of a Novel 12-Gene Signature for Prediction of Overall Survival in Muscle-Invasive Bladder Cancer Abudurexiti, MierXiati Xie, Huyang Jia, Zhongwei Zhu, Yiping Zhu, Yao Shi, Guohai Zhang, Hailiang Dai, Bo Wan, Fangning Shen, Yijun Ye, Dingwei Front Oncol Oncology Purpose: We aimed to develop and validate a novel gene signature from published data and improve the prediction of survival in muscle-invasive bladder cancer (MIBC). Methods: We searched the published gene signatures associated with the overall survival (OS) of MIBC and compiled all 274 genes to develop a novel gene signature. RNAseq data of TCGA (the Cancer Genome Atlas) bladder cohort were downloaded. All genes were included in a univariate Cox hazard ratio model. We then used a reduced multivariate Cox regression model, which included only genes achieving P < 0.05 in the univariate model. A total of 172 patients at Fudan University Shanghai Cancer Center (FUSCC) and 61 patients from GEO datasets were used as an external validation set. Results: A total of 327 patients in the TCGA cohort were enrolled. We identified 274 genes from eight published papers on the OS of MIBC. Using the TCGA database, we identified 12 genes that correlated with OS (P < 0.05 in both univariate and multivariate analyses). By integrating these genes with the RT-qPCR data in our validation dataset and GEO datasets, we confirmed that the power for predicting OS of the 12-gene panel (AUC of 0.741 and 0.727, respectively) was higher than just clinical data (including gender, age, T stage, grade, and N stage) alone in the TCGA and FUSCC cohort (AUC of 0.667 and 0.631, respectively). Additionally, upon combining the clinical data and 12-gene panel together, the AUC increased to 0.768, 0.757, and 0.88 in the TCGA, FUSCC and GSE13507 cohorts, respectively. Conclusions: Applying published gene signatures and TCGA data, we successfully built and externally validated a novel 12-gene signature for the survival of MIBC. BRIEF EXPLANATION: We systemically reviewed all published prognostic gene signatures of muscle-invasive bladder cancer (MIBC) and integrated the genes in the TCGA MIBC cohort. This new gene panel was validated in a newly established MIBC cohort in GEO and FUSCC. This method can help update the previous established panels in a new way. Frontiers Media S.A. 2019-09-06 /pmc/articles/PMC6743371/ /pubmed/31552180 http://dx.doi.org/10.3389/fonc.2019.00856 Text en Copyright © 2019 Abudurexiti, Xie, Jia, Zhu, Zhu, Shi, Zhang, Dai, Wan, Shen and Ye. http://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 Oncology
Abudurexiti, MierXiati
Xie, Huyang
Jia, Zhongwei
Zhu, Yiping
Zhu, Yao
Shi, Guohai
Zhang, Hailiang
Dai, Bo
Wan, Fangning
Shen, Yijun
Ye, Dingwei
Development and External Validation of a Novel 12-Gene Signature for Prediction of Overall Survival in Muscle-Invasive Bladder Cancer
title Development and External Validation of a Novel 12-Gene Signature for Prediction of Overall Survival in Muscle-Invasive Bladder Cancer
title_full Development and External Validation of a Novel 12-Gene Signature for Prediction of Overall Survival in Muscle-Invasive Bladder Cancer
title_fullStr Development and External Validation of a Novel 12-Gene Signature for Prediction of Overall Survival in Muscle-Invasive Bladder Cancer
title_full_unstemmed Development and External Validation of a Novel 12-Gene Signature for Prediction of Overall Survival in Muscle-Invasive Bladder Cancer
title_short Development and External Validation of a Novel 12-Gene Signature for Prediction of Overall Survival in Muscle-Invasive Bladder Cancer
title_sort development and external validation of a novel 12-gene signature for prediction of overall survival in muscle-invasive bladder cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743371/
https://www.ncbi.nlm.nih.gov/pubmed/31552180
http://dx.doi.org/10.3389/fonc.2019.00856
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