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Background: Bone metastasis is the most frequent complication in prostate cancer patients and associated outcome remains fatal. Radium223 (Rad223), a bone targeting radioisotope improves overall survival in patients (3.6 months vs. placebo). However, clinical response is often followed by relapse and disease progression, and associated mechanisms of efficacy and resistance are poorly understood. Research efforts to overcome this gap require a substantial investment of time and resources. Computational models, integrated with experimental data, can overcome this limitation and drive research in a more effective fashion.
Methods: Accordingly, we developed a predictive agent-based model of prostate cancer bone metastasis progression and response to Rad223 as an agile platform to maximize its efficacy. The driving coefficients were calibrated on ad hoc experimental observations retrieved from intravital microscopy and the outcome further validated, in vivo.
Results: In this work we offered a detailed description of our data-integrated computational infrastructure, tested its accuracy and robustness, quantified the uncertainty of its driving coefficients, and showed the role of tumor size and distance from bone on Rad223 efficacy. In silico tumor growth, which is strongly driven by its mitotic character as identified by sensitivity analysis, matched in vivo trend with 98.3% confidence. Tumor size determined efficacy of Rad223, with larger lesions insensitive to therapy, while medium- and micro-sized tumors displayed up to 5.02 and 152.28-fold size decrease compared to control-treated tumors, respectively. Eradication events occurred in 65 ± 2% of cases in micro-tumors only. In addition, Rad223 lost any therapeutic effect, also on micro-tumors, for distances bigger than 400 μm from the bone interface.
Conclusions: This model has the potential to be further developed to test additional bone targeting agents such as other radiopharmaceuticals or bisphosphonates.
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http://dx.doi.org/10.1186/s12885-020-07084-w | DOI Listing |
BMC Urol
September 2025
Department of Radiology, Osaka Proton Therapy Clinic, 1-27-9 Kasugade naka, Osaka konohana-ku, Osaka, 554-0022, Japan.
Int Urol Nephrol
September 2025
Department of Urology, Brigham and Women's Hospital, Harvard Medical School, 45 Francis St, ASB II-3, Boston, MA, 02115, USA.
Background: With the advancement of MR-based imaging, prostate cancer ablative therapies have seen increased interest to reduce complications of prostate cancer treatment. Although less invasive, they do carry procedural risks, including rectal injury. To date, the medicolegal aspects of ablative therapy remain underexplored.
View Article and Find Full Text PDFBr J Cancer
September 2025
Institute of Life Sciences, Bhubaneswar, Odisha, India.
Background: Docetaxel is the most common chemotherapy regimen for several neoplasms, including advanced OSCC (Oral Squamous Cell Carcinoma). Unfortunately, chemoresistance leads to relapse and adverse disease outcomes.
Methods: We performed CRISPR-based kinome screening to identify potential players of Docetaxel resistance.
Prostate Cancer Prostatic Dis
September 2025
Department of Urology, University of California Irvine, Irvine, CA, USA.
Eur Urol Focus
September 2025
Department of Urology, Medical Centre, University of Heidelberg, Heidelberg, Germany; Department of Urology, Medical Faculty Carl Gustav Carus, TU Dresden, Dresden, Germany; Department of Urology, Philipps-University Marburg, Marburg, Germany.
Background And Objective: Since 2016, >21 000 patients with prostate cancer (PC) used our personalized online decision aid in routine care in Germany. We analyzed the effects of this online decision aid for men with nonmetastatic PC in a randomized controlled trial.
Methods: In the randomized controlled EvEnt-PCA trial, 116 centers performed 1:1 allocation of 1115 patients with nonmetastatic PC to use an online decision aid (intervention = I) or a printed brochure (control = C).