Evolutionary rescue model informs strategies for driving cancer cell populations to extinction

The useful part

Schrider Cancers exhibit a remarkable ability to develop resistance to a range of treatments, often resulting in relapse following first-line therapies and significantly worse outcomes for subsequent treatments. Here, we present an evolutionary simulation model of a clonal population of cells that can acquire resistance mutations to one or more treatments. We conduct an in silico trial that reveals when and why a second strike will succeed or fail.

How it works

• While our understanding of the mechanisms and dynamics of the emergence of resistance during cancer therapy continues to advance, questions remain about how to minimize the probability that resistance will...
• We investigate how factors such as the timing of the switch between the two strikes, the rate of emergence of resistant mutations, the dose effects of the applied drugs, the presence of cross-resistance,...
• Our results show that the timing of switching to the second strike has a marked effect on the likelihood of driving the cancer to extinction, and that extinction therapy outperforms combination therapy when...
• Finally, we demonstrate that our conclusions hold whether we model resistance as a discrete trait or as a quantitative, multi-locus trait.

What to take from it

We leverage this model to examine the efficacy of a two-strike "extinction therapy" protocol, in which two treatments are applied sequentially to first contract the population to a vulnerable state and then push it to extinction, and compare it to a combination therapy protocol.