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

  • سال انتشار: 1402
  • محل انتشار: دوازدهمین همایش ملی و سومین همایش بین المللی بیوانفورماتیک
  • کد COI اختصاصی: IBIS12_159
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 84
دانلود فایل این مقاله

نویسندگان

Seyyed Mohammad Yaghoubi

Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran- Department of Animal Biology, Faculty of Natural Sciences, University of Tabriz, Tabriz, Iran

Mahdiyeh Azimi

Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran- Department of Animal Biology, Faculty of Natural Sciences, University of Tabriz, Tabriz, Iran

Sevda Ghoshouni

Tuberculosis and Lung Disease Research Center, Tabriz University of Medical Sciences, Tabriz, Iran

Alireza Emami

Department of Biochemistry and Molecular Medicine, Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, QC, Canada

Dariush Shanehbandi

Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran- Pharmaceutical Analysis Research Center, Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran

چکیده

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

مقالات مرتبط جدید

اطلاعات بیشتر در مورد COI

COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.

کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.