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Turnover Modulates the Need for a Cost of Resistance in Adaptive Therapy
Maximilian A R Strobl1,2, Jeffrey West3, Yannick Viossat4
1Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center, Tampa, Florida. maximilian.strobl@gmail.com alexander.anderson@moffitt.org.
Abstract:
Adaptive therapy seeks to exploit intratumoral competition to avoid, or at least delay, the emergence of therapy resistance in cancer. Motivated by promising results in prostate cancer, there is growing interest in extending this approach to other neoplasms. As such, it is urgent to understand the characteristics of a cancer that determine whether or not it will respond well to adaptive therapy. A plausible candidate for such a selection criterion is the fitness cost of resistance. In this article, we study a general, but simple, mathematical model to investigate whether the presence of a cost is necessary for adaptive therapy to extend the time to progression beyond that of a standard-of-care continuous therapy. Tumor cells were divided into sensitive and resistant populations and we model their competition using a system of two ordinary differential equations based on the Lotka-Volterra model. For tumors close to their environmental carrying capacity, a cost was not required. However, for tumors growing far from carrying capacity, a cost may be required to see meaningful gains. Notably, it is important to consider cell turnover in the tumor, and we discuss its role in modulating the impact of a resistance cost. To conclude, we present evidence for the predicted cost-turnover interplay in data from 67 patients with prostate cancer undergoing intermittent androgen deprivation therapy. Our work helps to clarify under which circumstances adaptive therapy may be beneficial and suggests that turnover may play an unexpectedly important role in the decision-making process. SIGNIFICANCE: Tumor cell turnover modulates the speed of selection against drug resistance by amplifying the effects of competition and resistance costs; as such, turnover is an important factor in resistance management via adaptive therapy.See related commentary by Strobl et al., p. 811.
Insights
Adaptive therapy can delay cancer progression by exploiting tumor cell competition. A resistance cost is not always necessary, but tumor cell turnover significantly impacts adaptive therapy effectiveness.
Area of Science:
- Oncology
- Mathematical Biology
- Cancer Research
Background:
- Adaptive therapy aims to delay cancer resistance by leveraging intratumoral competition.
- Prostate cancer research has shown promise, increasing interest in applying adaptive therapy to other cancers.
- Understanding factors predicting adaptive therapy response is crucial for its broader application.
Purpose of the Study:
- To investigate if a fitness cost of resistance is essential for adaptive therapy to prolong time to progression compared to continuous therapy.
- To explore the role of tumor cell turnover in modulating the impact of resistance costs.
Main Methods:
- A mathematical model using a Lotka-Volterra system of ordinary differential equations to simulate competition between sensitive and resistant tumor cell populations.
- Analysis of tumor dynamics under varying conditions of carrying capacity and resistance cost.
- Examination of patient data from 67 prostate cancer patients undergoing intermittent androgen deprivation therapy.
Main Results:
- A resistance cost was not required for adaptive therapy to outperform continuous therapy when tumors are near their carrying capacity.
- For tumors growing far from carrying capacity, a resistance cost may be necessary for significant benefits.
- Tumor cell turnover was found to modulate the effectiveness of resistance costs, amplifying their impact.
Conclusions:
- Adaptive therapy's benefit is context-dependent, influenced by tumor carrying capacity and the presence of a resistance cost.
- Tumor cell turnover plays a critical, often underestimated, role in managing drug resistance through adaptive therapy.
- Findings provide insights into optimizing adaptive therapy strategies and highlight the importance of considering cell turnover.
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