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      Stochastic state transitions give rise to phenotypic equilibrium in populations of cancer cells.

      Cell
      Animals, Breast Neoplasms, pathology, Female, Flow Cytometry, Gene Expression Profiling, Humans, Markov Chains, Mice, Mice, Inbred NOD, Mice, SCID, Neoplasm Transplantation, Neoplastic Stem Cells, Stochastic Processes, Transplantation, Heterologous

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          Abstract

          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. Copyright © 2011 Elsevier Inc. All rights reserved.

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