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Phenotypic heterogeneity in cancer cells is widely observed and is oftenlinked to drug resistance. In several cases, such heterogeneity in drugsensitivity of tumors is driven by stochastic and reversible acquisition of adrug tolerant phenotype by individual cells even in an isogenic population.Accumulating evidence further suggests that cell-fate transitions such as theepithelial to mesenchymal transition (EMT) are associated with drug resistance.In this study, we analyze stochastic models of phenotypic switching to providea framework for analyzing cell-fate transitions such as EMT as a source ofphenotypic variability in drug sensitivity. Motivated by our cell-culture basedexperimental observations connecting phenotypic switching in EMT and drugresistance, we analyze a coarse-grained model of phenotypic switching betweentwo states in the presence of cytotoxic stress from chemotherapy. We deriveanalytical results for time-dependent probability distributions that provideinsights into the rates of phenotypic switching and characterize initialphenotypic heterogeneity of cancer cells. The results obtained can also shedlight on fundamental questions relating to adaptation and selection scenariosin tumor response to cytotoxic therapy.

Stochastic modeling of phenotypic switching and chemoresistance in cancer cell populations