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Integrated cancer tissue engineering models for precision medicine
Tumors are not merely cancerous cells that undergo mindless proliferation. Rather, they are highly organized and interconnected organ systems. Tumor cells reside in complex microenvironments in which they are subjected to a variety of physical and chemical stimuli that influence cell behavior and ul...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510431/ https://www.ncbi.nlm.nih.gov/pubmed/31075118 http://dx.doi.org/10.1371/journal.pone.0216564 |
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author | Bregenzer, Michael E. Horst, Eric N. Mehta, Pooja Novak, Caymen M. Raghavan, Shreya Snyder, Catherine S. Mehta, Geeta |
author_facet | Bregenzer, Michael E. Horst, Eric N. Mehta, Pooja Novak, Caymen M. Raghavan, Shreya Snyder, Catherine S. Mehta, Geeta |
author_sort | Bregenzer, Michael E. |
collection | PubMed |
description | Tumors are not merely cancerous cells that undergo mindless proliferation. Rather, they are highly organized and interconnected organ systems. Tumor cells reside in complex microenvironments in which they are subjected to a variety of physical and chemical stimuli that influence cell behavior and ultimately the progression and maintenance of the tumor. As cancer bioengineers, it is our responsibility to create physiologic models that enable accurate understanding of the multi-dimensional structure, organization, and complex relationships in diverse tumor microenvironments. Such models can greatly expedite clinical discovery and translation by closely replicating the physiological conditions while maintaining high tunability and control of extrinsic factors. In this review, we discuss the current models that target key aspects of the tumor microenvironment and their role in cancer progression. In order to address sources of experimental variation and model limitations, we also make recommendations for methods to improve overall physiologic reproducibility, experimental repeatability, and rigor within the field. Improvements can be made through an enhanced emphasis on mathematical modeling, standardized in vitro model characterization, transparent reporting of methodologies, and designing experiments with physiological metrics. Taken together these considerations will enhance the relevance of in vitro tumor models, biological understanding, and accelerate treatment exploration ultimately leading to improved clinical outcomes. Moreover, the development of robust, user-friendly models that integrate important stimuli will allow for the in-depth study of tumors as they undergo progression from non-transformed primary cells to metastatic disease and facilitate translation to a wide variety of biological and clinical studies. |
format | Online Article Text |
id | pubmed-6510431 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-65104312019-05-23 Integrated cancer tissue engineering models for precision medicine Bregenzer, Michael E. Horst, Eric N. Mehta, Pooja Novak, Caymen M. Raghavan, Shreya Snyder, Catherine S. Mehta, Geeta PLoS One Collection Review Tumors are not merely cancerous cells that undergo mindless proliferation. Rather, they are highly organized and interconnected organ systems. Tumor cells reside in complex microenvironments in which they are subjected to a variety of physical and chemical stimuli that influence cell behavior and ultimately the progression and maintenance of the tumor. As cancer bioengineers, it is our responsibility to create physiologic models that enable accurate understanding of the multi-dimensional structure, organization, and complex relationships in diverse tumor microenvironments. Such models can greatly expedite clinical discovery and translation by closely replicating the physiological conditions while maintaining high tunability and control of extrinsic factors. In this review, we discuss the current models that target key aspects of the tumor microenvironment and their role in cancer progression. In order to address sources of experimental variation and model limitations, we also make recommendations for methods to improve overall physiologic reproducibility, experimental repeatability, and rigor within the field. Improvements can be made through an enhanced emphasis on mathematical modeling, standardized in vitro model characterization, transparent reporting of methodologies, and designing experiments with physiological metrics. Taken together these considerations will enhance the relevance of in vitro tumor models, biological understanding, and accelerate treatment exploration ultimately leading to improved clinical outcomes. Moreover, the development of robust, user-friendly models that integrate important stimuli will allow for the in-depth study of tumors as they undergo progression from non-transformed primary cells to metastatic disease and facilitate translation to a wide variety of biological and clinical studies. Public Library of Science 2019-05-10 /pmc/articles/PMC6510431/ /pubmed/31075118 http://dx.doi.org/10.1371/journal.pone.0216564 Text en © 2019 Bregenzer et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Collection Review Bregenzer, Michael E. Horst, Eric N. Mehta, Pooja Novak, Caymen M. Raghavan, Shreya Snyder, Catherine S. Mehta, Geeta Integrated cancer tissue engineering models for precision medicine |
title | Integrated cancer tissue engineering models for precision medicine |
title_full | Integrated cancer tissue engineering models for precision medicine |
title_fullStr | Integrated cancer tissue engineering models for precision medicine |
title_full_unstemmed | Integrated cancer tissue engineering models for precision medicine |
title_short | Integrated cancer tissue engineering models for precision medicine |
title_sort | integrated cancer tissue engineering models for precision medicine |
topic | Collection Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510431/ https://www.ncbi.nlm.nih.gov/pubmed/31075118 http://dx.doi.org/10.1371/journal.pone.0216564 |
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