Computational Drug Repositioning for Gastric Cancer using Reversal Gene Expression Profiles.

ABSTRACT: Treatment of gastric cancer (GC) often produces poor outcomes. Moreover, predicting which GC treatments will be effective remains challenging. Computational drug repositioning using public databases is a promising and efficient tool for discovering new uses for existing drugs. Here we used a computational reversal of gene expression approach based on effects on gene expression signatures by GC disease and drugs to explore new GC drug candidates. Gene expression profiles for individual GC tumoral and normal gastric tissue samples were downloaded from the Gene Expression Omnibus (GEO) and differentially expressed genes (DEGs) in GC were determined with a meta-signature analysis. Profiles drug activity and drug-induced gene expression were downloaded from the ChEMBL and the LINCS databases, r

SUBMITTER: Kim IW 

PROVIDER: S-EPMC6389943 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature