ArticleDiscrete and continuous dynamical systems. Series B2016
Controlling Stochasticity in Epithelial-Mesenchymal Transition Through Multiple Intermediate Cellular States.
Article in Discrete and continuous dynamical systems. Series B, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Data- and theory-driven approaches for understanding paths of epithelial-mesenchymal transition.Genesis (New York, N.Y. : 2000) · 2024Review
- Modeling the effects of EMT-immune dynamics on carcinoma disease progression.Communications biology · 2021Article
- Inference and multiscale model of epithelial-to-mesenchymal transition via single-cell transcriptomic data.Nucleic acids research · 2020Article
- A plausible accelerating function of intermediate states in cancer metastasis.PLoS computational biology · 2020Article
- Inference of Intercellular Communications and Multilayer Gene-Regulations of Epithelial-Mesenchymal Transition From Single-Cell Transcriptomic Data.Frontiers in genetics · 2020Article
- Investigating epithelial-to-mesenchymal transition with integrated computational and experimental approaches.Physical biology · 2019Review
- An enriched network motif family regulates multistep cell fate transitions with restricted reversibility.PLoS computational biology · 2019Article
- Intermediate cell states in epithelial-to-mesenchymal transition.Physical biology · 2019Review
- Combinatorial perturbation analysis reveals divergent regulations of mesenchymal genes during epithelial-to-mesenchymal transition.NPJ systems biology and applications · 2019Article
- Integrative Transcriptomic Analysis Reveals a Multiphasic Epithelial-Mesenchymal Spectrum in Cancer and Non-tumorigenic Cells.Frontiers in oncology · 2019Article
- Exploring intermediate cell states through the lens of single cells.Current opinion in systems biology · 2018Article
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Corrections and comments
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Authors and funding
3 authors.
Funding
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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Registered trials
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