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Journals / Doğu Karadeniz Sağlık Bilimleri Dergisi / 2026 / Cilt: 4 Sayı: 3 Özel Sayı

Exploring Bladder, Prostate, and Endometrial Cancer Risk in RRMS Patients: ATM, CREB1, and miR-19b-3p are Shared Biomarkers

RRMS Hastalarında Mesane, Prostat ve Endometrial Kanser Riskinin Araştırılması: ATM, CREB1 ve miR-19b-3p Ortak Biyobelirteçler

Tuba Denkçeken(SANKO ÜNİVERSİTESİ)0000-0002-4663-5410
Elif Onur(SANKO ÜNİVERSİTESİ)0000-0002-1690-3170
Pages
247–264
Publication Date
2025-09-30
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AI Summary & Key Takeaways

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

This study highlights biomarkers in RRMS patients that may contribute to an increased risk of these cancers.

📌 3 Key Takeaways

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Objective & Hypothesis:Aim: Relapsing-remitting multiple sclerosis (RRMS) is the most common phenotype of MS.
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Key Findings & Data:GEO2R was applied to analyze datasets, and DEGs and DEMs were classified based on fold change.
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Conclusion & Impact:This study highlights biomarkers in RRMS patients that may contribute to an increased risk of these cancers.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:RRMS · BLCA · PRAD

Abstract

Aim: Relapsing-remitting multiple sclerosis (RRMS) is the most common phenotype of MS. Bladder urothelial cancer (BLCA) is a highly prevalent malignancy of the urinary system. Prostate adenocarcinoma (PRAD) is the leading cause of cancer-related morbidity and mortality in males. Uterine corpus endometrial carcinoma (UCEC) is a prevalent malignancy in females. Identifying the risk of BLCA, PRAD, and UCEC in RRMS patients is crucial. This study aims to identify potential biomarkers that pose a risk for BLCA, PRAD, and UCEC in RRMS patients and have a common role. Materials and Methods: Expression profiles of RRMS patients were obtained from the GEO and ArrayExpress databases. Differentially expressed miRNAs (DEMs) and mRNAs (DEGs) were identified using the Principal Component Analysis (PCA)-based Unsupervised-Feature-Extraction (UFE) method. GEO2R was applied to analyze datasets, and DEGs and DEMs were classified based on fold change. Target genes of up/downregulated DEMs were identified, and common gene clusters with corresponding up/downregulated DEGs were determined. Further bioinformatics analyses were conducted to identify hub-miRNAs and hub-genes. Results: 321 control and 293 RRMS samples were analyzed. DEMs and DEGs were identified using both the PCA-based UFE and GEO2R, and their intersections were determined. Target genes of DEMs were selected based on validation and prediction in at least two databases. Negatively correlated target genes of up/downregulated DEMs were identified, and common gene clusters were established. STRING analysis was performed, and a negative regulatory network was constructed using Cytoscape. Validation of hub-genes and hub-miRNAs in BLCA, PRAD, and UCEC was conducted using UALCAN and OncomiR. Discussion: Decreased ATM and CREB1 have been identified as direct targets of hsa-miR-19b-3p. They were identified as potential biomarkers in RRMS and further validated in BLCA, PRAD, and UCEC. This study highlights biomarkers in RRMS patients that may contribute to an increased risk of these cancers.

Özet

Amaç: Relapsing-remitting multipl skleroz (RRMS), MS'in en yaygın fenotipidir. Mesane ürotelyal kanseri (BLCA), üriner sistemin oldukça yaygın bir malignitesidir. Prostat adenokarsinomu (PRAD), erkeklerde kanserle ilişkili morbidite ve mortalitenin önde gelen nedenidir. Uterin korpus endometriyal karsinomu (UCEC), kadınlarda yaygın bir malignitedir. RRMS hastalarında BLCA, PRAD ve UCEC riskini belirlemek çok önemlidir. Bu çalışma, RRMS hastalarında BLCA, PRAD ve UCEC için risk oluşturan ve ortak bir role sahip olan potansiyel biyobelirteçleri belirlemeyi amaçlamaktadır. Yöntem: RRMS hastalarının ekspresyon profilleri GEO ve ArrayExpress veritabanlarından elde edildi. Diferansiyel ekprese miRNA'lar (DEM'ler) ve mRNA'lar (DEG'ler), Temel Bileşen Analizi (PCA) tabanlı Denetimsiz Özellik Çıkarımı (UFE) yöntemi kullanılarak belirlendi. GEO2R veri kümelerini analiz etmek için uygulandı ve DEG'ler ve DEM'ler kat değişimine göre sınıflandırıldı. Yukarı/aşağı düzenlenmiş DEM'lerin hedef genleri tanımlandı ve karşılık gelen yukarı/aşağı düzenlenmiş DEG'lere sahip ortak gen kümeleri belirlendi. Hub-miRNA'ları ve hub-genleri tanımlamak için ileri biyoenformatik analizler yapıldı. Bulgular: 321 kontrol ve 293 RRMS örneği analiz edildi. DEM'ler ve DEG'ler hem PCA tabanlı UFE hem de GEO2R kullanılarak tanımlandı ve kesişimleri belirlendi. DEM'lerin hedef genleri en az iki veritabanındaki doğrulama ve tahmine göre seçildi. Yukarı/aşağı düzenlenmiş DEM'lerin negatif korelasyonlu hedef genleri belirlendi ve ortak gen kümeleri oluşturuldu. STRING analizi yapıldı ve Cytoscape kullanılarak negatif düzenleyici bir ağ oluşturuldu. BLCA, PRAD ve UCEC'deki hub-genlerin ve hub-miRNA'ların doğrulaması UALCAN ve OncomiR kullanılarak gerçekleştirildi. Sonuç: Azalmış ATM ve CREB1, hsa-miR-19b-3p'nin doğrudan hedefleri olarak tanımlanmıştır. Bunlar RRMS'de potansiyel biyobelirteçler olarak tanımlanmış ve BLCA, PRAD ve UCEC'de valide edilmiştir. Bu çalışma, RRMS hastalarında bu kanserlerin artma riskine katkıda bulunabilecek biyobelirteçleri vurgulamaktadır.

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Cite This Article

Denkçeken, T., Onur, E. (2025). Exploring Bladder, Prostate, and Endometrial Cancer Risk in RRMS Patients: ATM, CREB1, and miR-19b-3p are Shared Biomarkers. Doğu Karadeniz Sağlık Bilimleri Dergisi, Cilt: 4 Sayı: 3 Özel Sayı, 247–264. https://doi.org/10.59312/ebshealth.1722327

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