Literature DB >> 22210402

Strategies for cancer stem cell elimination: insights from mathematical modeling.

Vladimir Vainstein1, Oleg U Kirnasovsky, Yuri Kogan, Zvia Agur.   

Abstract

The cancer stem cell (CSC) hypothesis states that only a small fraction of a malignant cell population is responsible for tumor growth and relapse. Understanding the relationships between CSC dynamics and cancer progression may contribute to improvements in cancer treatment. Analysis of a simple discrete mathematical model has suggested that homeostasis in developing tissues is governed by a "quorum sensing" control mechanism, in which stem cells differentiate or proliferate according to feedback they receive from neighboring cell populations. Further analysis of the same model has indicated that excessive stem cell proliferation leading to malignant transformation mainly results from altered sensitivity to such micro-environmental signals. Our aim in this work is to expand the analysis to the dynamics of established populations of cancer cells and to examine possible therapeutic avenues for eliminating CSCs. The proposed model considers two populations of cells: CSCs, which can divide indefinitely, and differentiated cancer cells, which do not divide and have a limited lifespan. We assume that total cell density has negative feedback on CSC proliferation and that high CSC density activates CSC differentiation. We show that neither stimulation of CSC differentiation nor inhibition of CSC proliferation alone is sufficient for complete CSC elimination and cancer cure, since each of these two therapies affects a different subpopulation of CSCs. However, a combination of these two strategies can substantially reduce the population sizes and densities of all types of cancer cells. Therefore, we propose that in clinical trials, CSC differentiation therapy should only be examined in combination with chemotherapy. Our conclusions are corroborated by clinical experience with differentiating agents in acute promyelocytic leukemia and neuroblastoma. Copyright Â
© 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 22210402     DOI: 10.1016/j.jtbi.2011.12.016

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


  13 in total

1.  Analysis of a mathematical model of apoptosis: individual differences and malfunction in programmed cell death.

Authors:  Elife Zerrin Bagci; S Murat Sen; Mehmet C Camurdan
Journal:  J Clin Monit Comput       Date:  2013-04-21       Impact factor: 2.502

2.  Brain Metastases: Insights from Statistical Modeling of Size Distribution.

Authors:  M Buller; K M Chapple; C R Bird
Journal:  AJNR Am J Neuroradiol       Date:  2020-04-02       Impact factor: 3.825

3.  Defective quorum sensing of acute lymphoblastic leukemic cells: evidence of collective behavior of leukemic populations as semi-autonomous aberrant ecosystems.

Authors:  Sapan J Patel; Su Dao; Costel C Darie; Bayard D Clarkson
Journal:  Am J Cancer Res       Date:  2016-06-01       Impact factor: 6.166

4.  In silico study of the impact of cancer stem cell dynamics and radiobiological hypoxia on tumour response to hyperfractionated radiotherapy.

Authors:  L G Marcu; D Marcu; S M Filip
Journal:  Cell Prolif       Date:  2016-04-15       Impact factor: 6.831

5.  An agent-based model of cancer stem cell initiated avascular tumour growth and metastasis: the effect of seeding frequency and location.

Authors:  Kerri-Ann Norton; Aleksander S Popel
Journal:  J R Soc Interface       Date:  2014-11-06       Impact factor: 4.118

Review 6.  What Tumor Dynamics Modeling Can Teach us About Exploiting the Stem-Cell View for Better Cancer Treatment.

Authors:  Roger S Day
Journal:  Cancer Inform       Date:  2015-02-24

7.  Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata.

Authors:  Ángel Monteagudo; José Santos
Journal:  PLoS One       Date:  2015-07-15       Impact factor: 3.240

8.  A mathematical model of cancer stem cell driven tumor initiation: implications of niche size and loss of homeostatic regulatory mechanisms.

Authors:  Sara N Gentry; Trachette L Jackson
Journal:  PLoS One       Date:  2013-08-19       Impact factor: 3.240

9.  Dynamic regulation of the cancer stem cell compartment by Cripto-1 in colorectal cancer.

Authors:  F Francescangeli; P Contavalli; M L De Angelis; M Baiocchi; G Gambara; A Pagliuca; A Fiorenzano; C Prezioso; A Boe; M Todaro; G Stassi; N P Castro; K Watanabe; D S Salomon; R De Maria; G Minchiotti; A Zeuner
Journal:  Cell Death Differ       Date:  2015-03-20       Impact factor: 15.828

10.  Estimating dose painting effects in radiotherapy: a mathematical model.

Authors:  Juan Carlos López Alfonso; Nick Jagiella; Luis Núñez; Miguel A Herrero; Dirk Drasdo
Journal:  PLoS One       Date:  2014-02-26       Impact factor: 3.240

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