ArticleEvolutionary applications2018
Adaptive dynamics of unstable cancer populations: The canonical equation.
Article in Evolutionary applications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Reducing phenotype-structured partial differential equations models of cancer evolution to systems of ordinary differential equations: a generalised moment dynamics approach.Journal of mathematical biology · 2025Article
- Modeling tumors as complex ecosystems.iScience · 2024Review
- Modeling tumors as species-rich ecological communities.bioRxiv : the preprint server for biology · 2024Article
- Single-cell phylogenies reveal changes in the evolutionary rate within cancer and healthy tissues.Cell genomics · 2023Article
- Modeling cancer's ecological and evolutionary dynamics.Medical oncology (Northwood, London, England) · 2023Article
- Biomarkers or biotargets? Using competition to lure cancer cells into evolutionary traps.Evolution, medicine, and public health · 2023Article
- Do mechanisms matter? Comparing cancer treatment strategies across mathematical models and outcome objectives.Mathematical biosciences and engineering : MBE · 2021Article
- Long Noncoding RNAs in Gastrointestinal Cancer: Tumor Suppression Versus Tumor Promotion.Digestive diseases and sciences · 2021Review
- Genetic instability as a driver for immune surveillance.Journal for immunotherapy of cancer · 2019Article
- Adaptive dynamics of unstable cancer populations: The canonical equation.Evolutionary applications · 2018Article
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2 authors.
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Abstract
In most instances of tumour development, genetic instability plays a role in allowing cancer cell populations to respond to selection barriers, such as physical constraints or immune responses, and rapidly adapt to an always changing environment. Modelling instability is a nontrivial task, since by definition evolving instability leads to changes in the underlying landscape. In this article, we explore mathematically a simple version of unstable tumour progression using the formalism of adaptive dynamics (AD) where selection and mutation are explicitly coupled. Using a set of basic fitness landscapes, the so-called canonical equation for the evolution of genetic instability on a minimal scenario associated with a population of unstable cells is derived. We obtain explicit expressions for the evolution of mutation probabilities, and the implications of the model on further experimental studies and potential mutagenic therapies are discussed.
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