Identification of a nine-gene prognostic signature for gastric carcinoma using integrated bioinformatics analyses.

ABSTRACT:

Background

Gastric carcinoma (GC) is one of the most aggressive primary digestive cancers. It has unsatisfactory therapeutic outcomes and is difficult to diagnose early.

Aim

To identify prognostic biomarkers for GC patients using comprehensive bioinformatics analyses.

Methods

Differentially expressed genes (DEGs) were screened using gene expression data from The Cancer Genome Atlas and Gene Expression Omnibus databases for GC. Overlapping DEGs were analyzed using univariate and multivariate Cox regression analyses. A risk score model was then constructed and its prognostic value was validated utilizing an independent Gene Expression Omnibus dataset (GSE15459). Multiple databases were used to analyze each gene in the risk score model. High-risk score-associated pathway

SUBMITTER: Wu KZ 

PROVIDER: S-EPMC7509999 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature