Optimal dosing of anti-cancer treatment under drug-induced plasticity
Einar Bjarki Gunnarsson1,2, Benedikt Vilji Magnússon3, Jasmine Foo4
1Division of Applied Mathematics, Science Institute, University of Iceland, Reykjavik, Iceland. ebg@hi.is.
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.
Insights
This study reveals that optimal cancer treatment involves balancing cell kill and resistance by managing non-genetic drug tolerance. The best dosing strategy, whether continuous low dose or intermittent high dose, depends on how quickly cells become tolerant.
Area of Science:
- Cancer Biology
- Epigenetics
- Mathematical Oncology
Background:
- Cancer is increasingly recognized as involving non-genetic (epigenetic) mechanisms alongside genetic factors.
- Conventional high-dose cancer treatments can paradoxically promote non-genetic drug tolerance, accelerating drug resistance.
- This necessitates a re-evaluation of treatment strategies that account for drug-induced cell plasticity.
Purpose of the Study:
- To investigate optimal anti-cancer treatment dosing strategies considering drug-induced cell plasticity and non-genetic resistance.
- To determine how to balance tumor cell kill with the induction of drug tolerance.
- To explore the development of patient-specific treatment insights.
Main Methods:
- Mathematical modeling of anti-cancer treatment dynamics.
- Analysis of tumor evolution under varying drug dosing regimens.
- Investigating the trade-off between direct cell kill and the promotion of drug-tolerant states.
Main Results:
- Optimal dosing strategies can establish a stable equilibrium between drug-sensitive and drug-tolerant cancer cells.
- The ideal strategy balances immediate tumor reduction with the long-term management of resistance.
- Optimal dosing can range from continuous low-dose to intermittent high-dose therapy, contingent on tolerance induction rates.
Conclusions:
- Conventional high-dose strategies may be suboptimal due to promoting non-genetic resistance.
- A dynamic equilibrium approach to dosing can effectively manage cancer treatment and resistance.
- Integrating this model with experimental data can personalize cancer therapy.
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