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Stochastic state transitions give rise to phenotypic equilibrium in populations of cancer cells
Authors:Gupta Piyush B  Fillmore Christine M  Jiang Guozhi  Shapira Sagi D  Tao Kai  Kuperwasser Charlotte  Lander Eric S
Institution:1 Broad Institute, Cambridge, MA 02142, USA
2 Department of Anatomy and Cellular Biology, Sackler School of Graduate Biomedical Sciences, Tufts University School of Medicine, 136 Harrison Avenue, Boston, MA 02111, USA
3 Molecular Oncology Research Institute, Tufts Medical Center, Boston, MA 02111, USA
4 Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
5 Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
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.
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