Research article Special Issues

Adaptive dynamics of hematopoietic stem cells and their supporting stroma: a model and mathematical analysis

  • Received: 22 December 2018 Accepted: 07 May 2019 Published: 29 May 2019
  • We propose a mathematical model to describe the evolution of hematopoietic stem cells (HSCs) and stromal cells in considering the bi-directional interaction between them. Cancerous cells are also taken into account in our model. HSCs are structured by a continuous phenotype characterising the population heterogeneity in a way relevant to the question at stake while stromal cells are structured by another continuous phenotype representing their capacity of support to HSCs. We then analyse the model in the framework of adaptive dynamics. More precisely, we study single Dirac mass steady states, their linear stability and we investigate the role of parameters in the model on the nature of the evolutionary stable distributions (ESDs) such as monomorphism, dimorphism and the uniqueness properties. We also study the dominant phenotypes by an asymptotic approach and we obtain the equation for dominant phenotypes. Numerical simulations are employed to illustrate our analytical results. In particular, we represent the case of the invasion of malignant cells as well as the case of co-existence of cancerous cells and healthy HSCs.

    Citation: Thanh Nam Nguyen, Jean Clairambault, Thierry Jaffredo, Benoît Perthame, Delphine Salort. Adaptive dynamics of hematopoietic stem cells and their supporting stroma: a model and mathematical analysis[J]. Mathematical Biosciences and Engineering, 2019, 16(5): 4818-4845. doi: 10.3934/mbe.2019243

    Related Papers:

  • We propose a mathematical model to describe the evolution of hematopoietic stem cells (HSCs) and stromal cells in considering the bi-directional interaction between them. Cancerous cells are also taken into account in our model. HSCs are structured by a continuous phenotype characterising the population heterogeneity in a way relevant to the question at stake while stromal cells are structured by another continuous phenotype representing their capacity of support to HSCs. We then analyse the model in the framework of adaptive dynamics. More precisely, we study single Dirac mass steady states, their linear stability and we investigate the role of parameters in the model on the nature of the evolutionary stable distributions (ESDs) such as monomorphism, dimorphism and the uniqueness properties. We also study the dominant phenotypes by an asymptotic approach and we obtain the equation for dominant phenotypes. Numerical simulations are employed to illustrate our analytical results. In particular, we represent the case of the invasion of malignant cells as well as the case of co-existence of cancerous cells and healthy HSCs.


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    [1] M. C. Mackey, Unified hypothesis for the origin of aplastic anemia and periodic hematopoiesis, Blood, 51 (1978), 941–956.
    [2] F. Burns and I. Tannock, On the existence of a G 0 -phase in the cell cycle, Cell Prolif., 3 (1970), 321–334.
    [3] L. Lajtha, On DNA labeling in the study of the dynamics of bone marrow cell populations, F. StohlmanJr.(Ed.), The KineticsofCellularProliferation, Gruneand Stratton, NewYork, 173–182.
    [4] M. Adimy, S. Bernard, J. Clairambault, et al., Modélisation de la dynamique de l'hématopoïèse normale et pathologique, Hématologie, 14 (2008), 339–350.
    [5] M. C. Mackey, C. Ou, L. Pujo-Menjouet, et al., Periodic oscillations of blood cell populations in chronic myelogenous leukemia, SIAM J. Math. Anal., 38 (2006), 166–187.
    [6] M. Adimy, F. Crauste and S. Ruan, A mathematical study of the hematopoiesis process with applications to chronic myelogenous leukemia, SIAM J. Appl. Math., 65 (2005), 1328–1352.
    [7] L. Pujo-Menjouet, S. Bernard and M. C. Mackey, Long period oscillations in a G 0 model of hematopoietic stem cells, SIAM J. Appl. Dyn. Syst., 4 (2005), 312–332.
    [8] M. Adimy, F. Crauste and S. Ruan, Periodic oscillations in leukopoiesis models with two delays, J. Theor. Biol., 242 (2006), 288–299.
    [9] A. Ducrot and V. Volpert, On a model of Leukemia development with a spatial cell distribution, Math. Model. Nat. Phenom., 2 (2007), 101–120.
    [10] G. Clapp and D. Levy, A review of mathematical models for leukemia and lymphoma, Drug Discov. Today Dis. Models, 16 (2015), 1–6.
    [11] L. Pujo-Menjouet, Blood cell dynamics: half of a century of modelling, Math. Model. Nat. Phenom., 11 (2016), 92–115.
    [12] B. A. Anthony and D. C. Link, Regulation of hematopoietic stem cells by bone marrow stromal cells, Trends Immunol., 35 (2014), 32–37.
    [13] G. Stik, L. Petit, P. Charbord, et al., Vésicules extracellulaires stromales et régulation des cellules souches et progéniteurs hématopoï étiques, médecine/sciences, 34 (2018), 114–116.
    [14] P. Charbord, T. Jaffredo and C. Durand, Le cœur moléculaire de la fonction de la niche des cellules souches hématopoï étiques, médecine/sciences, 31 (2015), 12–14.
    [15] P. Hirsch, Y. Zhang, R. Tang, et al., Genetic hierarchy and temporal variegation in the clonal history of acute myeloid leukaemia, Nat. commun., 7 (2016), 12475.
    [16] P.-E. Jabin and G. Raoul, On selection dynamics for competitive interactions, J. Math. Biol., 63 (2011), 493–517.
    [17] C. Pouchol, J. Clairambault, A. Lorz, et al., Asymptotic analysis and optimal control of an integro- differential system modelling healthy and cancer cells exposed to chemotherapy, J. Math. Pures Appl., 116 (2018), 268–308.
    [18] C. Pouchol and E. Trélat, Global stability with selection in integro-differential Lotka-Volterra systems modelling trait-structured populations, J. Biol.l Dyn., 12 (2018), 872–893.
    [19] G. Barles and B. Perthame, Dirac concentrations in Lotka-Volterra parabolic PDEs, Indiana Univ. Math. J., 57 (2008), 3275–3301.
    [20] O. Diekmann, A beginner's guide to adaptive dynamics, Banach Center Publications, 63 (2003), 47–86.
    [21] O. Diekmann, P.-E. Jabin, S. Mischler, et al., The dynamics of adaptation: An illuminating example and a hamilton–jacobi approach, Theor. Popul. Biol., 67 (2005), 257–271.
    [22] W. Djema, C. Bonnet, F. Mazenc, et al., Control in dormancy or eradication of cancer stem cells: Mathematical modeling and stability issues, J. Theor. Biol., 449 (2018), 103–123.
    [23] A. Lorz, S. Mirrahimi and B. Perthame, Dirac mass dynamics in multidimensional nonlocal parabolic equations, Commun Part. Diff. Eq., 36 (2011), 1071–1098.
    [24] A. Lorz and B. Perthame, Long-term behaviour of phenotypically structured models, Proc. R. Soc. Lond. Ser. A Math. Phys. Eng. Sci., 470 (2014), 20140089, 10.
    [25] G. Meszéna, I. Czibula and S. Geritz, Adaptive dynamics in a 2-patch environment: A toy model for allopatric and parapatric speciation, J. Biol. Syst., 5 (1997), 265–284.
    [26] S. Mirrahimi and J.-M. Roquejoffre, A class of Hamilton-Jacobi equations with constraint: uniqueness and constructive approach, J. Differ. Equations, 260 (2016), 4717–4738.
    [27] J. D. Murray, Mathematical biology. I, vol. 17 of Interdisciplinary Applied Mathematics, 3rd edition, Springer-Verlag, New York, 2002, An introduction.
    [28] B. Perthame, Transport equations in biology, Frontiers in Mathematics, Birkhäuser Verlag, Basel, 2007.
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