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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The American Society for Cell Biology
2022
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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. |
format | Online Article Text |
id | pubmed-9727804 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The American Society for Cell Biology |
record_format | MEDLINE/PubMed |
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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