Epigenetic feedback and stochastic partitioning during cell division can drive resistance to EMT
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Wen Jia1,2, Shubham Tripathi1,3,4, Priyanka Chakraborty5, Adithya Chedere6, Annapoorni Rangarajan5,6, Herbert Levine1,4 and Mohit Kumar Jolly5
1 Center for Theoretical Biological Physics, Rice University, Houston, TX, USA
2 Department of Physics and Astronomy, Rice University, Houston, TX, USA
3 PhD Program in Systems, Synthetic, and Physical Biology, Rice University, Houston, TX, USA
4 Department of Physics, Northeastern University, Boston, MA, USA
5 Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India
6 Department of Molecular Reproduction, Development and Genetics, Indian Institute of Science, Bangalore, India
|Mohit Kumar Jolly,||email:||email@example.com|
Keywords: epithelial-mesenchymal transition; mesenchymal-epithelial transition; GRHL2; epigenetics; asymmetric cell division
Received: May 02, 2020 Accepted: June 01, 2020 Published: July 07, 2020
Epithelial-mesenchymal transition (EMT) and its reverse process mesenchymal-epithelial transition (MET) are central to metastatic aggressiveness and therapy resistance in solid tumors. While molecular determinants of both processes have been extensively characterized, the heterogeneity in the response of tumor cells to EMT and MET inducers has come into focus recently, and has been implicated in the failure of anti-cancer therapies. Recent experimental studies have shown that some cells can undergo an irreversible EMT depending on the duration of exposure to EMT-inducing signals. While the irreversibility of MET, or equivalently, resistance to EMT, has not been studied in as much detail, evidence supporting such behavior is slowly emerging. Here, we identify two possible mechanisms that can underlie resistance of cells to undergo EMT: epigenetic feedback in ZEB1/GRHL2 feedback loop and stochastic partitioning of biomolecules during cell division. Identifying the ZEB1/GRHL2 axis as a key determinant of epithelial-mesenchymal plasticity across many cancer types, we use mechanistic mathematical models to show how GRHL2 can be involved in both the abovementioned processes, thus driving an irreversible MET. Our study highlights how an isogenic population may contain subpopulation with varying degrees of susceptibility or resistance to EMT, and proposes a next set of questions for detailed experimental studies characterizing the irreversibility of MET/resistance to EMT.
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