A spatial cell culture model for predicting chemotherapy dosing strategies

Predicting patient responses to chemotherapy regimens is a major challenge in cancer treatment. To do this requires quantitative mathematical models to predict optimal dose and frequency for a particular drug, and experimental model systems such as three-dimensional organoids that accurately recapitulate the tumor microenvironment and heterogeneity. However, tracking the spatial dynamics of multiple cell types in three-dimensions can be a significant challenge in terms of time and throughput. Here we develop a two-dimensional system that allows for simple tracking of cell populations via fluorescence microscopy for modeling spatial dynamics in tumors. We first develop multiple 4T1 breast cancer cell lines resistant to varying concentrations of doxorubicin, and demonstrate how well mixed and spatially heterogeneous populations expand in a two-dimensional colony. We subject cell populations to varied dose and frequency of chemotherapy and measure colony growth radius and populations. We then build a mathematical model to describe the dynamics of both chemosensitive and chemoresistant populations, where we determine which number of doses can produce the smallest tumor size based on parameters in the system. In the future, this system can be adapted to quickly optimize dosing strategies in the setting of heterogeneous cell types or patient derived cells with varied chemoresistance.