Transition therapy: tackling the ecology of tumor phenotypic plasticity

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• dc.contributor.author Aguadé Gorgorió, Guim, 1991-
• dc.contributor.author Kauffman, Stuart
• dc.contributor.author Solé Vicente, Ricard, 1962-
• dc.date.accessioned 2022-02-11T07:07:07Z
• dc.date.available 2022-02-11T07:07:07Z
• dc.date.issued 2021
• dc.description.abstract Phenotypic switching in cancer cells has been found to be present across tumor types. Recent studies on Glioblastoma report a remarkably common architecture of four well-defined phenotypes coexisting within high levels of intra-tumor genetic heterogeneity. Similar dynamics have been shown to occur in breast cancer and melanoma and are likely to be found across cancer types. Given the adaptive potential of phenotypic switching (PHS) strategies, understanding how it drives tumor evolution and therapy resistance is a major priority. Here we present a mathematical framework uncovering the ecological dynamics behind PHS. The model is able to reproduce experimental results, and mathematical conditions for cancer progression reveal PHS-specific features of tumors with direct consequences on therapy resistance. In particular, our model reveals a threshold for the resistant-to-sensitive phenotype transition rate, below which any cytotoxic or switch-inhibition therapy is likely to fail. The model is able to capture therapeutic success thresholds for cancers where nonlinear growth dynamics or larger PHS architectures are in place, such as glioblastoma or melanoma. By doing so, the model presents a novel set of conditions for the success of combination therapies able to target replication and phenotypic transitions at once. Following our results, we discuss transition therapy as a novel scheme to target not only combined cytotoxicity but also the rates of phenotypic switching.
• dc.description.sponsorship This work was supported by the Botín Foundation by Banco Santander through its Santander Universities Global Division, the Spanish Ministry of Economy and Competitiveness, grant FIS2016-77447-R MINECO/AEI/FEDER, an AGAUR FI 2018 grant, and the Santa Fe Institute where most of this work was done.
• dc.format.mimetype application/pdf
• dc.identifier.citation Aguadé-Gorgorió G, Kauffman S, Solé R. Transition therapy: tackling the ecology of tumor phenotypic plasticity. Bull Math Biol. 2021;84(1):24. DOI: 10.1007/s11538-021-00970-9
• dc.identifier.doi http://dx.doi.org/10.1007/s11538-021-00970-9
• dc.identifier.issn 0092-8240
• dc.identifier.uri http://hdl.handle.net/10230/52468
• dc.language.iso eng
• dc.publisher Springer
• dc.relation.ispartof Bull Math Biol. 2021;84(1):24
• dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/FIS2016-77447-R
• dc.rights © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Cancer ecology
• dc.subject.keyword Combination therapies
• dc.subject.keyword Epigenetic plasticity
• dc.subject.keyword Phenotypic switching
• dc.subject.keyword Transition therapy
• dc.title Transition therapy: tackling the ecology of tumor phenotypic plasticity
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion