Cancer cells within individual tumors often exist in distinct phenotypic states that differ in functional attributes. While cancer cell populations typically display distinctive equilibria in the proportion of cells in various states, the mechanisms by which this occurs are poorly understood. Here, we study the dynamics of phenotypic proportions in human breast cancer cell lines. We show that subpopulations of cells purified for a given phenotypic state return towards equilibrium proportions over time. These observations can be explained by a Markov model in which cells transition stochastically between states. A prediction of this model is that, given certain conditions, any subpopulation of cells will return to equilibrium phenotypic proportions over time. A second prediction is that breast cancer stem-like cells arise de novo from non-stem-like cells. These findings contribute to our understanding of cancer heterogeneity and reveal how stochasticity in single-cell behaviors promotes phenotypic equilibrium in populations of cancer cells.

Non-small-cell lung cancers (NSCLCs), the most common lung cancers, are known to have diverse pathological features. During the past decade, in-depth analyses of lung cancer genomes and signalling pathways have further defined NSCLCs as a group of distinct diseases with genetic and cellular heterogeneity. Consequently, an impressive list of potential therapeutic targets was unveiled, drastically altering the clinical evaluation and treatment of patients. Many targeted therapies have been developed with compelling clinical proofs of concept; however, treatment responses are typically short-lived. Further studies of the tumour microenvironment have uncovered new possible avenues to control this deadly disease, including immunotherapy.