Discovering the Secrets of Gastric Cancer: Key Genes and Interaction Networks Revealed Through Bioinformatics

Gastric cancer (GC), with a death rate of ۳۲.۲ (۹۵% CI: ۲۹.۱-۳۵.۳) and ۱۶.۳ (۹۵% CI: ۱۳.۹-۱۸.۶) in northwestern Iran (Ardabil), casts a long shadow with high mortality rates both in Iran and inthe world [۱]. Using bioinformatics, this study identifies differentially expressed genes (DEGs) thatmay help understand GC involving genes.We analyzed gene expression profiles from normal tissue and GC tissue samples using the GeneExpression Omnibus (GEO) data set GSE۱۸۴۳۳۶. Results were evaluated using QC measures andDESeq۲ analysis, with an adjusted p-value threshold of ۰.۰۵, to identify ۲۷۸ DEGs that may playpotential roles in GC development. Data was further analyzed using R software, including visualizationusing volcano plots generated with the ggplot۲ and principal component analysis (PCA) using the"prcomp" function in R.This bioinformatics study evaluated GC gene expression, identifying ۹۶ DEGs with potential roles inGC development. Strikingly, ۷۱.۸% of these DEGs were categorized as signal peptides, suggesting apotential focus on cellular secretion and communication. Transcription factor analysis furtherhighlighted the significance of the NFIC family (۲۹%), alongside the involvement of ONECUT۱,RREB۱, HOXB۴, ARID۳A, and MEF۲A families. Additionally, Gene Ontology (GO) enrichmentanalysis revealed enrichment of "ECM structural constituents" (۱۲.۵%%, p < ۰.۰۰۱), implicating genescrucial for maintaining the extracellular matrix. Other enriched GO terms included "Metallopeptidaseactivity", "Cell adhesion molecule activity", and "Chemokine activity", emphasizing diverse functionalroles of the identified DEGs. Finally, network analysis uncovered ۲۷۸ interacting genes, visualizedusing Cytoscape, providing insights into potential GC-associated molecular interactions.Bioinformatics identified GC gene expression patterns. Further investigation of the identified DEGsenriched in specific functional categories could unlock novel therapeutic targets, benefiting thosebattling this disease.

کلیدواژه ها:

Gastric cancer ، DEGs ، bioinformatics ، gene interaction ، big data