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Modeling the Transitions between Collective and Solitary Migration Phenotypes in Cancer Metastasis

Cellular plasticity during cancer metastasis is a major clinical challenge. Two key cellular plasticity mechanisms —Epithelial-to-Mesenchymal Transition (EMT) and Mesenchymal-to-Amoeboid Transition (MAT) – have been carefully investigated individually, yet a comprehensive understanding of their inte...

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Autores principales: Huang, Bin, Jolly, Mohit Kumar, Lu, Mingyang, Tsarfaty, Ilan, Ben-Jacob, Eshel, Onuchic, Jose’ N
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4667179/
https://www.ncbi.nlm.nih.gov/pubmed/26627083
http://dx.doi.org/10.1038/srep17379
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author Huang, Bin
Jolly, Mohit Kumar
Lu, Mingyang
Tsarfaty, Ilan
Ben-Jacob, Eshel
Onuchic, Jose’ N
author_facet Huang, Bin
Jolly, Mohit Kumar
Lu, Mingyang
Tsarfaty, Ilan
Ben-Jacob, Eshel
Onuchic, Jose’ N
author_sort Huang, Bin
collection PubMed
description Cellular plasticity during cancer metastasis is a major clinical challenge. Two key cellular plasticity mechanisms —Epithelial-to-Mesenchymal Transition (EMT) and Mesenchymal-to-Amoeboid Transition (MAT) – have been carefully investigated individually, yet a comprehensive understanding of their interconnections remains elusive. Previously, we have modeled the dynamics of the core regulatory circuits for both EMT (miR-200/ZEB/miR-34/SNAIL) and MAT (Rac1/RhoA). We now extend our previous work to study the coupling between these two core circuits by considering the two microRNAs (miR-200 and miR-34) as external signals to the core MAT circuit. We show that this coupled circuit enables four different stable steady states (phenotypes) that correspond to hybrid epithelial/mesenchymal (E/M), mesenchymal (M), amoeboid (A) and hybrid amoeboid/mesenchymal (A/M) phenotypes. Our model recapitulates the metastasis-suppressing role of the microRNAs even in the presence of EMT-inducing signals like Hepatocyte Growth Factor (HGF). It also enables mapping the microRNA levels to the transitions among various cell migration phenotypes. Finally, it offers a mechanistic understanding for the observed phenotypic transitions among different cell migration phenotypes, specifically the Collective-to-Amoeboid Transition (CAT).
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spelling pubmed-46671792015-12-03 Modeling the Transitions between Collective and Solitary Migration Phenotypes in Cancer Metastasis Huang, Bin Jolly, Mohit Kumar Lu, Mingyang Tsarfaty, Ilan Ben-Jacob, Eshel Onuchic, Jose’ N Sci Rep Article Cellular plasticity during cancer metastasis is a major clinical challenge. Two key cellular plasticity mechanisms —Epithelial-to-Mesenchymal Transition (EMT) and Mesenchymal-to-Amoeboid Transition (MAT) – have been carefully investigated individually, yet a comprehensive understanding of their interconnections remains elusive. Previously, we have modeled the dynamics of the core regulatory circuits for both EMT (miR-200/ZEB/miR-34/SNAIL) and MAT (Rac1/RhoA). We now extend our previous work to study the coupling between these two core circuits by considering the two microRNAs (miR-200 and miR-34) as external signals to the core MAT circuit. We show that this coupled circuit enables four different stable steady states (phenotypes) that correspond to hybrid epithelial/mesenchymal (E/M), mesenchymal (M), amoeboid (A) and hybrid amoeboid/mesenchymal (A/M) phenotypes. Our model recapitulates the metastasis-suppressing role of the microRNAs even in the presence of EMT-inducing signals like Hepatocyte Growth Factor (HGF). It also enables mapping the microRNA levels to the transitions among various cell migration phenotypes. Finally, it offers a mechanistic understanding for the observed phenotypic transitions among different cell migration phenotypes, specifically the Collective-to-Amoeboid Transition (CAT). Nature Publishing Group 2015-12-02 /pmc/articles/PMC4667179/ /pubmed/26627083 http://dx.doi.org/10.1038/srep17379 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Huang, Bin
Jolly, Mohit Kumar
Lu, Mingyang
Tsarfaty, Ilan
Ben-Jacob, Eshel
Onuchic, Jose’ N
Modeling the Transitions between Collective and Solitary Migration Phenotypes in Cancer Metastasis
title Modeling the Transitions between Collective and Solitary Migration Phenotypes in Cancer Metastasis
title_full Modeling the Transitions between Collective and Solitary Migration Phenotypes in Cancer Metastasis
title_fullStr Modeling the Transitions between Collective and Solitary Migration Phenotypes in Cancer Metastasis
title_full_unstemmed Modeling the Transitions between Collective and Solitary Migration Phenotypes in Cancer Metastasis
title_short Modeling the Transitions between Collective and Solitary Migration Phenotypes in Cancer Metastasis
title_sort modeling the transitions between collective and solitary migration phenotypes in cancer metastasis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4667179/
https://www.ncbi.nlm.nih.gov/pubmed/26627083
http://dx.doi.org/10.1038/srep17379
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