Evolutionary implications of phenotype switching for growth and survival of tumors in stochastic environments

Abstract

Tumors evolve under constantly changing microenvironmental conditions, and a key major mechanism by which cancer cells adapt to fluctuating environments is stochastic phenotypic switch via epithelial–mesenchymal plasticity (EMP). Here we demonstrate the existence of EMP in human breast epithelial cell lines and assess the fitness of E and M cells in environments that fluctuate between favorable and harsh conditions. We then develop a theoretical framework for analysis of tumor evolution with E-M stochastic phenotypic switch that integrates the behaviors of E and M cells. We characterize the outcomes of tumor evolution via three characteristic times describing i) tumor growth, ii) phenotypic adaptation and iii) fluctuations of the environment. We identify a tradeoff between tumor growth and survival, with different phenotype switching rates maximizing each of these objectives. An anticancer therapeutic strategy is proposed based on tumor survival analysis, revealing that blocking mesenchymal to epithelial transition, rather than epithelial to mesenchymal transition, is critical under fluctuating conditions. Thus, this study elucidates fundamental evolutionary mechanisms of tumor phenotypic adaptation in fluctuating environments with potentially important clinical implications. SIGNIFICANCE Tumors evolve under constantly changing environmental conditions, to which they adapt primarily via epithelial-mesenchymal plasticity. However, the impact of fluctuating environment on tumor growth and phenotypic composition remains elusive. We developed a mathematical model of tumor growth under fluctuating conditions with stochastic phenotypic epithelial-mesenchymal switch as the main mechanism of adaptation. Motivated by experimentally observed differences in the growth of epithelial and mesenchymal cells under variable conditions, the model reveals non-trivial evolutionary outcomes, depending on the relative time scales of the underlying processes, reminiscent of the Parrondo’s Paradox in game theory. Based on the model analysis, an optimal therapeutic strategy is proposed, with the mesenchymal-epithelial transition identified as the critical target.