Deconstructing the Contributions of Heterogeneity to Combination Treatment of Hormone-Sensitive Breast Cancer

Abstract

AbstractCombination therapies are fundamental to cancer treatments, including in breast cancer, which is the most common invasive malignancy in women. Breast cancer treatment is determined based on molecular subtypes. Since 2016, combination palbociclib and fulvestrant has been used to treat hormone receptor-positive breast cancer. However, the impact of heterogeneity of the tumor landscape and tumor composition dynamics on scheduling decisions remains poorly understood. To elucidate the contributions of variability at multiple scales to treatment outcomes in hormone receptor-positive breast cancer, we developed a simple mathematical model of two unique estrogen receptor-positive (ER$$+$$ + ) breast cancer cell types and their responses to combination treatment with palbociclib and fulvestrant. We used this model to understand how the initial fraction of either cell type may impact the fraction remaining after treatment and examined how heterogeneity in pharmacokinetics and pharmacodynamics results in a large distribution of outcomes. Our results suggest that the pharmacokinetics and pharmacodynamics of fulvestrant were the major drivers of final tumor size and composition. We then leveraged our model to guide therapeutic scheduling of combination palbociclib and fulvestrant, demonstrating the use of mathematical modeling to improve our understanding of cancer biology and treatments.