Optimal dosing of anti-cancer treatment under drug-induced plasticity

While cancer has traditionally been considered a genetic disease, mounting evidence indicates an important role for non-genetic (epigenetic) mechanisms. Common anti-cancer drugs have recently been observed to induce the adoption of reversible drug-tolerant cell states, thereby accelerating the evolution of drug resistance. Determining how to optimally balance the competing goals of killing the tumor bulk and delaying resistance evolution in this scenario is a nontrivial question of high clinical importance. In this work, we use a combined mathematical and computational approach to study optimal dosing of anti-cancer drug treatment under drug-induced cell plasticity. Our results show that the optimal treatment steers the tumor into a fixed equilibrium composition while balancing the trade-off between cell kill and tolerance induction in a precisely quantifiable way. Under linear induction of tolerance, a low-dose constant strategy is optimal in equilibrium, while under uniform induction of tolerance, alternating between a large dose and no dose is best. The directionality of drug induction, whether the drug elevates transitions from sensitivity to tolerance or inhibits transitions back, significantly affects optimal dosing. To demonstrate the applicability of our approach, we use it to identify an optimal low-dose strategy for colorectal cancer using publicly available in vitro data.