PT  - JOURNAL ARTICLE
AU  - Wei He
AU  - Diane M. Demas
AU  - Ayesha N. Shajahan-Haq
AU  - William T. Baumann
TI  - Modeling Breast Cancer Proliferation, Drug Synergies, and Alternating Therapies
AID  - 10.1101/2022.09.20.508795
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.09.20.508795
4099  - http://biorxiv.org/content/early/2022/09/22/2022.09.20.508795.short
4100  - http://biorxiv.org/content/early/2022/09/22/2022.09.20.508795.full
AB  - 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. Mathematical modeling of the dynamics of cancer cell drug responses can help find better therapies that not only hold proliferation in check but also potentially stave off resistance. 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. Lastly, the model is used to optimize an alternating treatment protocol that works as well as monotherapy while using less total drug dose.Competing Interest StatementThe authors have declared no competing interest.