Speaker
Description
Drug resistance is an ongoing problem for maintaining a treatment response in advanced cancers, which are often more heterogeneous and evolvable. Evolvability may be beneficial if lesions can easily respond to large shifts in the microenvironment by modifying their traits to survive, like how metastases can survive a new environment and even thrive despite treatment applications. However, evolvability may also be a detriment. With too much deviation from the parental phenotype, cells lose important functions necessary to survive. So, is there an optimal rate of evolvability for tumors to grow and survive treatment that can be exploited therapeutically?
We use an off-lattice agent-based model to investigate how the rate of change through proliferation-migration phenotype space affects tumor growth and response to treatment. During growth, both proliferation and migration are advantageous traits. Increasing migration allows cells to distribute spatially, which allows more proliferation by lessening the spatial competition, and increasing proliferation allows for faster turnover and more mutation. More evolvability leads to more heterogeneity and faster recurrence under treatment. But when evolvability is costly, tumor survival depends on the rate and jump size of heritable changes to transiently lose proliferation fitness selected for during growth and gain resistance for survival. We consider how to design treatment strategies based on a tumor’s evolvability dynamics.
