Turnover modulates the need for a cost of resistance in adaptive therapy

Journal article

Adaptive therapy seeks to exploit intra-tumoral 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 which 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 paper, 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 prostate cancer patients 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.

Authors: Strobl, M; West, J; Viossat, Y; Damaghi, M; Robertson-Tessi, M

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: American Association for Cancer Research
• Journal: Cancer Research
• Volume: 81
• Issue: 4
• Pages: 1135-1147
• Publication date: 2020-11-10
• Acceptance date: 2020-10-23
• DOI: 10.1158/0008-5472.CAN-20-0806
• EISSN: 1538-7445
• ISSN: 0008-5472
• Language: English
• Keywords: computational methods; FFR; palliative care; drug resistance; chemotherapy