Modeling of mouse experiments suggests that optimal anti-hormonal treatment for breast cancer is diet-dependent

TL;DR

This study develops a mathematical model based on mouse experiment data to explore how high-fat diets influence the effectiveness of anti-hormonal breast cancer treatments, highlighting diet as a crucial factor in therapy outcomes.

Contribution

It introduces the first model integrating diet, drug resistance, and optimal control to evaluate anti-hormonal treatment strategies for breast cancer.

Findings

High-fat diet alters tumor growth response to treatment.

Model predicts differential outcomes based on diet and resistance.

Diet should be considered in clinical treatment planning.

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.