An outcome model for human bladder cancer: A comprehensive study based on weighted gene co-expression network analysis.

ABSTRACT: The precision evaluation of prognosis is crucial for clinical treatment decision of bladder cancer (BCa). Therefore, establishing an effective prognostic model for BCa has significant clinical implications. 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. Eight genes were eventually screened out as progression-related differentially expressed candidates in BCa. LASSO Cox regression analysis identified

SUBMITTER: Xiong Y 

PROVIDER: S-EPMC7011142 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature