Computational reactive-diffusive modeling for stratification and prognosis determination of patients with breast cancer receiving Olaparib.

Francesco Schettini, Maria Valeria De Bonis, Carla Strina, Manuela Milani, Nicoletta Ziglioli, Sergio Aguggini, Ignazio Ciliberto, Carlo Azzini, Giuseppina Barbieri, Valeria Cervoni, Maria Rosa Cappelletti, Giuseppina Ferrero, Marco Ungari, Mariavittoria Locci, Ida Paris, Giovanni Scambia, Gianpaolo Ruocco, Daniele Generali

Journal: Scientific reports 2023;13(1):11951

PMID: 37488154

Abstract

Mathematical models based on partial differential equations (PDEs) can be exploited to handle clinical data with space/time dimensions, e.g. tumor growth challenged by neoadjuvant therapy. A model based on simplified assessment of tumor malignancy and pharmacodynamics efficiency was exercised to discover new metrics of patient prognosis in the OLTRE trial. We tested in a 17-patients cohort affected by early-stage triple negative breast cancer (TNBC) treated with 3 weeks of olaparib, the capability of a PDEs-based reactive-diffusive model of tumor growth to efficiently predict the response to olaparib in terms of SUV detected at FDG-PET/CT scan, by using specific terms to characterize tumor diffusion and proliferation. Computations were performed with COMSOL Multiphysics. Driving parameters governing the mathematical model were selected with Pearson's correlations. Discrepancies between actual and computed SUV values were assessed with Student's t test and Wilcoxon rank sum test. The correlation between post-olaparib true and computed SUV was assessed with Pearson's r and Spearman's rho. After defining the proper mathematical assumptions, the nominal drug efficiency (ε) and tumor malignancy (r) were computationally evaluated. The former parameter reflected the activity of olaparib on the tumor, while the latter represented the growth rate of metabolic activity as detected by SUV. ε was found to be directly dependent on basal tumor-infiltrating lymphocytes (TILs) and Ki67% and was detectable through proper linear regression functions according to TILs values, while r was represented by the baseline Ki67-to-TILs ratio. Predicted post-olaparib SUV* did not significantly differ from original post-olaparib SUV in the overall, gBRCA-mutant and gBRCA-wild-type subpopulations (p > 0.05 in all cases), showing strong positive correlation (r = 0.9 and rho = 0.9, p < 0.0001 both). A model of simplified tumor dynamics was exercised to effectively produce an upfront prediction of efficacy of 3-week neoadjuvant olaparib in terms of SUV. Prospective evaluation in independent cohorts and correlation of these outcomes with more recognized efficacy endpoints is now warranted for model confirmation and tailoring of escalated/de-escalated therapeutic strategies for early-TNBC patients.

© 2023. The Author(s).

Address: Medical Oncology Department, Hospital Clinic of Barcelona, C. Villaroel 170, 08036, Barcelona, Spain. [email protected].; Translational Genomics and Targeted Therapies in Solid Tumors, August Pi I Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain. [email protected].; Faculty of Medicine, University of Barcelona, Barcelona, Spain. [email protected].; Department for Sustainable Food Process, Università Cattolica del Sacro Cuore, Piacenza, Italy.; Department of Medicine, Surgery and Health Sciences, Cattinara Hospital, University of Trieste, Strada di Fiume 447, 34149, Trieste, Italy.; UO Anatomia Patologica ASST di Cremona, Cremona, Italy.; Department of Neuroscience, Reproductive Sciences and Dentistry, University of Naples Federico II, Naples, Italy.; Department of Woman and Child Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.; Department of Woman and Child Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.; Università Cattolica del Sacro Cuore, Rome, Italy.; Modeling and Prototyping Laboratory, College of Engineering, University of Basilicata, Potenza, Italy.; Department of Medicine, Surgery and Health Sciences, Cattinara Hospital, University of Trieste, Strada di Fiume 447, 34149, Trieste, Italy. [email protected].; Multidisciplinary Unit of Breast Pathology and Translational Research, Cremona Hospital, Cremona, Italy. [email protected].
Bant logo

© Copyright 2026, Nutrition Evidence

NED wishes to thank the following organisations for their support:

We use cookies to improve your experience and analyze site traffic with Google Analytics. By continuing to use our site, you agree to our use of cookies. Learn more.