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Mathematical Models of Organoid Cultures

Organoids are engineered three-dimensional tissue cultures derived from stem cells and capable of self-renewal and self-organization into a variety of progenitors and differentiated cell types. An organoid resembles the cellular structure of an organ and retains some of its functionality, while stil...

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Autores principales: Montes-Olivas, Sandra, Marucci, Lucia, Homer, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6761251/
https://www.ncbi.nlm.nih.gov/pubmed/31592020
http://dx.doi.org/10.3389/fgene.2019.00873
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author Montes-Olivas, Sandra
Marucci, Lucia
Homer, Martin
author_facet Montes-Olivas, Sandra
Marucci, Lucia
Homer, Martin
author_sort Montes-Olivas, Sandra
collection PubMed
description Organoids are engineered three-dimensional tissue cultures derived from stem cells and capable of self-renewal and self-organization into a variety of progenitors and differentiated cell types. An organoid resembles the cellular structure of an organ and retains some of its functionality, while still being amenable to in vitro experimental study. Compared with two-dimensional cultures, the three-dimensional structure of organoids provides a more realistic environment and structural organization of in vivo organs. Similarly, organoids are better suited to reproduce signaling pathway dynamics in vitro, due to a more realistic physiological environment. As such, organoids are a valuable tool to explore the dynamics of organogenesis and offer routes to personalized preclinical trials of cancer progression, invasion, and drug response. Complementary to experiments, mathematical and computational models are valuable instruments in the description of spatiotemporal dynamics of organoids. Simulations of mathematical models allow the study of multiscale dynamics of organoids, at both the intracellular and intercellular levels. Mathematical models also enable us to understand the underlying mechanisms responsible for phenotypic variation and the response to external stimulation in a cost- and time-effective manner. Many recent studies have developed laboratory protocols to grow organoids resembling different organs such as the intestine, brain, liver, pancreas, and mammary glands. However, the development of mathematical models specific to organoids remains comparatively underdeveloped. Here, we review the mathematical and computational approaches proposed so far to describe and predict organoid dynamics, reporting the simulation frameworks used and the models’ strengths and limitations.
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spelling pubmed-67612512019-10-07 Mathematical Models of Organoid Cultures Montes-Olivas, Sandra Marucci, Lucia Homer, Martin Front Genet Genetics Organoids are engineered three-dimensional tissue cultures derived from stem cells and capable of self-renewal and self-organization into a variety of progenitors and differentiated cell types. An organoid resembles the cellular structure of an organ and retains some of its functionality, while still being amenable to in vitro experimental study. Compared with two-dimensional cultures, the three-dimensional structure of organoids provides a more realistic environment and structural organization of in vivo organs. Similarly, organoids are better suited to reproduce signaling pathway dynamics in vitro, due to a more realistic physiological environment. As such, organoids are a valuable tool to explore the dynamics of organogenesis and offer routes to personalized preclinical trials of cancer progression, invasion, and drug response. Complementary to experiments, mathematical and computational models are valuable instruments in the description of spatiotemporal dynamics of organoids. Simulations of mathematical models allow the study of multiscale dynamics of organoids, at both the intracellular and intercellular levels. Mathematical models also enable us to understand the underlying mechanisms responsible for phenotypic variation and the response to external stimulation in a cost- and time-effective manner. Many recent studies have developed laboratory protocols to grow organoids resembling different organs such as the intestine, brain, liver, pancreas, and mammary glands. However, the development of mathematical models specific to organoids remains comparatively underdeveloped. Here, we review the mathematical and computational approaches proposed so far to describe and predict organoid dynamics, reporting the simulation frameworks used and the models’ strengths and limitations. Frontiers Media S.A. 2019-09-19 /pmc/articles/PMC6761251/ /pubmed/31592020 http://dx.doi.org/10.3389/fgene.2019.00873 Text en Copyright © 2019 Montes-Olivas, Marucci and Homer http://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 Genetics
Montes-Olivas, Sandra
Marucci, Lucia
Homer, Martin
Mathematical Models of Organoid Cultures
title Mathematical Models of Organoid Cultures
title_full Mathematical Models of Organoid Cultures
title_fullStr Mathematical Models of Organoid Cultures
title_full_unstemmed Mathematical Models of Organoid Cultures
title_short Mathematical Models of Organoid Cultures
title_sort mathematical models of organoid cultures
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6761251/
https://www.ncbi.nlm.nih.gov/pubmed/31592020
http://dx.doi.org/10.3389/fgene.2019.00873
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