Cassidy, T. orcid.org/0000-0003-0757-0017, Nichol, D., Robertson-Tessi, M. et al. (2 more authors) (2021) The role of memory in non-genetic inheritance and its impact on cancer treatment resistance. PLOS Computational Biology, 17 (8). e1009348. ISSN: 1553-734X
Abstract
Intra-tumour heterogeneity is a leading cause of treatment failure and disease progression in cancer. While genetic mutations have long been accepted as a primary mechanism of generating this heterogeneity, the role of phenotypic plasticity is becoming increasingly apparent as a driver of intra-tumour heterogeneity. Consequently, understanding the role of this plasticity in treatment resistance and failure is a key component of improving cancer therapy. We develop a mathematical model of stochastic phenotype switching that tracks the evolution of drug-sensitive and drug-tolerant subpopulations to clarify the role of phenotype switching on population growth rates and tumour persistence. By including cytotoxic therapy in the model, we show that, depending on the strategy of the drug-tolerant subpopulation, stochastic phenotype switching can lead to either transient or permanent drug resistance. We study the role of phenotypic heterogeneity in a drug-resistant, genetically homogeneous population of non-small cell lung cancer cells to derive a rational treatment schedule that drives population extinction and avoids competitive release of the drug-tolerant sub-population. This model-informed therapeutic schedule results in increased treatment efficacy when compared against periodic therapy, and, most importantly, sustained tumour decay without the development of resistance.
Metadata
| Item Type: | Article |
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| Copyright, Publisher and Additional Information: | This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) |
| Date Deposited: | 04 Nov 2025 13:20 |
| Last Modified: | 04 Nov 2025 13:20 |
| Published Version: | https://journals.plos.org/ploscompbiol/article?id=... |
| Status: | Published |
| Publisher: | Public Library of Science (PLoS) |
| Identification Number: | 10.1371/journal.pcbi.1009348 |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:233807 |

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