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Regan2022 - Mechanosensitive EMT model

ABSTRACT: This file contains a 136-node modular Boolean network model of EMT triggered by biomechanical and growth signaling crosstalk, linked to a published network of epithelial contact inhibition, proliferation, and apoptosis (MODEL2006170001). This model reproduces the ability of the core EMT transcriptional network to maintain distinct epithelial, hybrid E/M and mesenchymal states, as well as EMT driven by mitogens such as EGF on stiff ECM. We also reproduce the observed lack of stepwise MET, in that our model's dynamics does not pass through the hybrid E/M state during MET. We show that in the absence of strong autocrine signals such as TGFβ (not included in this version), cells cannot maintain their mesenchymal state in the absence of mitogens, on softer matrices, or at high cell density.

SUBMITTER: Erzsébet Ravasz Regan

PROVIDER: MODEL2208050001 | BioModels | 2023-12-13

REPOSITORIES: BioModels

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			Action	DRS
	MODEL2208050001?filename=EMT_Mechanosensing.sbml	Other
	MODEL2208050001?filename=EMT_Mechanosensing_Supplementary_Table.pdf	Pdf

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Publications

Boolean modeling of mechanosensitive epithelial to mesenchymal transition and its reversal.

Sullivan Emmalee E Harris Marlayna M Bhatnagar Arnav A Guberman Eric E Zonfa Ian I Ravasz Regan Erzsébet E

iScience 20230302 4

The significance of biophysical modulators of the epithelial to mesenchymal transition (EMT) is demonstrated by experiments that document full EMT on stiff, nano-patterned substrates in the absence of biochemical induction. Yet, current models focus on biochemical triggers of EMT without addressing its mechanosensitive nature. Here, we built a Boolean model of EMT triggered by mechanosensing - mitogen crosstalk. Our model reproduces epithelial, hybrid E/M and mesenchymal phenotypes, the role of ...[more]

PMID: 36968076

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