Controlling Stochasticity in Epithelial-Mesenchymal Transition Through Multiple Intermediate Cellular States

Discrete and Continuous Dynamical Systems. Series B
Catherine Ha TaTian Hong

Abstract

Epithelial-mesenchymal transition (EMT) is an instance of cellular plasticity that plays critical roles in development, regeneration and cancer progression. Recent studies indicate that the transition between epithelial and mesenchymal states is a multi-step and reversible process in which several intermediate phenotypes might coexist. These intermediate states correspond to various forms of stem-like cells in the EMT system, but the function of the multi-step transition or the multiple stem cell phenotypes is unclear. Here, we use mathematical models to show that multiple intermediate phenotypes in the EMT system help to attenuate the overall fluctuations of the cell population in terms of phenotypic compositions, thereby stabilizing a heterogeneous cell population in the EMT spectrum. We found that the ability of the system to attenuate noise on the intermediate states depends on the number of intermediate states, indicating the stem-cell population is more stable when it has more sub-states. Our study reveals a novel advantage of multiple intermediate EMT phenotypes in terms of systems design, and it sheds light on the general design principle of heterogeneous stem cell population.

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Citations

Mar 11, 2020·PLoS Computational Biology·Hanah GoetzXiao-Jun Tian
Dec 19, 2018·Physical Biology·Yutong ShaQing Nie
Nov 15, 2018·IScience·Christopher RackauckasQing Nie
Aug 20, 2021·Communications Biology·Daniel R BergmanAdam L MacLean

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