Integrative Network-Based Characterization of Serum Biomarker Interactions in Prostate Cancer Progression

Huriye Erbak Yılmaz; Zeynep Özel; Çiğdem Dinçkal; Oğuz Karalar; Zeynep Gülsüm Güç; Mustafa Dinçkal; Mustafa Agah Tekindal; Şerif Şentürk

Makale detayları

Integrative Network-Based Characterization of Serum Biomarker Interactions in Prostate Cancer Progression

Yazarlar:

Huriye Erbak Yılmaz | Zeynep Özel | Çiğdem Dinçkal | Oğuz Karalar | Zeynep Gülsüm Güç | Mustafa Dinçkal | Mustafa Agah Tekindal | Şerif Şentürk

Yayıncı:

Izmir Katip Celebi University

Ana Başlıklar:

Cerrahi Onkoloji | Üroloji | Metabolik Tıp | Tıbbi biyokimya - Proteinler | Peptitler ve Proteomik

Dergi:

Güncel Tıbbi Araştırmaları Dergisi Vol.5 Issue 2, pp.7-18

Belge Tipi:

Makale

Yayın Tarihi:

8/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001357682

pISSN:

2791-7061

Anahtar kelimeler:

Özet:

 Objective: This study investigates the interactions among key serum biomarkersHypoxia-inducible factor-1 alpha HIF-1α, Thrombospondin-1 TSP1, Neuropilin-1 NRP1, and Prostate-specific antigen PSAand clinical parameters including age at diagnosis, diabetes mellitus DM, hypertension HT, and smoking status in patients with metastatic prostate cancer mPCa. The objective was to identify structural and functional interdependencies among these variables using a network-based analytical approach. Materials and Methods: Network analysis was conducted using JASP software v0.19.3.0. Variables were modeled as nodes, and partial correlations between them as edges. Edge color represented the direction positive or negative of the correlation, while thickness indicated its strength. Network topology was evaluated using graph-theoretical metrics including degree, closeness, betweenness, and eigenvector centrality. Additional measures of density and sparsity were also calculated. Spatial visualization of the network was performed using the FruchtermanReingold algorithm. Results: The network comprised eight variables and 27 connections, yielding a sparsity value of 0.036, indicating a highly dense structure. PSA and TSP1 exhibited the highest betweenness centrality, serving as critical bridging nodes. HT and DM had high degree and closeness centrality values, reflecting central positions within the network. NRP1 displayed the highest clustering coefficient, suggesting a localized regulatory role. A strong negative association was observed between TSP1 and HT. Conclusion: This study highlights the utility of network analysis as a systems-level tool to explore complex biomarker interactions in mPCa. PSA, TSP1, and NRP1 emerged as key molecular regulators, while systemic conditions such as HT and DM significantly influenced network architecture. These findings warrant further validation through mechanistic and hypothesis-driven statistical studies.

 Objective: This study investigates the interactions among key serum biomarkersHypoxia-inducible factor-1 alpha HIF-1α, Thrombospondin-1 TSP1, Neuropilin-1 NRP1, and Prostate-specific antigen PSAand clinical parameters including age at diagnosis, diabetes mellitus DM, hypertension HT, and smoking status in patients with metastatic prostate cancer mPCa. The objective was to identify structural and functional interdependencies among these variables using a network-based analytical approach. Materials and Methods: Network analysis was conducted using JASP software v0.19.3.0. Variables were modeled as nodes, and partial correlations between them as edges. Edge color represented the direction positive or negative of the correlation, while thickness indicated its strength. Network topology was evaluated using graph-theoretical metrics including degree, closeness, betweenness, and eigenvector centrality. Additional measures of density and sparsity were also calculated. Spatial visualization of the network was performed using the FruchtermanReingold algorithm. Results: The network comprised eight variables and 27 connections, yielding a sparsity value of 0.036, indicating a highly dense structure. PSA and TSP1 exhibited the highest betweenness centrality, serving as critical bridging nodes. HT and DM had high degree and closeness centrality values, reflecting central positions within the network. NRP1 displayed the highest clustering coefficient, suggesting a localized regulatory role. A strong negative association was observed between TSP1 and HT. Conclusion: This study highlights the utility of network analysis as a systems-level tool to explore complex biomarker interactions in mPCa. PSA, TSP1, and NRP1 emerged as key molecular regulators, while systemic conditions such as HT and DM significantly influenced network architecture. These findings warrant further validation through mechanistic and hypothesis-driven statistical studies.

 Objective: This study investigates the interactions among key serum biomarkersHypoxia-inducible factor-1 alpha HIF-1α, Thrombospondin-1 TSP1, Neuropilin-1 NRP1, and Prostate-specific antigen PSAand clinical parameters including age at diagnosis, diabetes mellitus DM, hypertension HT, and smoking status in patients with metastatic prostate cancer mPCa. The objective was to identify structural and functional interdependencies among these variables using a network-based analytical approach. Materials and Methods: Network analysis was conducted using JASP software v0.19.3.0. Variables were modeled as nodes, and partial correlations between them as edges. Edge color represented the direction positive or negative of the correlation, while thickness indicated its strength. Network topology was evaluated using graph-theoretical metrics including degree, closeness, betweenness, and eigenvector centrality. Additional measures of density and sparsity were also calculated. Spatial visualization of the network was performed using the FruchtermanReingold algorithm. Results: The network comprised eight variables and 27 connections, yielding a sparsity value of 0.036, indicating a highly dense structure. PSA and TSP1 exhibited the highest betweenness centrality, serving as critical bridging nodes. HT and DM had high degree and closeness centrality values, reflecting central positions within the network. NRP1 displayed the highest clustering coefficient, suggesting a localized regulatory role. A strong negative association was observed between TSP1 and HT. Conclusion: This study highlights the utility of network analysis as a systems-level tool to explore complex biomarker interactions in mPCa. PSA, TSP1, and NRP1 emerged as key molecular regulators, while systemic conditions such as HT and DM significantly influenced network architecture. These findings warrant further validation through mechanistic and hypothesis-driven statistical studies.

 Amaç: Bu çalışma, metastatik prostat kanseri mPK hastalarında Hipoksiye duyarlı faktör-1 alfa HIF-1α, Trombospondin-1 TSP1, Nöropilin-1 NRP1 ve Prostat spesifik antijen PSA gibi temel serum biyobelirteçleri ile tanı yaşı, diyabetes mellitus, hipertansiyon ve sigara kullanımı gibi klinik parametreler arasındaki etkileşimleri ağ tabanlı analitik bir yaklaşımla değerlendirmeyi amaçlamaktadır. Gereç ve Yöntemler: Analiz, JASP yazılımı v0.19.3.0 ile gerçekleştirilmiştir. Değişkenler düğüm node, kısmi korelasyonlar ise kenar edge olarak modellenmiştir. Kenar renkleri ilişkinin yönünü pozitifnegatif, kalınlıkları ise ilişkinin gücünü göstermektedir. Ağ yapısı; derece, yakınlık, aradalık ve özvektör merkezilik gibi grafik kuramı temelli ölçütlerle değerlendirilmiş; yoğunluk ve seyreklik değerleri hesaplanmıştır. Düğümlerin konumlandırılmasında FruchtermanReingold algoritması kullanılmıştır. Bulgular: Toplam sekiz değişken ve 27 bağlantıdan oluşan ağın seyreklik değeri 0,036 olarak bulunmuştur; bu da yoğun bir yapı olduğunu göstermektedir. PSA ve TSP1 en yüksek aradalık merkezilik değerleriyle köprü rolü üstlenmiştir. Hipertansiyon ve diyabet, yüksek derece ve yakınlık merkezilik değerleriyle ağın merkezinde yer almıştır. NRP1 en yüksek kümeleme katsayısına sahip olup lokal bir düzenleyici rol üstlenmektedir. TSP1 ile hipertansiyon arasında güçlü negatif bir ilişki gözlenmiştir. Sonuç: Bu çalışma, metastatik prostat kanserinde biyobelirteçler arası ilişkilerin sistem düzeyinde anlaşılmasında ağ analizinin etkili bir yöntem olduğunu ortaya koymaktadır. PSA, TSP1 ve NRP1 önemli moleküler düzenleyiciler olarak öne çıkarken; hipertansiyon ve diyabetes mellitus gibi sistemik hastalıklar ağ yapısının bütünlüğü üzerinde belirgin rol oynamaktadır. Bulguların mekanistik ve istatistiksel çalışmalarla doğrulanması gerekmektedir.

Makale detayları

Integrative Network-Based Characterization of Serum Biomarker Interactions in Prostate Cancer Progression

Yazarlar:

Huriye Erbak Yılmaz | Zeynep Özel | Çiğdem Dinçkal | Oğuz Karalar | Zeynep Gülsüm Güç | Mustafa Dinçkal | Mustafa Agah Tekindal | Şerif Şentürk

Yayıncı:

Izmir Katip Celebi University

Ana Başlıklar:

Cerrahi Onkoloji | Üroloji | Metabolik Tıp | Tıbbi biyokimya - Proteinler | Peptitler ve Proteomik

Dergi:

Güncel Tıbbi Araştırmaları Dergisi Vol.5 Issue 2, pp.7-18

Belge Tipi:

Makale

Yayın Tarihi:

8/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001357682

pISSN:

2791-7061

Prostate Cancer

Serum biomarkers

Network analysis

Thrombospondin-1

Neuropilin-1

Hypoxia-inducible factor-1 alpha

Hypoxia-inducible factor-1 alphaProstat kanseri

Serum biyobelirteçleri

Ağ analizi

Trombospondin-1

Nöropilin-1

Hipoksiye duyarlı faktör-1 alfa

Sayı

Makale detayları

Yazarlar: Huriye Erbak Yılmaz | Zeynep Özel | Çiğdem Dinçkal | Oğuz Karalar | Zeynep Gülsüm Güç | Mustafa Dinçkal | Mustafa Agah Tekindal | Şerif Şentürk

Yayıncı: Izmir Katip Celebi University

Ana Başlıklar: Cerrahi Onkoloji | Üroloji | Metabolik Tıp | Tıbbi biyokimya - Proteinler | Peptitler ve Proteomik

Dergi: Güncel Tıbbi Araştırmaları Dergisi Vol.5 Issue 2, pp.7-18

Belge Tipi: Makale

Yayın Tarihi: 8/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001357682

pISSN: 2791-7061

Sayı

Yazarlar:

Huriye Erbak Yılmaz | Zeynep Özel | Çiğdem Dinçkal | Oğuz Karalar | Zeynep Gülsüm Güç | Mustafa Dinçkal | Mustafa Agah Tekindal | Şerif Şentürk

Yayıncı:

Izmir Katip Celebi University

Ana Başlıklar:

Cerrahi Onkoloji | Üroloji | Metabolik Tıp | Tıbbi biyokimya - Proteinler | Peptitler ve Proteomik

Dergi:

Güncel Tıbbi Araştırmaları Dergisi Vol.5 Issue 2, pp.7-18

Belge Tipi:

Makale

Yayın Tarihi:

8/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001357682

pISSN:

2791-7061