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On a mathematical model of tumor growth based on cancer stem cells

  • We consider a simple mathematical model of tumor growth based on cancer stem cells. The model consists of four hyperbolic equations of first order to describe the evolution ofdifferent subpopulations of cells: cancer stem cells, progenitor cells, differentiated cells and dead cells. A fifth equation is introduced to model the evolution of the moving boundary. The system includes non-local terms of integral type in the coefficients. Under some restrictions in the parameters we show thatthere exists a unique homogeneous steady state which is stable.

    Citation: J. Ignacio Tello. On a mathematical model of tumor growth based on cancer stem cells[J]. Mathematical Biosciences and Engineering, 2013, 10(1): 263-278. doi: 10.3934/mbe.2013.10.263

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  • We consider a simple mathematical model of tumor growth based on cancer stem cells. The model consists of four hyperbolic equations of first order to describe the evolution ofdifferent subpopulations of cells: cancer stem cells, progenitor cells, differentiated cells and dead cells. A fifth equation is introduced to model the evolution of the moving boundary. The system includes non-local terms of integral type in the coefficients. Under some restrictions in the parameters we show thatthere exists a unique homogeneous steady state which is stable.


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  • This article has been cited by:

    1. Sara N. Gentry, Trachette L. Jackson, Shree Ram Singh, A Mathematical Model of Cancer Stem Cell Driven Tumor Initiation: Implications of Niche Size and Loss of Homeostatic Regulatory Mechanisms, 2013, 8, 1932-6203, e71128, 10.1371/journal.pone.0071128
    2. Youshan Tao, Qian Guo, Kazuyuki Aihara, A partial differential equation model and its reduction to an ordinary differential equation model for prostate tumor growth under intermittent hormone therapy, 2014, 69, 0303-6812, 817, 10.1007/s00285-013-0718-y
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    6. Azim Rivaz, Mahdieh Azizian, Madjid Soltani, Various Mathematical Models of Tumor Growth with Reference to Cancer Stem Cells: A Review, 2019, 43, 1028-6276, 687, 10.1007/s40995-019-00681-w
    7. L. G. Marcu, D. Marcu, S. M. Filip, In silicostudy of the impact of cancer stem cell dynamics and radiobiological hypoxia on tumour response to hyperfractionated radiotherapy, 2016, 49, 09607722, 304, 10.1111/cpr.12251
    8. Mihaela Negreanu, J. Ignacio Tello, Asymptotic stability of a mathematical model of cell population, 2014, 415, 0022247X, 963, 10.1016/j.jmaa.2014.02.032
    9. Alexander T. Pearson, Patrick Ingram, Shoumei Bai, Patrick O'Hayer, Jaehoon Chung, Euisik Yoon, Trachette Jackson, Ronald J. Buckanovich, Sampling from single-cell observations to predict tumor cell growth in-vitro and in-vivo, 2017, 8, 1949-2553, 111176, 10.18632/oncotarget.22693
    10. Alexander T. Pearson, Trachette L. Jackson, Jacques E. Nör, Modeling head and neck cancer stem cell-mediated tumorigenesis, 2016, 73, 1420-682X, 3279, 10.1007/s00018-016-2226-x
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