An Individualized Prognostic Signature for Clinically Predicting the Survival of Patients With Bladder Cancer.

ABSTRACT: Background: The tumor immune microenvironment (TIME) plays an important role in the development and prognosis of bladder cancer. It is essential to conduct a risk model to explore the prognostic value of the immunologic genes and establish an individualized prognostic signature for predicting the survival of patients with bladder cancer. Method: The differentially expressed immunologic genes (DEGs) are identified in The Cancer Genome Atlas (TCGA). The nonnegative matrix factorization (NMF) was used to stratify the DEGs in TCGA. We used the least absolute shrinkage and selection operator (LASSO) Cox regression and univariate Cox analysis to establish a prognostic risk model. A nomogram was used to establish an individualized prognostic signature for predicting survival. The po

SUBMITTER: Liu Q 

PROVIDER: S-EPMC9002098 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature