ArticleClinical & experimental metastasis2014
Improving treatment strategies for patients with metastatic castrate resistant prostate cancer through personalized computational modeling.
Article in Clinical & experimental metastasis, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed.
- Next-generation osteosarcoma models for precision medicine.Communications biology · 2026Review
- Overcoming vascular niche-mediated TKI resistance in acute myeloid leukemia through miR-126 inhibition.NPJ systems biology and applications · 2026Article
- The bone ecosystem facilitates multiple myeloma relapse and the evolution of heterogeneous drug resistant disease.Nature communications · 2024Article
- Education and Outreach in Physical Sciences in Oncology.Trends in cancer · 2021Article
- Hybrid modeling frameworks of tumor development and treatment.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Optimal control to reach eco-evolutionary stability in metastatic castrate-resistant prostate cancer.PloS one · 2020Article
- Optimizing Cancer Treatment Using Game Theory: A Review.JAMA oncology · 2019Review
- Emerging and Established Models of Bone Metastasis.Cancers · 2018Review
- Fractionated follow-up chemotherapy delays the onset of resistance in bone metastatic prostate cancer.Games · 2018Article
- Drug Repositioning for Effective Prostate Cancer Treatment.Frontiers in physiology · 2018Review
- Homeostasis Back and Forth: An Ecoevolutionary Perspective of Cancer.Cold Spring Harbor perspectives in medicine · 2017Review
- Predictive computational modeling to define effective treatment strategies for bone metastatic prostate cancer.Scientific reports · 2016Article
- Developing multi-target therapeutics to fine-tune the evolutionary dynamics of the cancer ecosystem.Frontiers in pharmacology · 2015Article
- Assessing Combinational Drug Efficacy in Cancer Cells by Using Image-based Dynamic Response Analysis.Cancer informatics · 2015Article
- Current and emerging therapies for bone metastatic castration-resistant prostate cancer.Cancer control : journal of the Moffitt Cancer Center · 2015Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Metastatic castrate resistant prostate cancer (mCRPC) is responsible for the majority of prostate cancer deaths with the median survival after diagnosis being 2 years. The metastatic lesions often arise in the skeleton, and current treatment options are primarily palliative. Using guidelines set forth by the National Comprehensive Cancer Network (NCCN), the medical oncologist has a number of choices available to treat the metastases. However, the sequence of those treatments is largely dependent on the patient history, treatment response and preferences. We posit that the utilization of personalized computational models and treatment optimization algorithms based on patient specific parameters could significantly enhance the oncologist's ability to choose an optimized sequence of available therapies to maximize overall survival. In this perspective, we used an integrated team approach involving clinicians, researchers, and mathematicians, to generate an example of how computational models and genetic algorithms can be utilized to predict the response of heterogeneous mCRPCs in bone to varying sequences of standard and targeted therapies. The refinement and evolution of these powerful models will be critical for extending the overall survival of men diagnosed with mCRPC.
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Registered trials
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