Huang, BinJolly, Mohit KumarLu, MingyangTsarfaty, IlanBen-Jacob, EshelOnuchic, José Nelson2016-01-152016-01-152015Huang, Bin, Jolly, Mohit Kumar, Lu, Mingyang, et al.. "Modeling the Transitions between Collective and Solitary Migration Phenotypes in Cancer Metastasis." <i>Scientific Reports,</i> 5, (2015) Macmillan Publishers Limited: http://dx.doi.org/10.1038/srep17379.https://hdl.handle.net/1911/87844Cellular 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).engThis 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 maJournal articlehttp://dx.doi.org/10.1038/srep17379