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Computational Simulation of Exosome Transport in Tumor Microenvironment
Cellular exosome-mediated crosstalk in tumor microenvironment (TME) is a critical component of anti-tumor immune responses. In addition to particle size, exosome transport and uptake by target cells is influenced by physical and physiological factors, including interstitial fluid pressure, and exoso...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8076500/ https://www.ncbi.nlm.nih.gov/pubmed/33928104 http://dx.doi.org/10.3389/fmed.2021.643793 |
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author | Koomullil, Roy Tehrani, Behnam Goliwas, Kayla Wang, Yong Ponnazhagan, Selvarangan Berry, Joel Deshane, Jessy |
author_facet | Koomullil, Roy Tehrani, Behnam Goliwas, Kayla Wang, Yong Ponnazhagan, Selvarangan Berry, Joel Deshane, Jessy |
author_sort | Koomullil, Roy |
collection | PubMed |
description | Cellular exosome-mediated crosstalk in tumor microenvironment (TME) is a critical component of anti-tumor immune responses. In addition to particle size, exosome transport and uptake by target cells is influenced by physical and physiological factors, including interstitial fluid pressure, and exosome concentration. These variables differ under both normal and pathological conditions, including cancer. The transport of exosomes in TME is governed by interstitial flow and diffusion. Based on these determinants, mathematical models were adapted to simulate the transport of exosomes in the TME with specified exosome release rates from the tumor cells. In this study, the significance of spatial relationship in exosome-mediated intercellular communication was established by treating their movement in the TME as a continuum using a transport equation, with advection due to interstitial flow and diffusion due to concentration gradients. To quantify the rate of release of exosomes by biomechanical forces acting on the tumor cells, we used a transwell platform with confluent triple negative breast cancer cells 4T1.2 seeded in BioFlex plates exposed to an oscillatory force. Exosome release rates were quantified from 4T1.2 cells seeded at the bottom of the well following the application of either no force or an oscillatory force, and these rates were used to model exosome transport in the transwell. The simulations predicted that a larger number of exosomes reached the membrane of the transwell for 4T1.2 cells exposed to the oscillatory force when compared to controls. Additionally, we simulated the interstitial fluid flow and exosome transport in a 2-dimensional TME with macrophages, T cells, and mixtures of these two populations at two different stages of a tumor growth. Computational simulations were carried out using the commercial computational simulation package, ANSYS/Fluent. The results of this study indicated higher exosome concentrations and larger interstitial fluid pressure at the later stages of the tumor growth. Quantifying the release of exosomes by cancer cells, their transport through the TME, and their concentration in TME will afford a deeper understanding of the mechanisms of these interactions and aid in deriving predictive models for therapeutic intervention. |
format | Online Article Text |
id | pubmed-8076500 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80765002021-04-28 Computational Simulation of Exosome Transport in Tumor Microenvironment Koomullil, Roy Tehrani, Behnam Goliwas, Kayla Wang, Yong Ponnazhagan, Selvarangan Berry, Joel Deshane, Jessy Front Med (Lausanne) Medicine Cellular exosome-mediated crosstalk in tumor microenvironment (TME) is a critical component of anti-tumor immune responses. In addition to particle size, exosome transport and uptake by target cells is influenced by physical and physiological factors, including interstitial fluid pressure, and exosome concentration. These variables differ under both normal and pathological conditions, including cancer. The transport of exosomes in TME is governed by interstitial flow and diffusion. Based on these determinants, mathematical models were adapted to simulate the transport of exosomes in the TME with specified exosome release rates from the tumor cells. In this study, the significance of spatial relationship in exosome-mediated intercellular communication was established by treating their movement in the TME as a continuum using a transport equation, with advection due to interstitial flow and diffusion due to concentration gradients. To quantify the rate of release of exosomes by biomechanical forces acting on the tumor cells, we used a transwell platform with confluent triple negative breast cancer cells 4T1.2 seeded in BioFlex plates exposed to an oscillatory force. Exosome release rates were quantified from 4T1.2 cells seeded at the bottom of the well following the application of either no force or an oscillatory force, and these rates were used to model exosome transport in the transwell. The simulations predicted that a larger number of exosomes reached the membrane of the transwell for 4T1.2 cells exposed to the oscillatory force when compared to controls. Additionally, we simulated the interstitial fluid flow and exosome transport in a 2-dimensional TME with macrophages, T cells, and mixtures of these two populations at two different stages of a tumor growth. Computational simulations were carried out using the commercial computational simulation package, ANSYS/Fluent. The results of this study indicated higher exosome concentrations and larger interstitial fluid pressure at the later stages of the tumor growth. Quantifying the release of exosomes by cancer cells, their transport through the TME, and their concentration in TME will afford a deeper understanding of the mechanisms of these interactions and aid in deriving predictive models for therapeutic intervention. Frontiers Media S.A. 2021-04-13 /pmc/articles/PMC8076500/ /pubmed/33928104 http://dx.doi.org/10.3389/fmed.2021.643793 Text en Copyright © 2021 Koomullil, Tehrani, Goliwas, Wang, Ponnazhagan, Berry and Deshane. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Medicine Koomullil, Roy Tehrani, Behnam Goliwas, Kayla Wang, Yong Ponnazhagan, Selvarangan Berry, Joel Deshane, Jessy Computational Simulation of Exosome Transport in Tumor Microenvironment |
title | Computational Simulation of Exosome Transport in Tumor Microenvironment |
title_full | Computational Simulation of Exosome Transport in Tumor Microenvironment |
title_fullStr | Computational Simulation of Exosome Transport in Tumor Microenvironment |
title_full_unstemmed | Computational Simulation of Exosome Transport in Tumor Microenvironment |
title_short | Computational Simulation of Exosome Transport in Tumor Microenvironment |
title_sort | computational simulation of exosome transport in tumor microenvironment |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8076500/ https://www.ncbi.nlm.nih.gov/pubmed/33928104 http://dx.doi.org/10.3389/fmed.2021.643793 |
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