Modeling stress-induced responses : plasticity in continuous state space and gradual clonal evolution
(2024) In Theory in Biosciences- Abstract
Mathematical models of cancer and bacterial evolution have generally stemmed from a gene-centric framework, assuming clonal evolution via acquisition of resistance-conferring mutations and selection of their corresponding subpopulations. More recently, the role of phenotypic plasticity has been recognized and models accounting for phenotypic switching between discrete cell states (e.g., epithelial and mesenchymal) have been developed. However, seldom do models incorporate both plasticity and mutationally driven resistance, particularly when the state space is continuous and resistance evolves in a continuous fashion. In this paper, we develop a framework to model plastic and mutational mechanisms of acquiring resistance in a continuous... (More)
Mathematical models of cancer and bacterial evolution have generally stemmed from a gene-centric framework, assuming clonal evolution via acquisition of resistance-conferring mutations and selection of their corresponding subpopulations. More recently, the role of phenotypic plasticity has been recognized and models accounting for phenotypic switching between discrete cell states (e.g., epithelial and mesenchymal) have been developed. However, seldom do models incorporate both plasticity and mutationally driven resistance, particularly when the state space is continuous and resistance evolves in a continuous fashion. In this paper, we develop a framework to model plastic and mutational mechanisms of acquiring resistance in a continuous gradual fashion. We use this framework to examine ways in which cancer and bacterial populations can respond to stress and consider implications for therapeutic strategies. Although we primarily discuss our framework in the context of cancer and bacteria, it applies broadly to any system capable of evolving via plasticity and genetic evolution.
(Less)
- author
- Bukkuri, Anuraag LU
- organization
- publishing date
- 2024
- type
- Contribution to journal
- publication status
- epub
- subject
- keywords
- Bacterial evolution, Cancer evolution, Eco-evolutionary dynamics, Plasticity, Therapeutic resistance
- in
- Theory in Biosciences
- publisher
- Springer
- external identifiers
-
- scopus:85183610716
- ISSN
- 1431-7613
- DOI
- 10.1007/s12064-023-00410-3
- language
- English
- LU publication?
- yes
- id
- 33d9e44a-b3cb-41fb-b0a1-41504afeb638
- date added to LUP
- 2024-02-21 15:48:00
- date last changed
- 2024-02-21 15:48:43
@article{33d9e44a-b3cb-41fb-b0a1-41504afeb638,
abstract = {{<p>Mathematical models of cancer and bacterial evolution have generally stemmed from a gene-centric framework, assuming clonal evolution via acquisition of resistance-conferring mutations and selection of their corresponding subpopulations. More recently, the role of phenotypic plasticity has been recognized and models accounting for phenotypic switching between discrete cell states (e.g., epithelial and mesenchymal) have been developed. However, seldom do models incorporate both plasticity and mutationally driven resistance, particularly when the state space is continuous and resistance evolves in a continuous fashion. In this paper, we develop a framework to model plastic and mutational mechanisms of acquiring resistance in a continuous gradual fashion. We use this framework to examine ways in which cancer and bacterial populations can respond to stress and consider implications for therapeutic strategies. Although we primarily discuss our framework in the context of cancer and bacteria, it applies broadly to any system capable of evolving via plasticity and genetic evolution.</p>}},
author = {{Bukkuri, Anuraag}},
issn = {{1431-7613}},
keywords = {{Bacterial evolution; Cancer evolution; Eco-evolutionary dynamics; Plasticity; Therapeutic resistance}},
language = {{eng}},
publisher = {{Springer}},
series = {{Theory in Biosciences}},
title = {{Modeling stress-induced responses : plasticity in continuous state space and gradual clonal evolution}},
url = {{http://dx.doi.org/10.1007/s12064-023-00410-3}},
doi = {{10.1007/s12064-023-00410-3}},
year = {{2024}},
}