Signaling network state predicts Twist-mediated effects on breast cell migration across diverse growth factor contexts
Epithelial-mesenchymal transition (EMT), whether in developmental morphogenesis or malignant transformation, prominently involves modified cell motility behavior. Although major advances have transpired in understanding the molecular pathways regulating the process of EMT induction per se by certain...
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| Format: | Article |
| Language: | en_US |
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American Society of Biochemistry and Molecular Biology
2012
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| Online Access: | http://hdl.handle.net/1721.1/67899 https://orcid.org/0000-0003-3214-4554 |
| _version_ | 1826202221688127488 |
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| author | Kim, Hyung-Do Meyer, Aaron Samuel Wagner, Joel Patrick Wells, Alan Gertler, Frank Hughes-Alford, Shannon Kay Lauffenburger, Douglas A |
| author2 | Massachusetts Institute of Technology. Department of Biological Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Biological Engineering Kim, Hyung-Do Meyer, Aaron Samuel Wagner, Joel Patrick Wells, Alan Gertler, Frank Hughes-Alford, Shannon Kay Lauffenburger, Douglas A |
| author_sort | Kim, Hyung-Do |
| collection | MIT |
| description | Epithelial-mesenchymal transition (EMT), whether in developmental morphogenesis or malignant transformation, prominently involves modified cell motility behavior. Although major advances have transpired in understanding the molecular pathways regulating the process of EMT induction per se by certain environmental stimuli, an important outstanding question is how the activities of signaling pathways governing motility yield the diverse movement behaviors characteristic of pre-induction versus postinduction states across a broad landscape of growth factor contexts. For the particular case of EMT induction in human mammary cells by ectopic expression of the transcription factor Twist, we found the migration responses to a panel of growth factors (EGF, HRG, IGF, HGF) dramatically disparate between confluent pre-Twist epithelial cells and sparsely distributed post-Twist mesenchymal cells—but that a computational model quantitatively integrating multiple key signaling node activities could nonetheless account for this full range of behavior. Moreover, motility in both conditions was successfully predicted a priori for an additional growth factor (PDGF) treatment. Although this signaling network state model could comprehend motility behavior globally, modulation of the network interactions underlying the altered pathway activities was identified by ascertaining differences in quantitative topological influences among the nodes between the two conditions. |
| first_indexed | 2024-09-23T12:04:05Z |
| format | Article |
| id | mit-1721.1/67899 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T12:04:05Z |
| publishDate | 2012 |
| publisher | American Society of Biochemistry and Molecular Biology |
| record_format | dspace |
| spelling | mit-1721.1/678992022-09-27T23:51:10Z Signaling network state predicts Twist-mediated effects on breast cell migration across diverse growth factor contexts Kim, Hyung-Do Meyer, Aaron Samuel Wagner, Joel Patrick Wells, Alan Gertler, Frank Hughes-Alford, Shannon Kay Lauffenburger, Douglas A Massachusetts Institute of Technology. Department of Biological Engineering Massachusetts Institute of Technology. Department of Biology Koch Institute for Integrative Cancer Research at MIT Lauffenburger, Douglas A. Kim, Hyung-Do Meyer, Aaron Samuel Wagner, Joel Patrick Alford, Shannon K. Gertler, Frank Lauffenburger, Douglas A. Epithelial-mesenchymal transition (EMT), whether in developmental morphogenesis or malignant transformation, prominently involves modified cell motility behavior. Although major advances have transpired in understanding the molecular pathways regulating the process of EMT induction per se by certain environmental stimuli, an important outstanding question is how the activities of signaling pathways governing motility yield the diverse movement behaviors characteristic of pre-induction versus postinduction states across a broad landscape of growth factor contexts. For the particular case of EMT induction in human mammary cells by ectopic expression of the transcription factor Twist, we found the migration responses to a panel of growth factors (EGF, HRG, IGF, HGF) dramatically disparate between confluent pre-Twist epithelial cells and sparsely distributed post-Twist mesenchymal cells—but that a computational model quantitatively integrating multiple key signaling node activities could nonetheless account for this full range of behavior. Moreover, motility in both conditions was successfully predicted a priori for an additional growth factor (PDGF) treatment. Although this signaling network state model could comprehend motility behavior globally, modulation of the network interactions underlying the altered pathway activities was identified by ascertaining differences in quantitative topological influences among the nodes between the two conditions. National Institutes of Health (U.S.) (grant U54-CA112967) National Institutes of Health (U.S.) (grant R01-GM081336) Ludwig Center for Molecular Oncology 2012-01-04T19:53:42Z 2012-01-04T19:53:42Z 2011-11 2011-08 Article http://purl.org/eprint/type/JournalArticle 1535-9476 1535-9484 http://hdl.handle.net/1721.1/67899 Kim, H.-D. et al. “Signaling Network State Predicts Twist-Mediated Effects on Breast Cell Migration Across Diverse Growth Factor Contexts.” Molecular & Cellular Proteomics 10.11 (2011): M111.008433-M111.008433. © 2011 by The American Society for Biochemistry and Molecular Biology, Inc. 21832255 https://orcid.org/0000-0003-3214-4554 en_US http://dx.doi.org/10.1074/mcp.M111.008433 Molecular and Cellular Proteomics 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. application/pdf American Society of Biochemistry and Molecular Biology Prof. Lauffenburger |
| spellingShingle | Kim, Hyung-Do Meyer, Aaron Samuel Wagner, Joel Patrick Wells, Alan Gertler, Frank Hughes-Alford, Shannon Kay Lauffenburger, Douglas A Signaling network state predicts Twist-mediated effects on breast cell migration across diverse growth factor contexts |
| title | Signaling network state predicts Twist-mediated effects on breast cell migration across diverse growth factor contexts |
| title_full | Signaling network state predicts Twist-mediated effects on breast cell migration across diverse growth factor contexts |
| title_fullStr | Signaling network state predicts Twist-mediated effects on breast cell migration across diverse growth factor contexts |
| title_full_unstemmed | Signaling network state predicts Twist-mediated effects on breast cell migration across diverse growth factor contexts |
| title_short | Signaling network state predicts Twist-mediated effects on breast cell migration across diverse growth factor contexts |
| title_sort | signaling network state predicts twist mediated effects on breast cell migration across diverse growth factor contexts |
| url | http://hdl.handle.net/1721.1/67899 https://orcid.org/0000-0003-3214-4554 |
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