Literature DB >> 19101772

An "age"-structured model of hematopoietic stem cell organization with application to chronic myeloid leukemia.

Ingo Roeder1, Maria Herberg, Matthias Horn.   

Abstract

Previously, we have modeled hematopoietic stem cell organization by a stochastic, single cell-based approach. Applications to different experimental systems demonstrated that this model consistently explains a broad variety of in vivo and in vitro data. A major advantage of the agent-based model (ABM) is the representation of heterogeneity within the hematopoietic stem cell population. However, this advantage comes at the price of time-consuming simulations if the systems become large. One example in this respect is the modeling of disease and treatment dynamics in patients with chronic myeloid leukemia (CML), where the realistic number of individual cells to be considered exceeds 10(6). To overcome this deficiency, without losing the representation of the inherent heterogeneity of the stem cell population, we here propose to approximate the ABM by a system of partial differential equations (PDEs). The major benefit of such an approach is its independence from the size of the system. Although this mean field approach includes a number of simplifying assumptions compared to the ABM, it retains the key structure of the model including the "age"-structure of stem cells. We show that the PDE model qualitatively and quantitatively reproduces the results of the agent-based approach.

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Year:  2008        PMID: 19101772     DOI: 10.1007/s11538-008-9373-7

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  8 in total

1.  Structured models of cell migration incorporating molecular binding processes.

Authors:  Pia Domschke; Dumitru Trucu; Alf Gerisch; Mark A J Chaplain
Journal:  J Math Biol       Date:  2017-04-12       Impact factor: 2.259

2.  Long-term treatment effects in chronic myeloid leukemia.

Authors:  Apollos Besse; Thomas Lepoutre; Samuel Bernard
Journal:  J Math Biol       Date:  2017-01-25       Impact factor: 2.259

3.  A Review of Mathematical Models for Leukemia and Lymphoma.

Authors:  Geoffrey Clapp; Doron Levy
Journal:  Drug Discov Today Dis Models       Date:  2014-11-29

4.  Computational modeling of stem and progenitor cell kinetics identifies plausible hematopoietic lineage hierarchies.

Authors:  Lisa Bast; Michèle C Buck; Judith S Hecker; Robert A J Oostendorp; Katharina S Götze; Carsten Marr
Journal:  iScience       Date:  2021-01-29

5.  Stem cell proliferation and quiescence--two sides of the same coin.

Authors:  Ingmar Glauche; Kateri Moore; Lars Thielecke; Katrin Horn; Markus Loeffler; Ingo Roeder
Journal:  PLoS Comput Biol       Date:  2009-07-24       Impact factor: 4.475

6.  Dynamical models of mutated chronic myelogenous leukemia cells for a post-imatinib treatment scenario: Response to dasatinib or nilotinib therapy.

Authors:  Clemens Woywod; Franz X Gruber; Richard A Engh; Tor Flå
Journal:  PLoS One       Date:  2017-07-05       Impact factor: 3.240

7.  Modelling stem cell ageing: a multi-compartment continuum approach.

Authors:  Yanli Wang; Wing-Cheong Lo; Ching-Shin Chou
Journal:  R Soc Open Sci       Date:  2020-03-18       Impact factor: 2.963

8.  Mathematical modeling reveals the factors involved in the phenomena of cancer stem cells stabilization.

Authors:  Nikolay Bessonov; Guillaume Pinna; Andrey Minarsky; Annick Harel-Bellan; Nadya Morozova
Journal:  PLoS One       Date:  2019-11-11       Impact factor: 3.240

  8 in total

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