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dc.contributor.authorHuang, Bin
Lu, Mingyang
Jolly, Mohit Kumar
Tsarfaty, Ilan
Onuchic, José
Ben-Jacob, Eshel
dc.date.accessioned 2014-11-14T17:45:22Z
dc.date.available 2014-11-14T17:45:22Z
dc.date.issued 2014
dc.identifier.citation Huang, Bin, Lu, Mingyang, Jolly, Mohit Kumar, et al.. "The three-way switch operation of Rac1/RhoA GTPase-based circuit controlling amoeboid-hybrid-mesenchymal transition." Scientific Reports, 4, (2014) Nature Publishing Group: 6449. http://dx.doi.org/10.1038/srep06449.
dc.identifier.urihttps://hdl.handle.net/1911/78271
dc.description.abstract Metastatic carcinoma cells exhibit at least two different phenotypes of motility and invasion - amoeboid and mesenchymal. This plasticity poses a major clinical challenge for treating metastasis, while its underlying mechanisms remain enigmatic. Transitions between these phenotypes are mediated by the Rac1/RhoA circuit that responds to external signals such as HGF/SF via c-MET pathway. Using detailed modeling of GTPase-based regulation to study the Rac1/RhoA circuit's dynamics, we found that it can operate as a three-way switch. We propose to associate the circuit's three possible states to the amoeboid, mesenchymal and amoeboid/mesenchymal hybrid phenotype. In particular, we investigated the range of existence of, and the transition between, the three states (phenotypes) in response to Grb2 and Gab1 - two downstream adaptors of c-MET. The results help to explain the regulation of metastatic cells by c-MET pathway and hence can contribute to the assessment of possible clinical interventions.
dc.language.iso eng
dc.publisher Nature Publishing Group
dc.rights Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
dc.title The three-way switch operation of Rac1/RhoA GTPase-based circuit controlling amoeboid-hybrid-mesenchymal transition
dc.type Journal article
dc.contributor.funder National Science Foundation
dc.contributor.funder Cancer Prevention and Research Institute of Texas
dc.contributor.funder Tauber Family Funds
dc.contributor.funder Maguy-Glass Chair in Physics of Complex Systems, Tel Aviv University
dc.contributor.funder Breast Cancer Research Foundation
dc.contributor.funder United States-Israel Binational Science Foundation
dc.contributor.funder Federico Foundation
dc.citation.journalTitle Scientific Reports
dc.contributor.org Center for Theoretical Biological Physics
dc.subject.keywordcomputational models
computer modelling
cancer models
dc.citation.volumeNumber 4
dc.type.dcmi Text
dc.identifier.doihttp://dx.doi.org/10.1038/srep06449
dc.identifier.pmcid PMC4171704
dc.identifier.pmid 25245029
dc.identifier.grantID PHY-1427654 (National Science Foundation)
dc.identifier.grantID NSF-MCB-1214457 (National Science Foundation)
dc.type.publication publisher version
dc.citation.firstpage 6449


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