Bioinformatics analysis identifies dysregulation of MiR-۵۴۸F-۳p and its hub gene in triple-negative breast cancer

  • سال انتشار: 1404
  • محل انتشار: مجله علوم پایه پزشکی ایران، دوره: 28، شماره: 4
  • کد COI اختصاصی: JR_IJBMS-28-4_004
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 100
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نویسندگان

Samira Behroozi

National Institute of Genetic Engineering and Biotechnology (NIGEB), Institute of Medical Biotechnology, Department of Medical Genetics, Tehran, Iran

Mahdieh Salimi

National Institute of Genetic Engineering and Biotechnology (NIGEB), Institute of Medical Biotechnology, Department of Medical Genetics, Tehran, Iran

Najaf Allahyari Fard

National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran

چکیده

Objective(s): Triple-negative breast cancer (TNBC), which affects ۱۵–۲۰% of cases, lacks targeted therapies and poses challenges in treatment. MicroRNAs (miRNAs) are potential biomarkers and therapeutic targets in breast cancer. To unravel its unique regulatory role, this study focused on miRNA microarray analysis, particularly miR-۵۴۸F-۳p, in TNBC samples.Materials and Methods: Using the GSE۷۶۲۷۵ dataset, gene expression profiles were analyzed using the Affymetrix Human Genome U۱۳۳ Plus ۲.۰ Array. Differentially expressed genes (DEGs) were identified using robust preprocessing. Weighted gene co-expression network analysis (WGCNA) explored gene modules and identified hub genes co-expressed with miR-۵۴۸F-۳p. Functional enrichment and protein-protein interaction (PPI) network analyses were conducted. Survival analysis was used to assess the prognostic impact of the identified genes.Results: The study found ۲۲۴ up-regulated DEGs, with miR-۵۴۸F-۳p exhibiting significant down-regulation. MultimiR identified ۴۰۰ genes that were targeted by miR-۵۴۸F-۳p. WGCNA revealed a blue co-expression module, with ۳۵۶ genes targeted by miR-۵۴۸F-۳p. A Venn diagram identified common genes, including VANGL۲, BRCC۳, ANP۳۲E, and ANLN. Functional enrichment highlighted crucial pathways in TNBC pathogenesis, including mitotic spindle organization, spindle assembly checkpoint signaling, cell cycle, and amino acid (serine) metabolism. PPI network analysis identified hub genes, including FOXM۱, KIF۲۳, and CDC۲۰. VANGL۲, BRCC۳, ANP۳۲E, and ANLN were significantly associated with patient outcomes in survival analysis.Conclusion: This analysis highlighted TNBC’s molecular landscape, emphasizing miR-۵۴۸F-۳p’s regulatory role. The identified genes, VANGL۲, BRCC۳, ANP۳۲E, and ANLN, offer insights into TNBC pathogenesis and potential therapeutic targets, laying the foundation for understanding their clinical implications in the intricate landscape of TNBC.

کلیدواژه ها

Computational biology, Gene expression profiling, microRNAs, Survival analysis, Triple negative breast - neoplasms

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