Modeling breast cancer proliferation, drug synergies, and alternating therapies

Estrogen receptor positive (ER+) breast cancer is responsive to a number of targeted therapies used clinically. Unfortunately, the continuous application of targeted therapy often results in resistance, driving the consideration of combination and alternating therapies. Toward this end, we developed a mathematical model that can simulate various mono, combination, and alternating therapies for ER + breast cancer cells at different doses over long time scales. The model is used to look for optimal drug combinations and predicts a significant synergism between Cdk4/6 inhibitors in combination with the anti-estrogen fulvestrant, which may help explain the clinical success of adding Cdk4/6 inhibitors to anti-estrogen therapy. Furthermore, the model is used to optimize an alternating treatment protocol so it works as well as monotherapy while using less total drug dose. [Display omitted] •Dynamic model of proliferation in response to anticancer therapies in breast cancer•Experimental verification of synergy between an anti-estrogen and CDK4/6 inhibitor•Optimizing alternating therapy protocols to limit proliferation and drug dosage Mathematical biosciences; Computational bioinformatics; Pharmacoinformatics; Cancer systems biology; Cancer