In silico development and experimental validation of a novel 7-gene signature based on PI3K pathway-related genes in bladder cancer.

ABSTRACT: Although bladder cancer (BLCA) is the 10th most common tumor worldwide, particularly practical markers and prognostic models that might guide therapy are needed. We used a non-negative matrix factorization algorithm to classify PI3K pathway-related genes into molecular subtypes. A weighted gene co-expression network analysis (WGCNA) was generated to identify co-expression modules. Univariate Cox regression, least absolute shrinkage sum selection operator-Cox regression, and multivariate Cox regression were utilized to develop a prognostic score model. Kaplan-Meier analysis and receiver operating characteristics were utilized to measure the model's effectiveness. A nomogram was constructed to improve the predictive ability of the model based on clinical parameters and risk. Decision curve a

SUBMITTER: Wang L 

PROVIDER: S-EPMC9550739 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature