Literature DB >> 17329969

Stochastic dynamics of hematopoietic tumor stem cells.

David Dingli1, Arne Traulsen, Jorge M Pacheco.   

Abstract

Many tumors derive from the transformation of normal stem cells into cancer stem cells that retain their self-renewal capacity. This modern view of cancer has provided a natural explanation for the striking parallels which exist between these two different types of self-renewing cells. Here we develop a simple mathematical model to investigate the implications of this concept regarding the evolution of tumors in the hematopoietic system. Our results unequivocally demonstrate that stochastic effects related to the finite size of the active stem cell population have a profound influence on the dynamics of cancer evolution. For input parameters compatible with both the natural history of human cancer and mouse models, our results show how stochastic dynamics alone may lead to both remission in some cases and rapid expansion in others.

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Year:  2007        PMID: 17329969     DOI: 10.4161/cc.6.4.3853

Source DB:  PubMed          Journal:  Cell Cycle        ISSN: 1551-4005            Impact factor:   4.534


  42 in total

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6.  Analysis of stochastic stem cell models with control.

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7.  Tyrosine kinase inhibitor therapy can cure chronic myeloid leukemia without hitting leukemic stem cells.

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Journal:  Neoplasia       Date:  2008-11       Impact factor: 5.715

9.  On the dynamics of neutral mutations in a mathematical model for a homogeneous stem cell population.

Authors:  Arne Traulsen; Tom Lenaerts; Jorge M Pacheco; David Dingli
Journal:  J R Soc Interface       Date:  2012-12-05       Impact factor: 4.118

10.  Dynamics of leukemia stem-like cell extinction in acute promyelocytic leukemia.

Authors:  Benjamin Werner; Robert E Gallagher; Elisabeth M Paietta; Mark R Litzow; Martin S Tallman; Peter H Wiernik; James L Slack; Cheryl L Willman; Zhuoxin Sun; Arne Traulsen; David Dingli
Journal:  Cancer Res       Date:  2014-07-31       Impact factor: 12.701

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