Cited by 227Mathematical Biology Tumor GrowthCancer Genomics and DiagnosticsEvolution and Genetic Dynamics

Integrating evolutionary dynamics into cancer therapy

Gatenby, Robert A., Brown, Joel S.·2020·Nature Reviews Clinical Oncology

Abstract

Many effective drugs for metastatic and/or advanced-stage cancers have been developed over the past decade, although the evolution of resistance remains the major barrier to disease control or cure. In large, diverse populations such as the cells that compose metastatic cancers, the emergence of cells that are resistant or that can quickly develop resistance is virtually inevitable and most likely cannot be prevented. However, clinically significant resistance occurs only when the pre-existing resistant phenotypes are able to proliferate extensively, a process governed by eco-evolutionary dynamics. Attempts to disrupt the molecular mechanisms of resistance have generally been unsuccessful in clinical practice. In this Review, we focus on the Darwinian processes driving the eco-evolutionary dynamics of treatment-resistant cancer populations. We describe a variety of evolutionarily informed strategies designed to increase the probability of disease control or cure by anticipating and steering the evolutionary dynamics of acquired resistance.

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Crossref · 10.1038/s41571-020-0411-1

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References 105 · Cited by 227

Authors
Gatenby, R. A., & Brown, J. S.
Affiliations
Moffitt Cancer Center (US)
Corresponding author
Gatenby, Robert A.
Venue
Nature Reviews Clinical Oncology
Published
2020-07-22
Volume
17
Issue
11
Pages
675-686
ISSN
  • 1759-4774 (ISSN-L)
  • 1759-4782
OpenAlex
W3045230440
Cited by
227
References
105
Citations by year
2026: 39 · 2025: 41 · 2024: 34 · 2023: 43 · 2022: 27 · 2021: 35 · 2020: 7 · 2012: 1
FWCI
1.12
Type
journal article
Language
en
Open access
closed
Locations
  • Nature Reviews Clinical Oncology (publishedVersion)
  • PubMed (publishedVersion)
Funders
National Cancer Institute (R01CA187532, U54CA143970, U01CA232382, R01CA170595)
Topics
  • Physical Sciences › Mathematics › Modeling and Simulation › Mathematical Biology Tumor Growth
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
Keywords
tumor evolution, treatment resistance, eco-evolutionary dynamics, acquired drug resistance, metastatic cancer, resistance selection, dose optimization
MeSH terms
Antineoplastic Agents, Humans, Neoplasm Metastasis, Neoplasm Staging, Neoplasms, Drug Resistance, Neoplasm, Evolution, Molecular, Genetic Fitness

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