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Investigation of the Protein Interaction in the Metastatic Progression of Prostate Cancer to Bone Metastasis: A Computational Biology Approach
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Fereshteh Atabi *   , Mahdi Moassesfar , Parisa Fathi |
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Abstract: (8 Views) |
Background: Conventional diagnostic techniques for prostate cancer and its bone metastasis, such as PET scans and biopsies, are invasive and often result in delayed detection. This hampers timely therapeutic interventions, particularly for bone metastasis, which worsens patient outcomes. To address this challenge, our study aims to identify potential early biomarkers through proteomic profiling using in silico approaches.
Methods: We employed advanced in silico analysis, utilizing R software and Gene Ontology tools, to compare protein expression in metastatic bone tissues with their non-metastatic counterparts. We identified a set of proteins uniquely expressed in bone metastasis through differential expression analysis. These proteins were further analyzed for their roles in critical biological pathways related to cancer progression, with the goal of establishing a robust biomarker panel for early diagnosis.
Results: Our findings revealed key proteins that are pivotal in pathways linked to cell proliferation, immune modulation, and metastasis. Many of these proteins involved in carcinogenic signaling pathways were significantly altered in metastatic bone tissues, suggesting their potential as early diagnostic markers.
Conclusion: The identified protein panel underscores biomarkers strongly associated with bone metastasis in prostate cancer, providing a promising avenue for non-invasive early detection. By targeting these proteins, clinical diagnostics may be enhanced, improving patient prognosis through earlier therapeutic intervention. The novelty of this study lies in the discovery of the central role of the Complement and Coagulation cascades in prostate cancer bone metastasis, providing new avenues for non-invasive early diagnosis.
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| Keywords: Prostate Cancer, Bone Metastasis, Bioinformatics, Biomarker Panel, Early Diagnosis. |
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Full-Text [PDF 1948 kb]
(3 Downloads)
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Type of Study: Research |
Subject:
Signaling pathway of cancer cells
Received: 2025/06/30 | Accepted: 2025/10/16 | Published: 2024/08/20
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