The logic of containing tumors

Abstract

Challenging the paradigm of the maximum tolerated dose, recent studies have shown that a strategy aiming for containment, not elimination, can control tumor burden more effectively in vitro, in mouse models, and in the clinic. These outcomes are consistent with the hypothesis that emergence of resistance to cancer therapy may be prevented or delayed by exploiting competitive ecological interactions between drug-sensitive and resistant tumor cell subpopulations. However, although various mathematical and computational models have been proposed to explain the superiority of particular containment strategies, this evolutionary approach to cancer therapy lacks a rigorous theoretical foundation. Here we combine extensive mathematical analysis and numerical simulations to establish general conditions under which a containment strategy is expected to control tumor burden more effectively than applying the maximum tolerated dose. We show that when resistant cells are present, an idealized strategy of containing a tumor at a maximum tolerable size maximizes time to treatment failure (that is, the time at which tumor burden becomes intolerable). These results are very general and do not depend on any fitness cost of resistance. We further provide formulas for predicting the clinical benefits attributable to containment strategies in a wide range of scenarios, and we compare outcomes of theoretically optimal treatments with those of more practical protocols. Our results strengthen the rationale for clinical trials of evolutionarily-informed cancer therapy.

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].…”

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

“…). As Hansen et al[8] and Viossat and Noble[32] show, if one accounts for potential de novo resistance acquisition, this high burden can generate situations in which maintaining a pool of sensitive cells can in fact accelerate the emergence of the resistant population. Investigating the risks associated with the higher average tumour burden under adaptive therapy is an important area of future research.…”

Understanding the potential benefits of adaptive therapy for metastatic melanoma

“…This criterion was implemented in the first clinical trial of adaptive therapy for castrateresistant prostate cancer (20). Would a less aggressive treatment stop criterion be better as suggested by more recent models (27,28,34)? We simulated a suite of adaptive therapy simulations with a new stopping criterion of 20% reduction to address this question.…”

“…Strobl et al showed how the turnover rate of cancer cells within the tumor influences benefits derived from adaptive therapy (27). More general and deeper mathematical analysis by Viossat and Noble predict the clinical benefits of tumor containment therapy (28).…”