Identification of a tumor microenvironment-related seven-gene signature for predicting prognosis in bladder cancer.

ABSTRACT:

Background

Accumulating evidences demonstrated tumor microenvironment (TME) of bladder cancer (BLCA) may play a pivotal role in modulating tumorigenesis, progression, and alteration of biological features. Currently we aimed to establish a prognostic model based on TME-related gene expression for guiding clinical management of BLCA.

Methods

We employed ESTIMATE algorithm to evaluate TME cell infiltration in BLCA. The RNA-Seq data from The Cancer Genome Atlas (TCGA) database was used to screen out differentially expressed genes (DEGs). Underlying relationship between co-expression modules and TME was investigated via Weighted gene co-expression network analysis (WGCNA). COX regression and the least absolute shrinkage and selection operator (LASSO) analysis were applied for sc

SUBMITTER: Wang Z 

PROVIDER: S-EPMC8194149 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature