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Agent-based modeling predicts RAC1 is critical for ovarian cancer metastasis

Experimental and computational studies pinpoint rate-limiting step(s) in metastasis governed by Rac1. Using ovarian cancer cell and animal models, Rac1 expression was manipulated, and quantitative measurements of cell–cell and cell–substrate adhesion, cell invasion, mesothelial clearance, and perito...

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Autores principales: Rivera, Melanie, Toledo-Jacobo, Leslie, Romero, Elsa, Oprea, Tudor I., Moses, Melanie E., Hudson, Laurie G., Wandinger-Ness, Angela, Grimes, Martha M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society for Cell Biology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9727804/
https://www.ncbi.nlm.nih.gov/pubmed/36200848
http://dx.doi.org/10.1091/mbc.E21-11-0540
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author Rivera, Melanie
Toledo-Jacobo, Leslie
Romero, Elsa
Oprea, Tudor I.
Moses, Melanie E.
Hudson, Laurie G.
Wandinger-Ness, Angela
Grimes, Martha M.
author_facet Rivera, Melanie
Toledo-Jacobo, Leslie
Romero, Elsa
Oprea, Tudor I.
Moses, Melanie E.
Hudson, Laurie G.
Wandinger-Ness, Angela
Grimes, Martha M.
author_sort Rivera, Melanie
collection PubMed
description Experimental and computational studies pinpoint rate-limiting step(s) in metastasis governed by Rac1. Using ovarian cancer cell and animal models, Rac1 expression was manipulated, and quantitative measurements of cell–cell and cell–substrate adhesion, cell invasion, mesothelial clearance, and peritoneal tumor growth discriminated the tumor behaviors most highly influenced by Rac1. The experimental data were used to parameterize an agent-based computational model simulating peritoneal niche colonization, intravasation, and hematogenous metastasis to distant organs. Increased ovarian cancer cell survival afforded by the more rapid adhesion and intravasation upon Rac1 overexpression is predicted to increase the numbers of and the rates at which tumor cells are disseminated to distant sites. Surprisingly, crowding of cancer cells along the blood vessel was found to decrease the numbers of cells reaching a distant niche irrespective of Rac1 overexpression or knockdown, suggesting that sites for tumor cell intravasation are rate limiting and become accessible if cells intravasate rapidly or are displaced due to diminished viability. Modeling predictions were confirmed through animal studies of Rac1-dependent metastasis to the lung. Collectively, the experimental and modeling approaches identify cell adhesion, rapid intravasation, and survival in the blood as parameters in the ovarian metastatic cascade that are most critically dependent on Rac1.
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spelling pubmed-97278042023-02-02 Agent-based modeling predicts RAC1 is critical for ovarian cancer metastasis Rivera, Melanie Toledo-Jacobo, Leslie Romero, Elsa Oprea, Tudor I. Moses, Melanie E. Hudson, Laurie G. Wandinger-Ness, Angela Grimes, Martha M. Mol Biol Cell Articles Experimental and computational studies pinpoint rate-limiting step(s) in metastasis governed by Rac1. Using ovarian cancer cell and animal models, Rac1 expression was manipulated, and quantitative measurements of cell–cell and cell–substrate adhesion, cell invasion, mesothelial clearance, and peritoneal tumor growth discriminated the tumor behaviors most highly influenced by Rac1. The experimental data were used to parameterize an agent-based computational model simulating peritoneal niche colonization, intravasation, and hematogenous metastasis to distant organs. Increased ovarian cancer cell survival afforded by the more rapid adhesion and intravasation upon Rac1 overexpression is predicted to increase the numbers of and the rates at which tumor cells are disseminated to distant sites. Surprisingly, crowding of cancer cells along the blood vessel was found to decrease the numbers of cells reaching a distant niche irrespective of Rac1 overexpression or knockdown, suggesting that sites for tumor cell intravasation are rate limiting and become accessible if cells intravasate rapidly or are displaced due to diminished viability. Modeling predictions were confirmed through animal studies of Rac1-dependent metastasis to the lung. Collectively, the experimental and modeling approaches identify cell adhesion, rapid intravasation, and survival in the blood as parameters in the ovarian metastatic cascade that are most critically dependent on Rac1. The American Society for Cell Biology 2022-11-18 /pmc/articles/PMC9727804/ /pubmed/36200848 http://dx.doi.org/10.1091/mbc.E21-11-0540 Text en © 2022 Rivera et al. “ASCB®,” “The American Society for Cell Biology®,” and “Molecular Biology of the Cell®” are registered trademarks of The American Society for Cell Biology. https://creativecommons.org/licenses/by-nc-sa/4.0/This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial-Share Alike 4.0 International Creative Commons License.
spellingShingle Articles
Rivera, Melanie
Toledo-Jacobo, Leslie
Romero, Elsa
Oprea, Tudor I.
Moses, Melanie E.
Hudson, Laurie G.
Wandinger-Ness, Angela
Grimes, Martha M.
Agent-based modeling predicts RAC1 is critical for ovarian cancer metastasis
title Agent-based modeling predicts RAC1 is critical for ovarian cancer metastasis
title_full Agent-based modeling predicts RAC1 is critical for ovarian cancer metastasis
title_fullStr Agent-based modeling predicts RAC1 is critical for ovarian cancer metastasis
title_full_unstemmed Agent-based modeling predicts RAC1 is critical for ovarian cancer metastasis
title_short Agent-based modeling predicts RAC1 is critical for ovarian cancer metastasis
title_sort agent-based modeling predicts rac1 is critical for ovarian cancer metastasis
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9727804/
https://www.ncbi.nlm.nih.gov/pubmed/36200848
http://dx.doi.org/10.1091/mbc.E21-11-0540
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