{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["10(9)"],"submitter":["Eskandarion MR"],"funding":["Tehran University of Medical Sciences Cancer Research Center"],"pubmed_abstract":["<h4>Background & aim</h4>The histologic and molecular changes from intestinal metaplasia (IM) to gastric cancer (GC) have not been fully characterized. The present study sought to identify potential alterations in signaling pathways in IM and GC to predict disease progression; these alterations can be considered therapeutic targets.<h4>Materials & methods</h4>Seven gene expression profiles were selected from the GEO database. Discriminate differentially expressed genes (DEGs) were analyzed by EnrichR. The STRING database, Cytoscape, Gene Expression Profiling Interactive Analysis (GEPIA), cBioPortal, NetworkAnalyst, MirWalk database, OncomiR, and bipartite miRNA‒mRNA correlation network was used for downstream analyses of selected module genes.<h4>Results</h4>Analyses revealed that extracel"],"journal":["Heliyon"],"pagination":["e30253"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11088262"],"repository":["biostudies-literature"],"pubmed_title":["Prediction of novel biomarkers for gastric intestinal metaplasia and gastric adenocarcinoma using bioinformatics analysis."],"pmcid":["PMC11088262"],"pubmed_authors":["Eskandarion MR","Mahmoodzadeh H","Eskandarieh S","Shirkoohi R","Shahi F","Oghabian MA","Shakoori Farahani A"],"additional_accession":[]},"is_claimable":false,"name":"Prediction of novel biomarkers for gastric intestinal metaplasia and gastric adenocarcinoma using bioinformatics analysis.","description":"<h4>Background & aim</h4>The histologic and molecular changes from intestinal metaplasia (IM) to gastric cancer (GC) have not been fully characterized. The present study sought to identify potential alterations in signaling pathways in IM and GC to predict disease progression; these alterations can be considered therapeutic targets.<h4>Materials & methods</h4>Seven gene expression profiles were selected from the GEO database. Discriminate differentially expressed genes (DEGs) were analyzed by EnrichR. The STRING database, Cytoscape, Gene Expression Profiling Interactive Analysis (GEPIA), cBioPortal, NetworkAnalyst, MirWalk database, OncomiR, and bipartite miRNA‒mRNA correlation network was used for downstream analyses of selected module genes.<h4>Results</h4>Analyses revealed that extracel","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 May","modification":"2026-06-03T06:47:37.314Z","creation":"2026-05-29T03:06:10.635Z"},"accession":"S-EPMC11088262","cross_references":{"pubmed":["38737262"],"doi":["10.1016/j.heliyon.2024.e30253"]}}