Literature DB >> 33130064

Effect of feedback regulation on stem cell fractions in tissues and tumors: Understanding chemoresistance in cancer.

Lora D Weiss1, P van den Driessche2, John S Lowengrub1, Dominik Wodarz3, Natalia L Komarova4.   

Abstract

While resistance mutations are often implicated in the failure of cancer therapy, lack of response also occurs without such mutants. In bladder cancer mouse xenografts, repeated chemotherapy cycles have resulted in cancer stem cell (CSC) enrichment, and consequent loss of therapy response due to the reduced susceptibility of CSCs to drugs. A particular feedback loop present in the xenografts has been shown to promote CSC enrichment in this system. Yet, many other regulatory loops might also be operational and might promote CSC enrichment. Their identification is central to improving therapy response. Here, we perform a comprehensive mathematical analysis to define what types of regulatory feedback loops can and cannot contribute to CSC enrichment, providing guidance to the experimental identification of feedback molecules. We derive a formula that reveals whether or not the cell population experiences CSC enrichment over time, based on the properties of the feedback. We find that negative feedback on the CSC division rate or positive feedback on differentiated cell death rate can lead to CSC enrichment. Further, the feedback mediators that achieve CSC enrichment can be secreted by either CSCs or by more differentiated cells. The extent of enrichment is determined by the CSC death rate, the CSC self-renewal probability, and by feedback strength. Defining these general characteristics of feedback loops can guide the experimental screening for and identification of feedback mediators that can promote CSC enrichment in bladder cancer and potentially other tumors. This can help understand and overcome the phenomenon of CSC-based therapy resistance.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bladder cancer; Feedback loops; Hierarchical tissues; Lineages; Mathematical modeling

Mesh:

Year:  2020        PMID: 33130064      PMCID: PMC8445233          DOI: 10.1016/j.jtbi.2020.110499

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  41 in total

1.  Activin and GDF11 collaborate in feedback control of neuroepithelial stem cell proliferation and fate.

Authors:  Kimberly K Gokoffski; Hsiao-Huei Wu; Crestina L Beites; Joon Kim; Euiseok J Kim; Martin M Matzuk; Jane E Johnson; Arthur D Lander; Anne L Calof
Journal:  Development       Date:  2011-08-18       Impact factor: 6.868

Review 2.  Tumour stem cells and drug resistance.

Authors:  Michael Dean; Tito Fojo; Susan Bates
Journal:  Nat Rev Cancer       Date:  2005-04       Impact factor: 60.716

Review 3.  Cancer epigenetics: tumor heterogeneity, plasticity of stem-like states, and drug resistance.

Authors:  Hariharan Easwaran; Hsing-Chen Tsai; Stephen B Baylin
Journal:  Mol Cell       Date:  2014-06-05       Impact factor: 17.970

4.  Evolutionary dynamics of feedback escape and the development of stem-cell-driven cancers.

Authors:  Ignacio A Rodriguez-Brenes; Natalia L Komarova; Dominik Wodarz
Journal:  Proc Natl Acad Sci U S A       Date:  2011-11-14       Impact factor: 11.205

Review 5.  Cancer stem cells: small subpopulation or evolving fraction?

Authors:  Heiko Enderling
Journal:  Integr Biol (Camb)       Date:  2015-01       Impact factor: 2.192

6.  Blocking PGE2-induced tumour repopulation abrogates bladder cancer chemoresistance.

Authors:  Antonina V Kurtova; Jing Xiao; Qianxing Mo; Senthil Pazhanisamy; Ross Krasnow; Seth P Lerner; Fengju Chen; Terrence T Roh; Erica Lay; Philip Levy Ho; Keith Syson Chan
Journal:  Nature       Date:  2014-12-03       Impact factor: 49.962

Review 7.  Mathematical models of cancer stem cells.

Authors:  Franziska Michor
Journal:  J Clin Oncol       Date:  2008-06-10       Impact factor: 44.544

8.  Association of reactive oxygen species levels and radioresistance in cancer stem cells.

Authors:  Maximilian Diehn; Robert W Cho; Neethan A Lobo; Tomer Kalisky; Mary Jo Dorie; Angela N Kulp; Dalong Qian; Jessica S Lam; Laurie E Ailles; Manzhi Wong; Benzion Joshua; Michael J Kaplan; Irene Wapnir; Frederick M Dirbas; George Somlo; Carlos Garberoglio; Benjamin Paz; Jeannie Shen; Sean K Lau; Stephen R Quake; J Martin Brown; Irving L Weissman; Michael F Clarke
Journal:  Nature       Date:  2009-04-09       Impact factor: 49.962

9.  Mathematical modeling of the impact of cytokine response of acute myeloid leukemia cells on patient prognosis.

Authors:  Thomas Stiehl; Anthony D Ho; Anna Marciniak-Czochra
Journal:  Sci Rep       Date:  2018-02-12       Impact factor: 4.379

10.  Cell lineages and the logic of proliferative control.

Authors:  Arthur D Lander; Kimberly K Gokoffski; Frederic Y M Wan; Qing Nie; Anne L Calof
Journal:  PLoS Biol       Date:  2009-01-20       Impact factor: 8.029

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  1 in total

1.  Spatial dynamics of feedback and feedforward regulation in cell lineages.

Authors:  Peter Uhl; John Lowengrub; Natalia Komarova; Dominik Wodarz
Journal:  PLoS Comput Biol       Date:  2022-05-06       Impact factor: 4.779

  1 in total

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