Modeling of mouse experiments suggests that optimal anti-hormonal treatment for breast cancer is diet-dependent
Matlab codes and data to reproduce the results and figures in the preprint published in Bulletin of Mathematical Biology (https://doi.org/10.1007/s11538-023-01253-1). In each folder, the file main_X.m must be run.
Author list: Tuğba Akman, Lisa M. Arendt, Jürgen Geisler, Vessela N. Kristensen, Arnoldo Frigessi and Alvaro Köhn-Luque.
Abstract: Estrogen receptor positive breast cancer is frequently treated with anti-hormonal treatment such as aromatase inhibitors (AI). Interestingly, a high body mass index has been shown to have a negative impact on AI efficacy, most likely due to disturbances in steroid metabolism and adipokine production. Here, we propose a mathematical model based on a system of ordinary differential equations to investigate the effect of high-fat diet on tumor growth. We inform the model with data from mouse experiments, where the animals are fed with high-fat or control (normal) diet. By incorporating AI treatment with drug resistance into the model and by solving optimal control problems we found differential responses for control and high-fat diet. To the best of our knowledge, this is the first attempt to model optimal anti-hormonal treatment for breast cancer in the presence of drug resistance. Our results underline the importance of considering high-fat diet and obesity as factors influencing clinical outcomes during anti-hormonal therapies in breast cancer patients.