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An Outcome Model for Human Bladder Cancer: A Comprehensive Study Based on Weighted Gene Co-Expression Network Analysis

56 Pages Posted: 14 Nov 2019

See all articles by Yaoyi Xiong

Yaoyi Xiong

Wuhan University - Zhongnan Hospital

Lushun Yuan

Leiden University

Jing Xiong

Wuhan University - Department of Urology

Huimin Xu

Wuhan University - Department of Urology

Yongwen Luo

Wuhan University - Department of Urology

Gang Wang

Wuhan University - Department of Biological Repositories; Human Genetics Resource Preservation Center of Hubei Province; Wuhan University - Human Genetics Resource Preservation Center

Lingao Ju

Wuhan University - Department of Biological Repositories

Yu Xiao

Wuhan University - Department of Urology

Xinghuan Wang

Wuhan University - Department of Urology; Wuhan University - Center for Evidence-Based and Translational Medicine; Wuhan University - Medical Research Institute

More...

Abstract

Background: The evaluation of prognosis is crucial for clinical treatment decision of bladder cancer (BCa) patients. We aim to establishing an effective and reliable model to predict the prognosis of BCa patients.

Methods: We performed WGCNA and DEG screening to initially identify the candidate genes. The candidate genes were applied to construct a LASSO Cox regression analysis model. The effectiveness and accuracy of the prognostic model were tested by internal/external validation and pan-cancer validation and time-dependent ROC. Additionally, a nomogram based on the parameter selected from univariate and multivariate cox regression analysis was constructed.

Findings: Eight genes were eventually screened out as progression-related differentially expressed candidates in BCa. LASSO Cox regression analysis identified 3 genes to build up the outcome model in E-MTAB-4321 and the outcome model had good performance in predicting patient progress free survival of BCa patients in discovery and test set. Subsequently, another three datasets also have a good predictive value for BCa patients' OS and DFS. Time-dependent ROC indicated an ideal predictive accuracy of the outcome model. Meanwhile, the nomogram showed a good performance and clinical utility. In addition, the prognostic model also exhibits good performance in pan-cancer patients.

Interpretation: Our outcome model has proven to be an effective prognostic model for predicting the risk of prognosis in BCa as well as some other cancers.

Funding Statement: This work was supported by the Health commission of Hubei Province scientific research project (WJ2019H023 and WJ2019H013) and the Fundamental Research Funds for the Central Universities (2042019kf0150 and 2042019kf0176).

Declaration of Interests: The authors declare that there is no conflict of interests.

Ethics Approval Statement: Informed consent was obtained from all subjects. The Ethics Committee at Zhongnan Hospital of Wuhan University approved the experiments using human bladder tissue samples for RNA isolation and immunofluorescence staining analysis (approval number: 2015029). All methods used for human bladder tissue samples were performed in accordance with the approved guidelines and regulations.

Keywords: Bladder cancer; WGCNA; LASSO; Prognosis; Gene Expression Omnibus (GEO)

Suggested Citation

Xiong, Yaoyi and Yuan, Lushun and Xiong, Jing and Xu, Huimin and Luo, Yongwen and Wang, Gang and Ju, Lingao and Xiao, Yu and Wang, Xinghuan and Wang, Xinghuan, An Outcome Model for Human Bladder Cancer: A Comprehensive Study Based on Weighted Gene Co-Expression Network Analysis (10/23/2019 08:38:28). Available at SSRN: https://ssrn.com/abstract=3474500 or http://dx.doi.org/10.2139/ssrn.3474500

Yaoyi Xiong

Wuhan University - Zhongnan Hospital

Wuhan
China

Lushun Yuan

Leiden University

Postbus 9500
Leiden, Zuid Holland 2300 RA
Netherlands

Jing Xiong

Wuhan University - Department of Urology

China

Huimin Xu

Wuhan University - Department of Urology

China

Yongwen Luo

Wuhan University - Department of Urology

China

Gang Wang

Wuhan University - Department of Biological Repositories ( email )

Wuhan
China

Human Genetics Resource Preservation Center of Hubei Province ( email )

Wuhan
China

Wuhan University - Human Genetics Resource Preservation Center ( email )

Wuhan
China

Lingao Ju

Wuhan University - Department of Biological Repositories

Wuhan
China

Yu Xiao

Wuhan University - Department of Urology ( email )

China

Xinghuan Wang (Contact Author)

Wuhan University - Department of Urology ( email )

China

Wuhan University - Center for Evidence-Based and Translational Medicine ( email )

China

Wuhan University - Medical Research Institute ( email )

Wuhan
China