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Journals / Adıyaman Üniversitesi Sağlık Bilimleri Dergisi / 2026 / Cilt: 11 Sayı: 2

Integrative analysis of somatic mutations, gene expression, and co-expression networks in ERG-stratified prostate adenocarcinoma

ERG'ye göre sınıflandırılan prostat adenokarsinomunda somatik mutasyonlar, gen ekspresyonu ve ko-ekspresyon ağlarının entegre analizi

Perçin Pazarcı(ÇUKUROVA ÜNİVERSİTESİ, TIP FAKÜLTESİ, TEMEL TIP BİLİMLERİ BÖLÜMÜ, TIBBİ BİYOLOJİ ANABİLİM DALI)0000-0002-3708-0054
Pages
92–102
Publication Date
2025-08-30
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AI Summary & Key Takeaways

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

Conclusion: ERG status significantly shapes transcriptional and regulatory landscape of prostate cancer, offering potential targets for ERG-specific therapies.

📌 3 Key Takeaways

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Objective & Hypothesis:Aim: ERG overexpression driven by gene fusions is well-characterized event in prostate cancer, yet its impact on gene expression profiles and regulatory networks remains unclear.
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Key Findings & Data:This study aims to identify most frequently mutated 20 genes in prostate adenocarcinoma, compare their expression levels in ERG+ and ERG- tumors, and construct gene correlation networks to uncover ERG-dependent molecular interactions.
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Conclusion & Impact:Conclusion: ERG status significantly shapes transcriptional and regulatory landscape of prostate cancer, offering potential targets for ERG-specific therapies.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Prostat adenokarsinomu · ERG · Korelasyon ağı analizi

Abstract

Aim: ERG overexpression driven by gene fusions is well-characterized event in prostate cancer, yet its impact on gene expression profiles and regulatory networks remains unclear. This study aims to identify most frequently mutated 20 genes in prostate adenocarcinoma, compare their expression levels in ERG+ and ERG- tumors, and construct gene correlation networks to uncover ERG-dependent molecular interactions. Materials and Methods: RNA-seq and somatic mutation data from the TCGA-PRAD cohort were used. Most frequently mutated 20 genes were identified. Patients were grouped by ERG expression status. Differential expression analysis and gene co-expression network construction were performed for each subgroup. Results: TP53, SPOP, FOXA1, KMT2D, KDM6A, and MUC17 showed higher expression in ERG+ tumors, while TTN, LRP1B, PTEN, and RYR2 were more expressed in ERG- tumors. Network analysis revealed distinct regulatory patterns between subgroups. Conclusion: ERG status significantly shapes transcriptional and regulatory landscape of prostate cancer, offering potential targets for ERG-specific therapies.

Özet

Amaç: Gen füzyonlarına bağlı ERG aşırı ekspresyonu, prostat kanserinde iyi tanımlanmıştır; ancak gen ekspresyon profilleri ve düzenleyici ağlar üzerindeki etkisi net değildir. Bu çalışmanın amacı, prostat adenokarsinomunda en sık mutasyona uğrayan 20 geni belirlemek, bu genlerin ERG+ ve ERG− tümörlerdeki ekspresyon düzeylerini karşılaştırmak ve ERG'ye bağlı moleküler etkileşimleri ortaya koymak üzere korelasyon ağları oluşturmaktır. Gereç ve Yöntem: TCGA-PRAD kohortuna ait RNA-seq ve somatik mutasyon verileri kullanıldı. En sık mutasyona uğrayan 20 gen belirlendi. Hastalar ERG ekspresyon durumuna göre gruplandırıldı. Her alt grup için diferansiyel gen ekspresyon analizi ve gen ortak ekspresyon ağı analizi gerçekleştirildi. Bulgular: TP53, SPOP, FOXA1, KMT2D, KDM6A ve MUC17 genleri ERG+ tümörlerde daha yüksek düzeyde ekspresyon gösterirken, TTN, LRP1B, PTEN ve RYR2 genleri ERG− tümörlerde daha fazla ifade edildi. Ağ analizi, alt gruplar arasında farklı düzenleyici kalıpları ortaya koydu. Sonuç: ERG durumu, prostat kanserinin transkripsiyonel ve düzenleyici yapısını önemli ölçüde şekillendirir ve ERG'ye özgü tedavi hedefleri sunabilir.

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Cite This Article

Pazarcı, P. (2025). Integrative analysis of somatic mutations, gene expression, and co-expression networks in ERG-stratified prostate adenocarcinoma. Adıyaman Üniversitesi Sağlık Bilimleri Dergisi, Cilt: 11 Sayı: 2, 92–102. https://doi.org/10.30569/adiyamansaglik.1685370

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