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...

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Bibliographic Details
Published in:Cancer control 2020-07, Vol.27 (3), p.1073274820946804-1073274820946804
Main Authors: Gatenbee, Chandler D., Minor, Emily S., Slebos, Robbert J. C., Chung, Christine H., Anderson, Alexander R. A.
Format: Article
Language:English
Subjects:
Biopsy
Cancer
Cancer research
Disease Progression
Ecology - methods
Ecosystem dynamics
Environmental factors
Geographical distribution
Humans
Microenvironments
Models, Biological
Neoplasms - mortality
Neoplasms - pathology
Neoplasms - therapy
Prognosis
Spatio-Temporal Analysis
Special Collection on Ecological and Evolutionary Approaches to Cancer Control- & View
Species
Treatment Outcome
Treatment resistance
Tumor cells
Tumor Microenvironment
Tumors
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Summary: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.
ISSN:1073-2748
1526-2359
1073-2748
DOI:10.1177/1073274820946804