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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2014
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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. |
format | Online Article Text |
id | pubmed-3973374 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
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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