Characterizing Phenotypic Dynamics of Chemoresistance in Breast Cancer Cells

Despite the continuing advancements in chemotherapy for breast cancer, the development of chemoresistance remains a significant cause of treatment failure. Intratumoral and inter-patient heterogeneity pose critical challenges to designing patient-specific optimized treatment plans. We posit that a mathematical understanding of chemoresistance dynamics could be key to developing clinically-feasible, successful treatment regimens. In this study, we develop a model that describes the effects of a standard neoadjuvant drug (doxorubicin) on a common breast cancer cell line (MCF7). We assume that the tumor is composed of two subpopulations: drug-resistant cells, which continue proliferating after treatment, and drug-sensitive cells, which gradually transition from proliferating to treatment-induced death. The model is calibrated with time-resolved microscopy data including variations in drug concentration, inter-treatment interval, and number of doses. Our results show that the model can recapitulate tumor growth dynamics in all of these scenarios (CCC>0.95). We observe that higher dosages resulted in significantly lower drug-resistant fraction and proliferation rates (p<0.05). Our results also show superior tumor control with a higher number of doses and shorter inter-treatment intervals (p<0.05). Thus, we believe that our model may contribute to our understanding of doxorubicin action and may guide the selection of therapeutic regimens that achieve optimal tumor control.