A robust 11-genes prognostic model can predict overall survival in bladder cancer patients based on five cohorts.

ABSTRACT:

Background

Bladder cancer is the tenth most common cancer globally, but existing biomarkers and prognostic models are limited.

Method

In this study, we used four bladder cancer cohorts from The Cancer Genome Atlas and Gene Expression Omnibus databases to perform univariate Cox regression analysis to identify common prognostic genes. We used the least absolute shrinkage and selection operator regression to construct a prognostic Cox model. Kaplan-Meier analysis, receiver operating characteristic curve, and univariate/multivariate Cox analysis were used to evaluate the prognostic model. Finally, a co-expression network, CIBERSORT, and ESTIMATE algorithm were used to explore the mechanism related to the model.

Results

A total of 11 genes were identified from the four coh

SUBMITTER: Lin J 

PROVIDER: S-EPMC7441568 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature