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

TL;DR

This paper develops an optimal dosing strategy for anti-cancer treatments that accounts for drug-induced cell plasticity, balancing tumor cell kill and resistance development to improve treatment outcomes.

Contribution

It introduces a novel approach to optimize cancer therapy by steering tumor cell populations to a stable equilibrium considering non-genetic resistance mechanisms.

Findings

Optimal dosing balances cell kill and resistance induction.

Strategy ranges from continuous low dose to intermittent maximum dose.

Approach can be personalized using in vitro data.

Abstract

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 non-genetic drug-tolerant cell states, thereby accelerating the evolution of drug resistance. This confounds conventional high-dose treatment strategies aimed at maximal tumor reduction, since high doses can simultaneously promote non-genetic resistance. In this work, we study optimal dosing of anti-cancer treatment under drug-induced cell plasticity. We show that the optimal dosing strategy steers the tumor to a fixed equilibrium composition between sensitive and tolerant cells, while precisely balancing the trade-off between cell kill and tolerance induction. The optimal equilibrium strategy ranges from applying a low dose continuously to applying the maximum dose intermittently, depending on the dynamics of tolerance induction. We finally discuss how our approach can be integrated with in vitro data to derive patient-specific treatment insights.