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

Abstract

Control and conquer" -this is the philosophy behind adaptive therapy, which seeks to exploit intra-tumoural competition to avoid, or at least, delay the emergence of therapy resistance in cancer. Motivated by promising results from theoretical, experimental and, most recently, a clinical study in prostate cancer, there is an increasing interest in extending this approach to other cancers. As such, it is urgent to understand the characteristics of a cancer which determine whether it will respond well to adaptive therapy, or not. A plausible candidate for such a selection criterion is the fitness cost of resistance. In this 1 paper, we study a simple competition model between sensitive & resistant cell populations to investigate whether the presence of a cost is a necessary condition for adaptive therapy to extend the time to progression beyond that of a standard-of-care continuous therapy. We find that for tumours close to their environmental carrying capacity such a cost of resistance is not required. However, for tumours growing far from carrying capacity, a cost may be required to see meaningful gains. Notably, we show that in such cases it is important to consider the cell turnover in the tumour and we discuss its role in modulating the impact of a cost of resistance. Overall, 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.

Spatial structure impacts adaptive therapy by shaping intra-tumoral competition

“…We have shown that high initial tumour cell density, and low initial resistance fractions, maximise the benefit of adaptive therapy, assuming a cure is not possible. This prediction is consistent with previous non-spatial [11,15,16,18,22,33] and spatial theoretical studies [11,19], and experimental evidence in cancer [11] and bacteria [34].…”

“…In Figure A2a we illustrate, for one parameter combination, how the thus obtained 10 outcome distributions for each value of n become almost indistinguishable for n ≥ 250. To quantify consistency if resistance is prevalent prior to treatment, will result in longer tumour control, and matches the results obtained for non-spatial models [15,16,22]. Note though that we are not taking into account possible risks associated with the higher tumour burden under the 30% threshold algorithm.…”

“…To understand the impact of space we compare the agent-based model to the following ODE model which we have studied previously in [22]:…”

“…We previously showed in a non-spatial model that high tumour cell turnover rates may increase the benefits of adaptive therapy [22]. To test whether this prediction holds true if spatial interactions are taken into account, we repeat our analysis from the previous section with a cell turnover rate of 30% relative to the proliferation rate, which is the value we previously estimated for prostate cancer [22]. For simplicity, we assume the same death rate for both sensitive and resistant cells and that dead cells are immediately removed from the domain.…”

The logic of containing tumors

“…In contrast, lowering K r or increasing β increases both absolute and relative clinical gains, because it harms resistant cells proportionally more in the presence of sensitive cells. Some of these effects are illustrated in Figure 4 (see also complementary analyses in [18,34]).…”