Construction of a novel mRNA-signature prediction model for prognosis of bladder cancer based on a statistical analysis.

ABSTRACT:

Background

Bladder cancer (BC) is a common malignancy neoplasm diagnosed in advanced stages in most cases. It is crucial to screen ideal biomarkers and construct a more accurate prognostic model than conventional clinical parameters. The aim of this research was to develop and validate an mRNA-based signature for predicting the prognosis of patients with bladder cancer.

Methods

The RNA-seq data was downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were screened in three datasets, and prognostic genes were identified from the training set of TCGA dataset. The common genes between DEGs and prognostic genes were narrowed down to six genes via Least Absolute Shrinkage and Selection Operator (LASSO) regression,

SUBMITTER: Li J 

PROVIDER: S-EPMC8314557 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature