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Journals / Interdisciplinary Medical Journal / 2026 / Volume: 17 Issue: 58

Analysis of gene expression to explore the contribution of cancer-associated fibroblasts to breast cancer progression: a computational analysis

Nail Beşli(SAĞLIK BİLİMLERİ ÜNİVERSİTESİ, HAMİDİYE TIP FAKÜLTESİ, TEMEL TIP BİLİMLERİ BÖLÜMÜ, TIBBİ BİYOLOJİ ANABİLİM DALI)0000-0002-6174-915X
Nilufer Ercin(SAĞLIK BİLİMLERİ ÜNİVERSİTESİ, HAMİDİYE TIP FAKÜLTESİ, TEMEL TIP BİLİMLERİ BÖLÜMÜ, TIBBİ BİYOLOJİ ANABİLİM DALI)0000-0003-0137-4963
Bahar Sarikamis Johnson(Department of Medical Biology, Faculty of Medicine, Istanbul Atlas University, Istanbul, Türkiye)0000-0003-4407-3829
Ulkan Celik(Department of Medical Biology, Faculty of Medicine, Istanbul Atlas University, Istanbul, Türkiye)0000-0002-6895-8560
Pages
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Publication Date
2026-08-23
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Conclusion: This findings suggest that critical genes such as ESR1, MET, IL1B, SMAD3, and FOS are predicted to contribute to CAF-mediated regulatory networks in breast cancer.

📌 3 Key Takeaways

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Objective & Hypothesis:Objective: Cancer-associated fibroblasts (CAFs) are critical components of the tumor microenvironment that greatly influence breast cancer progression.
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Key Findings & Data:Results: In CAFs, 940 genes were upregulated, and 561 genes were downregulated.
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Conclusion & Impact:Conclusion: This findings suggest that critical genes such as ESR1, MET, IL1B, SMAD3, and FOS are predicted to contribute to CAF-mediated regulatory networks in breast cancer.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Breast cancer · Cancer-associated fibroblasts · Differentially expressed genes

Abstract

Objective: Cancer-associated fibroblasts (CAFs) are critical components of the tumor microenvironment that greatly influence breast cancer progression. In this study, we used in silico analysis to determine the potential pathways and genes that could affect breast cancer progression associated with CAFs. Method: Data from breast cancer patients, collected through microarray and next-generation sequencing (NGS), were retrieved using the Gene Expression Omnibus (GEO) platform. The differentially expressed genes (DEGs) were determined and further analyzed through Gene Ontology (GO) and pathway analysis, and potential therapeutic targets were predicted via hub genes. Results: In CAFs, 940 genes were upregulated, and 561 genes were downregulated. These genes were significantly linked to pathways such as MAPK signaling, estrogen signaling, NF-kB signaling, IL-17 signaling, and TGF-ß signaling. These pathways suggest that CAFs are involved in the progression of breast cancer. The hub genes, namely ESR1, MET, IL1B, SMAD3, and FOS, were found to be enriched in key pathways and were associated with certain anti-tumor drugs that are either undergoing clinical trials or have been approved for clinical use. Conclusion: This findings suggest that critical genes such as ESR1, MET, IL1B, SMAD3, and FOS are predicted to contribute to CAF-mediated regulatory networks in breast cancer.

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Cite This Article

Beşli, N., Ercin, N., Johnson, B. S., Celik, U. (2026). Analysis of gene expression to explore the contribution of cancer-associated fibroblasts to breast cancer progression: a computational analysis. Interdisciplinary Medical Journal, Volume: 17 Issue: 58. https://doi.org/10.17944/interdiscip.1828109

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