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.

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