Integrated bioinformatics analysis for differentially expressed genes and signaling pathways identification in gastric cancer.

ABSTRACT: Background: Gastric cancer (GC) has a high mortality rate in cancer-related deaths worldwide. Currently, the pathogenesis of gastric cancer progression remains unclear. Here, we identified several vital candidate genes related to gastric cancer development and revealed the potential pathogenic mechanisms using integrated bioinformatics analysis. Methods: Two microarray datasets from Gene Expression Omnibus (GEO) database integrated. Limma package was used to analyze differentially expressed genes (DEGs) between GC and matched normal specimens. DAVID was utilized to conduct Gene ontology (GO) and KEGG enrichment analysis. The relative expression of OLFM4, IGF2BP3, CLDN1 and MMP1were analyzed based on TCGA database provided by UALCAN. Western blot and quantitative real time PCR

SUBMITTER: Yang C 

PROVIDER: S-EPMC7797537 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature