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A stochastic population model for the impact of cancer cell dormancy on therapy success

  • Therapy evasion – and subsequent disease progression – is a major challenge in current oncology. An important role in this context seems to be played by various forms of cancer cell dormancy. For example, therapy-induced dormancy, over short timescales, can create serious obstacles to aggressive treatment approaches such as chemotherapy, and long-term dormancy may lead to relapses and metastases even many years after an initially successful treatment. The underlying dormancy-related mechanisms are complex and highly diverse, so that the analysis even of basic patterns of the population-level consequences of dormancy requires abstraction and idealization, as well as the identification of the relevant specific scenarios. In this paper, we focus on a situation in which individual cancer cells may switch into and out of a dormant state both spontaneously as well as in response to treatment, and over relatively short time-spans. We introduce a mathematical ‘toy model’, based on stochastic agent-based interactions, for the dynamics of cancer cell populations involving individual short-term dormancy, and allow for a range of (multi-drug) therapy protocols. Our analysis shows that in our idealized model, even a small initial population of dormant cells can lead to therapy failure under classical (and in the absence of dormancy successful) single-drug treatments. We further investigate the effectiveness of several multidrug regimes (manipulating dormant cancer cells in specific ways) and provide some basic rules for the design of (multi-)drug treatment protocols depending on the types and parameters of dormancy mechanisms present in the population.

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Author:Jochen BlathGND, Anna KrautGND, Tobias Paul, András József TóbiásORCiDGND
URN:urn:nbn:de:hebis:30:3-830252
URL:https://www.biorxiv.org/content/10.1101/2023.12.15.571717v1
DOI:https://doi.org/10.1101/2023.12.15.571717
Parent Title (English):bioRxiv
Publisher:bioRxiv
Document Type:Preprint
Language:English
Year of Completion:2023
Year of first Publication:2023
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2024/03/04
Tag:cancer cell dormancy; individual-based models; multi-drug treatment; resistance mutation; stochastic population dynamics; therapy evasion; treatment protocol design; treatment success
Issue:2023.12.15.571717 Version 1
Edition:Version 1
Page Number:29
HeBIS-PPN:516961098
Institutes:Informatik und Mathematik / Mathematik
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 51 Mathematik / 510 Mathematik
6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
MSC-Classification:34-XX ORDINARY DIFFERENTIAL EQUATIONS / 34Cxx Qualitative theory [See also 37-XX] / 34C60 Qualitative investigation and simulation of models
60-XX PROBABILITY THEORY AND STOCHASTIC PROCESSES (For additional applications, see 11Kxx, 62-XX, 90-XX, 91-XX, 92-XX, 93-XX, 94-XX) / 60Jxx Markov processes / 60J85 Applications of branching processes [See also 92Dxx]
92-XX BIOLOGY AND OTHER NATURAL SCIENCES / 92Cxx Physiological, cellular and medical topics / 92C50 Medical applications (general)
92-XX BIOLOGY AND OTHER NATURAL SCIENCES / 92Dxx Genetics and population dynamics / 92D25 Population dynamics (general)
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International