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Updated: Oct 18, 2025

A Bioluminescent and Fluorescent Orthotopic Syngeneic Murine Model of Androgen-dependent and Castration-resistant Prostate Cancer
Published on: March 6, 2018
Computational modeling identifies multitargeted kinase inhibitors as effective therapies for metastatic,
Thomas Bello1,2, Claudia Paindelli3,4,5, Luis A Diaz-Gomez6
1Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109.
Abstract:
Castration-resistant prostate cancer (CRPC) is an advanced subtype of prostate cancer with limited therapeutic options. Here, we applied a systems-based modeling approach called kinome regularization (KiR) to identify multitargeted kinase inhibitors (KIs) that abrogate CRPC growth. Two predicted KIs, PP121 and SC-1, suppressed CRPC growth in two-dimensional in vitro experiments and in vivo subcutaneous xenografts. An ex vivo bone mimetic environment and in vivo tibia xenografts revealed resistance to these KIs in bone. Combining PP121 or SC-1 with docetaxel, standard-of-care chemotherapy for late-stage CRPC, significantly reduced tibia tumor growth in vivo, decreased growth factor signaling, and vastly extended overall survival, compared to either docetaxel monotherapy. These results highlight the utility of computational modeling in forming physiologically relevant predictions and provide evidence for the role of multitargeted KIs as chemosensitizers for late-stage, metastatic CRPC.
Insights
New kinase inhibitors show promise for advanced prostate cancer. Combining these with chemotherapy overcomes bone resistance, improving survival in castration-resistant prostate cancer (CRPC) models.
Area of Science:
- Oncology
- Computational Biology
- Pharmacology
Background:
- Castration-resistant prostate cancer (CRPC) represents an advanced stage of prostate cancer with significant unmet therapeutic needs.
- Current treatment options for CRPC are limited, necessitating the exploration of novel therapeutic strategies.
- Identifying effective multitargeted agents is crucial for improving patient outcomes.
Purpose of the Study:
- To utilize a systems-based modeling approach, kinome regularization (KiR), for the identification of novel multitargeted kinase inhibitors (KIs) against CRPC.
- To evaluate the efficacy of predicted KIs, PP121 and SC-1, in preclinical models of CRPC, including bone microenvironments.
- To assess the potential of combining KIs with docetaxel as a therapeutic strategy for advanced CRPC.
Main Methods:
- Application of kinome regularization (KiR) for the in silico identification of multitargeted kinase inhibitors.
- In vitro 2D cell culture and in vivo subcutaneous xenograft models to assess KI efficacy.
- Ex vivo bone mimetic environment and in vivo tibia xenograft models to evaluate bone metastasis and resistance.
- Combination therapy studies involving KIs (PP121, SC-1) and docetaxel in vivo.
Main Results:
- Two identified KIs, PP121 and SC-1, demonstrated efficacy in suppressing CRPC growth in vitro and in subcutaneous xenografts.
- Resistance to PP121 and SC-1 was observed in bone microenvironments, both ex vivo and in vivo.
- Combination therapy of PP121 or SC-1 with docetaxel significantly inhibited tibia tumor growth, reduced growth factor signaling, and extended survival in vivo.
- Docetaxel monotherapy showed less efficacy compared to the combination treatments.
Conclusions:
- Computational modeling, specifically KiR, is a valuable tool for predicting physiologically relevant therapeutic strategies.
- Multitargeted kinase inhibitors show potential as chemosensitizers, enhancing the efficacy of standard chemotherapy in late-stage, metastatic CRPC.
- Combining novel kinase inhibitors with docetaxel offers a promising therapeutic approach to overcome resistance and improve outcomes in CRPC, particularly in bone metastases.
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