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Histoecology: Applying Ecological Principles and Approaches to Describe and Predict Tumor Ecosystem Dynamics Across Space and Time
Cancer cells exist within a complex spatially structured ecosystem composed of resources and different cell types. As the selective pressures imposed by this environment determine the fate of cancer cells, an improved understanding of how this ecosystem evolves will better elucidate how tumors grow...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7710396/ https://www.ncbi.nlm.nih.gov/pubmed/32869651 http://dx.doi.org/10.1177/1073274820946804 |
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author | Gatenbee, Chandler D. Minor, Emily S. Slebos, Robbert J. C. Chung, Christine H. Anderson, Alexander R. A. |
author_facet | Gatenbee, Chandler D. Minor, Emily S. Slebos, Robbert J. C. Chung, Christine H. Anderson, Alexander R. A. |
author_sort | Gatenbee, Chandler D. |
collection | PubMed |
description | Cancer cells exist within a complex spatially structured ecosystem composed of resources and different cell types. As the selective pressures imposed by this environment determine the fate of cancer cells, an improved understanding of how this ecosystem evolves will better elucidate how tumors grow and respond to therapy. State of the art imaging methods can now provide highly resolved descriptions of the microenvironment, yielding the data required for a thorough study of its role in tumor growth and treatment resistance. The field of landscape ecology has been studying such species-environment relationship for decades, and offers many tools and perspectives that cancer researchers could greatly benefit from. Here, we discuss one such tool, species distribution modeling (SDM), that has the potential to, among other things, identify critical environmental factors that drive tumor evolution and predict response to therapy. SDMs only scratch the surface of how ecological theory and methods can be applied to cancer, and we believe further integration will take cancer research in exciting new and productive directions. Significance: Here we describe how species distribution modeling can be used to quantitatively describe the complex relationship between tumor cells and their microenvironment. Such a description facilitates a deeper understanding of cancers eco-evolutionary dynamics, which in turn sheds light on the factors that drive tumor growth and response to treatment. |
format | Online Article Text |
id | pubmed-7710396 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-77103962020-12-08 Histoecology: Applying Ecological Principles and Approaches to Describe and Predict Tumor Ecosystem Dynamics Across Space and Time Gatenbee, Chandler D. Minor, Emily S. Slebos, Robbert J. C. Chung, Christine H. Anderson, Alexander R. A. Cancer Control Special Collection on Ecological and Evolutionary Approaches to Cancer Control-Commentary & View Cancer cells exist within a complex spatially structured ecosystem composed of resources and different cell types. As the selective pressures imposed by this environment determine the fate of cancer cells, an improved understanding of how this ecosystem evolves will better elucidate how tumors grow and respond to therapy. State of the art imaging methods can now provide highly resolved descriptions of the microenvironment, yielding the data required for a thorough study of its role in tumor growth and treatment resistance. The field of landscape ecology has been studying such species-environment relationship for decades, and offers many tools and perspectives that cancer researchers could greatly benefit from. Here, we discuss one such tool, species distribution modeling (SDM), that has the potential to, among other things, identify critical environmental factors that drive tumor evolution and predict response to therapy. SDMs only scratch the surface of how ecological theory and methods can be applied to cancer, and we believe further integration will take cancer research in exciting new and productive directions. Significance: Here we describe how species distribution modeling can be used to quantitatively describe the complex relationship between tumor cells and their microenvironment. Such a description facilitates a deeper understanding of cancers eco-evolutionary dynamics, which in turn sheds light on the factors that drive tumor growth and response to treatment. SAGE Publications 2020-09-01 /pmc/articles/PMC7710396/ /pubmed/32869651 http://dx.doi.org/10.1177/1073274820946804 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Special Collection on Ecological and Evolutionary Approaches to Cancer Control-Commentary & View Gatenbee, Chandler D. Minor, Emily S. Slebos, Robbert J. C. Chung, Christine H. Anderson, Alexander R. A. Histoecology: Applying Ecological Principles and Approaches to Describe and Predict Tumor Ecosystem Dynamics Across Space and Time |
title | Histoecology: Applying Ecological Principles and Approaches to
Describe and Predict Tumor Ecosystem Dynamics Across Space and
Time |
title_full | Histoecology: Applying Ecological Principles and Approaches to
Describe and Predict Tumor Ecosystem Dynamics Across Space and
Time |
title_fullStr | Histoecology: Applying Ecological Principles and Approaches to
Describe and Predict Tumor Ecosystem Dynamics Across Space and
Time |
title_full_unstemmed | Histoecology: Applying Ecological Principles and Approaches to
Describe and Predict Tumor Ecosystem Dynamics Across Space and
Time |
title_short | Histoecology: Applying Ecological Principles and Approaches to
Describe and Predict Tumor Ecosystem Dynamics Across Space and
Time |
title_sort | histoecology: applying ecological principles and approaches to
describe and predict tumor ecosystem dynamics across space and
time |
topic | Special Collection on Ecological and Evolutionary Approaches to Cancer Control-Commentary & View |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7710396/ https://www.ncbi.nlm.nih.gov/pubmed/32869651 http://dx.doi.org/10.1177/1073274820946804 |
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