Bioinformatics and pathway enrichment analysis identified hub genes and potential biomarker for gastric cancer prognosis.

ABSTRACT:

Introduction

Gastric cancer is one of the most common cancers in the world. This study aimed to identify genes, biomarkers, and metabolic pathways affecting gastric cancer using bioinformatic analysis and meta-analysis.

Methods

Datasets containing gene expression profiles of tumor lesions and adjacent non-tumor mucosa samples were downloaded. Common differentially expressed genes between data sets were selected to identify hub genes and further analysis. Gene Expression Profiling and Interactive Analyses (GEPIA) and the Kaplan-Meier method were used to further validate the expression level of genes and plot the overall survivalcurve, respectively.

Results and disscussion

KEGG pathway analysis showed that the most important pathway was enriched in ECM-receptor interact

SUBMITTER: Darang E 

PROVIDER: S-EPMC10288990 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature