Literature DB >> 24567385

The ecology in the hematopoietic stem cell niche determines the clinical outcome in chronic myeloid leukemia.

Adam L MacLean1, Sarah Filippi, Michael P H Stumpf.   

Abstract

Chronic myeloid leukemia (CML) is a blood disease that disrupts normal function of the hematopoietic system. Despite the great progress made in terms of molecular therapies for CML, there remain large gaps in our understanding. By comparing mathematical models that describe CML progression and etiology we sought to identify those models that provide the best description of disease dynamics and their underlying mechanisms. Data for two clinical outcomes--disease remission or relapse--are considered, and we investigate these using Bayesian inference techniques throughout. We find that it is not possible to choose between the models based on fits to the data alone; however, by studying model predictions we can discard models that fail to take niche effects into account. More detailed analysis of the remaining models reveals mechanistic differences: for one model, leukemia stem cell dynamics determine the disease outcome; and for the other model disease progression is determined at the stage of progenitor cells, in particular by differences in progenitor death rates. This analysis also reveals distinct transient dynamics that will be experimentally accessible, but are currently at the limits of what is possible to measure. To resolve these differences we need to be able to probe the hematopoietic stem cell niche directly. Our analysis highlights the importance of further mapping of the bone marrow hematopoietic niche microenvironment as the "ecological" interactions between cells in this niche appear to be intricately linked to disease outcome.

Entities:  

Keywords:  cancer progression; competition; model selection; niche dynamics

Mesh:

Year:  2014        PMID: 24567385      PMCID: PMC3956166          DOI: 10.1073/pnas.1317072111

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  28 in total

1.  Dynamic modeling of imatinib-treated chronic myeloid leukemia: functional insights and clinical implications.

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2.  The relationship between the spleen colony-forming cell and the haemopoietic stem cell.

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Journal:  Blood Cells       Date:  1978

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Authors:  François-Xavier Mahon
Journal:  Hematology Am Soc Hematol Educ Program       Date:  2012

4.  A mathematical model of hematopoiesis--I. Periodic chronic myelogenous leukemia.

Authors:  Caroline Colijn; Michael C Mackey
Journal:  J Theor Biol       Date:  2005-06-21       Impact factor: 2.691

5.  A cell initiating human acute myeloid leukaemia after transplantation into SCID mice.

Authors:  T Lapidot; C Sirard; J Vormoor; B Murdoch; T Hoang; J Caceres-Cortes; M Minden; B Paterson; M A Caligiuri; J E Dick
Journal:  Nature       Date:  1994-02-17       Impact factor: 49.962

6.  Kinetics of normal hematopoietic stem and progenitor cells in a Notch1-induced leukemia model.

Authors:  Xiaoxia Hu; Hongmei Shen; Chen Tian; Hui Yu; Guoguang Zheng; Richard XuFeng; Zhenyu Ju; Jing Xu; Jianmin Wang; Tao Cheng
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7.  Wnt signaling in the niche enforces hematopoietic stem cell quiescence and is necessary to preserve self-renewal in vivo.

Authors:  Heather E Fleming; Viktor Janzen; Cristina Lo Celso; Jun Guo; Kathleen M Leahy; Henry M Kronenberg; David T Scadden
Journal:  Cell Stem Cell       Date:  2008-03-06       Impact factor: 24.633

8.  GPU accelerated biochemical network simulation.

Authors:  Yanxiang Zhou; Juliane Liepe; Xia Sheng; Michael P H Stumpf; Chris Barnes
Journal:  Bioinformatics       Date:  2011-01-11       Impact factor: 6.937

9.  Dynamics of mutant cells in hierarchical organized tissues.

Authors:  Benjamin Werner; David Dingli; Tom Lenaerts; Jorge M Pacheco; Arne Traulsen
Journal:  PLoS Comput Biol       Date:  2011-12-01       Impact factor: 4.475

10.  Population dynamics of normal and leukaemia stem cells in the haematopoietic stem cell niche show distinct regimes where leukaemia will be controlled.

Authors:  Adam L MacLean; Cristina Lo Celso; Michael P H Stumpf
Journal:  J R Soc Interface       Date:  2013-01-24       Impact factor: 4.118

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  15 in total

1.  Parameter-free methods distinguish Wnt pathway models and guide design of experiments.

Authors:  Adam L MacLean; Zvi Rosen; Helen M Byrne; Heather A Harrington
Journal:  Proc Natl Acad Sci U S A       Date:  2015-02-17       Impact factor: 11.205

Review 2.  CBP/Catenin antagonists: Targeting LSCs' Achilles heel.

Authors:  Yong-Mi Kim; Eun-Ji Gang; Michael Kahn
Journal:  Exp Hematol       Date:  2017-05-04       Impact factor: 3.084

Review 3.  Chronic myeloid leukemia: advances in understanding disease biology and mechanisms of resistance to tyrosine kinase inhibitors.

Authors:  Christopher A Eide; Thomas O'Hare
Journal:  Curr Hematol Malig Rep       Date:  2015-06       Impact factor: 3.952

Review 4.  Chronic Myeloid Leukemia in the Era of Tyrosine Kinase Inhibitors: An Evolving Paradigm of Molecularly Targeted Therapy.

Authors:  Mohamed A M Ali
Journal:  Mol Diagn Ther       Date:  2016-08       Impact factor: 4.074

Review 5.  Chemokines as a Conductor of Bone Marrow Microenvironment in Chronic Myeloid Leukemia.

Authors:  Naofumi Mukaida; Yamato Tanabe; Tomohisa Baba
Journal:  Int J Mol Sci       Date:  2017-08-22       Impact factor: 5.923

Review 6.  Identifying niche-mediated regulatory factors of stem cell phenotypic state: a systems biology approach.

Authors:  Srikanth Ravichandran; Antonio Del Sol
Journal:  FEBS Lett       Date:  2017-01-30       Impact factor: 4.124

7.  Epithelial-Mesenchymal Transition in Metastatic Cancer Cell Populations Affects Tumor Dormancy in a Simple Mathematical Model.

Authors:  Adam L MacLean; Heather A Harrington; Michael P H Stumpf; Marc D H Hansen
Journal:  Biomedicines       Date:  2014-12-09

8.  Feedback mechanisms control coexistence in a stem cell model of acute myeloid leukaemia.

Authors:  Helena L Crowell; Adam L MacLean; Michael P H Stumpf
Journal:  J Theor Biol       Date:  2016-04-27       Impact factor: 2.691

9.  Systems Analysis of the Dynamic Inflammatory Response to Tissue Damage Reveals Spatiotemporal Properties of the Wound Attractant Gradient.

Authors:  Helen Weavers; Juliane Liepe; Aaron Sim; Will Wood; Paul Martin; Michael P H Stumpf
Journal:  Curr Biol       Date:  2016-07-14       Impact factor: 10.834

10.  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

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