A bioinformatics analysis to evaluate the prognostic value of stemness-related genes in gastric cancer.

ABSTRACT:

Background

This study aimed to identify potential stemness-related targets in gastric cancer (GC) in order to support the development of new treatment strategies and improve patient survival.

Methods

Using the edgeR package, we identified stemness-related differentially expressed genes (DEGs) using GSE112631 and the stemness-related signaling pathways in the Gene Set Enrichment Analysis (GSEA) database. Lasso-penalized Cox regression analysis and multivariate Cox regression analysis tested by Akaike Information Criterion (AIC) were used to screen out survival genes in order to construct a prognostic model. We verified the accuracy of our prognostic model using a nomogram and receiver operating characteristic (ROC) curve analysis. Patients were divided into two groups based o

SUBMITTER: Lu YJ 

PROVIDER: S-EPMC8798931 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature