Understanding the potential benefits of adaptive therapy for metastatic melanoma

Abstract

Adaptive therapy is an evolution-based treatment approach that aims to maintain tumor volume by employing minimum effective drug doses or timed drug holidays. For successful adaptive therapy outcomes, it is critical to find the optimal timing of treatment switch points. Mathematical models are ideal tools to facilitate adaptive therapy dosing and switch time points. We developed two different mathematical models to examine interactions between drug-sensitive and resistant cells in a tumor. The first model assumes genetically fixed drug-sensitive and resistant populations that compete for limited resources. Resistant cell growth is inhibited by sensitive cells. The second model considers phenotypic switching between drug-sensitive and resistant cells. We calibrated each model to fit melanoma patient biomarker changes over time and predicted patient-specific adaptive therapy schedules. Overall, the models predict that adaptive therapy would have delayed time to progression by 6-25 months compared to continuous therapy with dose rates of 6%-74% relative to continuous therapy. We identified predictive factors driving the clinical time gained by adaptive therapy. The first model predicts 6-20 months gained from continuous therapy when the initial population of sensitive cells is large enough, and when the sensitive cells have a large competitive effect on resistant cells. The second model predicts 20-25 months gained from continuous therapy when the switching rate from resistant to sensitive cells is high and the growth rate of sensitive cells is low. This study highlights that there is a range of potential patient specific benefits of adaptive therapy, depending on the underlying mechanism of resistance, and identifies tumor specific parameters that modulate this benefit.

Feasibility of an Evolutionary Tumor Board for Generating Novel Personalized Therapeutic Strategies

“…By removing therapy while there is still a high frequency and density of sensitive cells, these sensitive cells effectively compete with and therefore suppress the resistant cancer cells. Adaptive therapy is an important and active area of evolutionary therapy research 16,17,19,[21][22][23][24][25][26][27][28][29][30][31][32] that can encompass multiple drugs 31,32 and has already been considered for some ETB patients.…”

Spatial structure impacts adaptive therapy by shaping intra-tumoral competition

“…A final, important caveat is that we have not explicitly modelled the mechanism by which resistance arises. Depending on whether it arises through mutation, phenotypic switching, or is environmentally induced, this may drive different initial distributions of resistant cells, and will also result in different dynamics during treatment due to de novo resistance acquisition (see also [16,19,51,63]). Furthermore, our model cannot explain how some of the initial tumour compositions we have analysed would have arisen prior to treatment.…”