Patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse

Guillermo Lorenzo; Nadia di Muzio; Chiara Lucrezia Deantoni; Cesare Cozzarini; Andrei Fodor; Alberto Briganti; Francesco Montorsi; Víctor M Pérez-García; Hector Gomez; Alessandro Reali

doi:10.1016/j.isci.2022.105430

Patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse

iScience. 2022 Oct 25;25(11):105430. doi: 10.1016/j.isci.2022.105430. eCollection 2022 Nov 18.

Authors

Guillermo Lorenzo^{1

2}, Nadia di Muzio^{3

4}, Chiara Lucrezia Deantoni³, Cesare Cozzarini³, Andrei Fodor³, Alberto Briganti^{4

5}, Francesco Montorsi^{4

5}, Víctor M Pérez-García⁶, Hector Gomez^{7

8

9}, Alessandro Reali¹

Affiliations

¹ Department of Civil Engineering and Architecture, University of Pavia, via Ferrata 3, 27100 Pavia, Italy.
² Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, 201 E. 24th Street, Austin, TX 78712-1229, USA.
³ Department of Radiation Oncology, IRCCS San Raffaele Hospital and Scientific Institute, via Olgettina 60, 20132 Milan, Italy.
⁴ Vita-Salute San Raffaele University, via Olgettina 58, 20132 Milan, Italy.
⁵ Department of Urology, IRCCS San Raffaele Hospital and Scientific Institute, via Olgettina 60, 20132 Milan, Italy.
⁶ Mathematical Oncology Laboratory, University of Castilla-La Mancha, Edificio Politécnico, Avenida Camilo José Cela 3, 13071 Ciudad Real, Spain.
⁷ School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN 47907, USA.
⁸ Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, IN 47907, USA.
⁹ Purdue Center for Cancer Research, Purdue University, 201 S. University Street, West Lafayette, IN 47907, USA.

Abstract

The detection of prostate cancer recurrence after external beam radiotherapy relies on the measurement of a sustained rise of serum prostate-specific antigen (PSA). However, this biochemical relapse may take years to occur, thereby delaying the delivery of a secondary treatment to patients with recurring tumors. To address this issue, we propose to use patient-specific forecasts of PSA dynamics to predict biochemical relapse earlier. Our forecasts are based on a mechanistic model of prostate cancer response to external beam radiotherapy, which is fit to patient-specific PSA data collected during standard posttreatment monitoring. Our results show a remarkable performance of our model in recapitulating the observed changes in PSA and yielding short-term predictions over approximately 1 year (cohort median root mean squared error of 0.10-0.47 ng/mL and 0.13 to 1.39 ng/mL, respectively). Additionally, we identify 3 model-based biomarkers that enable accurate identification of biochemical relapse (area under the receiver operating characteristic curve > 0.80) significantly earlier than standard practice (p < 0.01).

Keywords: Biological sciences; Cancer; Oncology; Systems biology.