Personalized prediction of PSA dynamics after external radiotherapy of prostate cancer

External beam radiation therapy is a widespread treatment for prostate cancer. The ensuing patient follow-up is based on the evolution of the prostate-specific antigen (PSA), which is an ubiquitous biomarker of prostate cancer measured in a blood test. Serum levels of PSA decay due to the radiation-induced death of tumor cells and cancer recurrence usually manifests as a rising PSA. 
The current definitions of biochemical relapse require that PSA reaches a minimum value (nadir) and starts increasing, which delays the use of further treatments. Also, these criteria for relapse do not account for the post-radiation tumor dynamics, which may contain early information to identify cancer recurrence. 
To address these issues, this project aims at developing new biomarkers for the early detection of PSA relapse after external beam radiation therapy based on biomechanistic mathematical models of tumor and PSA dynamics. 

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 838786.
Figure. Our mathematical models assume that serum PSA is proportional to the number of cancer cells in the patient's tumor. After each radiation dose, the cancerous cells either survive and continue proliferating, or are irreversibly damaged and ultimately die (left). We calibrate our models with PSA measurements from each patient. Then, the personalized model enables the prediction of PSA dynamics, which we validate against posterior observations of PSA. Additionally, we define model-based biomarkers of  biochemical relapse, and analyze their predictive performance in ROC analysis. Finally, we assess whether the proposed biomarkers can anticipate the detection of biochemical relapse based on the patient-specific model forecasts as compared to standard clinical methods.


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