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Clonal selection and therapy resistance in acute leukaemias: mathematical modelling explains different proliferation patterns at diagnosis and relapse

Recent experimental evidence suggests that acute myeloid leukaemias may originate from multiple clones of malignant cells. Nevertheless, it is not known how the observed clones may differ with respect to cell properties, such as proliferation and self-renewal. There are scarcely any data on how thes...

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Detalles Bibliográficos
Autores principales: Stiehl, Thomas, Baran, Natalia, Ho, Anthony D., Marciniak-Czochra, Anna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3973374/
https://www.ncbi.nlm.nih.gov/pubmed/24621818
http://dx.doi.org/10.1098/rsif.2014.0079
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author Stiehl, Thomas
Baran, Natalia
Ho, Anthony D.
Marciniak-Czochra, Anna
author_facet Stiehl, Thomas
Baran, Natalia
Ho, Anthony D.
Marciniak-Czochra, Anna
author_sort Stiehl, Thomas
collection PubMed
description Recent experimental evidence suggests that acute myeloid leukaemias may originate from multiple clones of malignant cells. Nevertheless, it is not known how the observed clones may differ with respect to cell properties, such as proliferation and self-renewal. There are scarcely any data on how these cell properties change due to chemotherapy and relapse. We propose a new mathematical model to investigate the impact of cell properties on the multi-clonal composition of leukaemias. Model results imply that enhanced self-renewal may be a key mechanism in the clonal selection process. Simulations suggest that fast proliferating and highly self-renewing cells dominate at primary diagnosis, while relapse following therapy-induced remission is triggered mostly by highly self-renewing but slowly proliferating cells. Comparison of simulation results to patient data demonstrates that the proposed model is consistent with clinically observed dynamics based on a clonal selection process.
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spelling pubmed-39733742014-05-06 Clonal selection and therapy resistance in acute leukaemias: mathematical modelling explains different proliferation patterns at diagnosis and relapse Stiehl, Thomas Baran, Natalia Ho, Anthony D. Marciniak-Czochra, Anna J R Soc Interface Research Articles Recent experimental evidence suggests that acute myeloid leukaemias may originate from multiple clones of malignant cells. Nevertheless, it is not known how the observed clones may differ with respect to cell properties, such as proliferation and self-renewal. There are scarcely any data on how these cell properties change due to chemotherapy and relapse. We propose a new mathematical model to investigate the impact of cell properties on the multi-clonal composition of leukaemias. Model results imply that enhanced self-renewal may be a key mechanism in the clonal selection process. Simulations suggest that fast proliferating and highly self-renewing cells dominate at primary diagnosis, while relapse following therapy-induced remission is triggered mostly by highly self-renewing but slowly proliferating cells. Comparison of simulation results to patient data demonstrates that the proposed model is consistent with clinically observed dynamics based on a clonal selection process. The Royal Society 2014-05-06 /pmc/articles/PMC3973374/ /pubmed/24621818 http://dx.doi.org/10.1098/rsif.2014.0079 Text en http://creativecommons.org/licenses/by/3.0/ © 2014 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Research Articles
Stiehl, Thomas
Baran, Natalia
Ho, Anthony D.
Marciniak-Czochra, Anna
Clonal selection and therapy resistance in acute leukaemias: mathematical modelling explains different proliferation patterns at diagnosis and relapse
title Clonal selection and therapy resistance in acute leukaemias: mathematical modelling explains different proliferation patterns at diagnosis and relapse
title_full Clonal selection and therapy resistance in acute leukaemias: mathematical modelling explains different proliferation patterns at diagnosis and relapse
title_fullStr Clonal selection and therapy resistance in acute leukaemias: mathematical modelling explains different proliferation patterns at diagnosis and relapse
title_full_unstemmed Clonal selection and therapy resistance in acute leukaemias: mathematical modelling explains different proliferation patterns at diagnosis and relapse
title_short Clonal selection and therapy resistance in acute leukaemias: mathematical modelling explains different proliferation patterns at diagnosis and relapse
title_sort clonal selection and therapy resistance in acute leukaemias: mathematical modelling explains different proliferation patterns at diagnosis and relapse
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3973374/
https://www.ncbi.nlm.nih.gov/pubmed/24621818
http://dx.doi.org/10.1098/rsif.2014.0079
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