Prostate-specific antigen dynamics predict individual responses to intermittent androgen deprivation

Area of Science:

• Oncology
• Mathematical Biology
• Cancer Research

Background:

• Intermittent androgen deprivation therapy (IADT) is a viable strategy for biochemically recurrent prostate cancer (PCa), aiming to reduce cumulative toxicity.
• Prostate-specific antigen (PSA) dynamics during IADT can reflect underlying tumor evolution, including the enrichment of prostate cancer stem-like cells (PCaSCs).

Purpose of the Study:

• To simulate PSA dynamics and PCaSC enrichment during IADT to understand resistance evolution.
• To develop a predictive model for patient-specific resistance to IADT.
• To assess the feasibility of using mathematical models to guide adaptive clinical trial designs.

Main Methods:

• Mathematical modeling of PSA dynamics and PCaSC proliferation.
• Correlation of simulated PCaSC patterns with longitudinal PSA measurements from 70 PCa patients.
• Leave-one-out cross-validation to evaluate model prediction accuracy for resistance evolution.

Main Results:

• Simulated PCaSC proliferation patterns showed correlation with patient PSA measurements.
• The model achieved 89% accuracy (73% sensitivity, 91% specificity) in predicting patient-specific resistance evolution.
• Model simulations identified patients who could benefit from concurrent docetaxel during IADT based on early response dynamics.

Conclusions:

• Mathematical modeling of intratumoral evolutionary dynamics offers a powerful tool for predicting resistance to IADT in prostate cancer.
• Patient-specific models can guide adaptive clinical trials, potentially optimizing treatment strategies like concurrent docetaxel administration.
• This approach holds promise for personalizing prostate cancer therapy and improving treatment efficacy.