Mathematical Modelling of Cancer Stem Cells Population Behavior

E. Beretta; V. Capasso; N. Morozova

Mathematical Modelling of Natural Phenomena (2012)

  • Volume: 7, Issue: 1, page 279-305
  • ISSN: 0973-5348

Abstract

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Recent discovery of cancer stem cells in tumorigenic tissues has raised many questions about their nature, origin, function and their behavior in cell culture. Most of current experiments reporting a dynamics of cancer stem cell populations in culture show the eventual stability of the percentages of these cell populations in the whole population of cancer cells, independently of the starting conditions. In this paper we propose a mathematical model of cancer stem cell population behavior, based on specific features of cancer stem cell divisions and including, as a mathematical formalization of cell-cell communications, an underlying field concept. We compare the qualitative behavior of mathematical models of stem cells evolution, without and with an underlying signal. In absence of an underlying field, we propose a mathematical model described by a system of ordinary differential equations, while in presence of an underlying field it is described by a system of delay differential equations, by admitting a delayed signal originated by existing cells. Under realistic assumptions on the parameters, in both cases (ODE without underlying field, and DDE with underlying field) we show in particular the stability of percentages, provided that the delay is sufficiently small. Further, for the DDE case (in presence of an underlying field) we show the possible existence of, either damped or standing, oscillations in the cell populations, in agreement with some existing mathematical literature. The outcomes of the analysis may offer to experimentalists a tool for addressing the issue regarding the possible non-stem to stem cells transition, by determining conditions under which the stability of cancer stem cells population can be obtained only in the case in which such transition can occur. Further, the provided description of the variable corresponding to an underlying field may stimulate further experiments for elucidating the nature of “instructive" signals for cell divisions, underlying a proper pattern of the biological system.

How to cite

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Beretta, E., Capasso, V., and Morozova, N.. "Mathematical Modelling of Cancer Stem Cells Population Behavior." Mathematical Modelling of Natural Phenomena 7.1 (2012): 279-305. <http://eudml.org/doc/222434>.

@article{Beretta2012,
abstract = {Recent discovery of cancer stem cells in tumorigenic tissues has raised many questions about their nature, origin, function and their behavior in cell culture. Most of current experiments reporting a dynamics of cancer stem cell populations in culture show the eventual stability of the percentages of these cell populations in the whole population of cancer cells, independently of the starting conditions. In this paper we propose a mathematical model of cancer stem cell population behavior, based on specific features of cancer stem cell divisions and including, as a mathematical formalization of cell-cell communications, an underlying field concept. We compare the qualitative behavior of mathematical models of stem cells evolution, without and with an underlying signal. In absence of an underlying field, we propose a mathematical model described by a system of ordinary differential equations, while in presence of an underlying field it is described by a system of delay differential equations, by admitting a delayed signal originated by existing cells. Under realistic assumptions on the parameters, in both cases (ODE without underlying field, and DDE with underlying field) we show in particular the stability of percentages, provided that the delay is sufficiently small. Further, for the DDE case (in presence of an underlying field) we show the possible existence of, either damped or standing, oscillations in the cell populations, in agreement with some existing mathematical literature. The outcomes of the analysis may offer to experimentalists a tool for addressing the issue regarding the possible non-stem to stem cells transition, by determining conditions under which the stability of cancer stem cells population can be obtained only in the case in which such transition can occur. Further, the provided description of the variable corresponding to an underlying field may stimulate further experiments for elucidating the nature of “instructive" signals for cell divisions, underlying a proper pattern of the biological system.},
author = {Beretta, E., Capasso, V., Morozova, N.},
journal = {Mathematical Modelling of Natural Phenomena},
keywords = {cancer stem cells; delay differential equations; qualitative behavior; stability; oscillations},
language = {eng},
month = {1},
number = {1},
pages = {279-305},
publisher = {EDP Sciences},
title = {Mathematical Modelling of Cancer Stem Cells Population Behavior},
url = {http://eudml.org/doc/222434},
volume = {7},
year = {2012},
}

TY - JOUR
AU - Beretta, E.
AU - Capasso, V.
AU - Morozova, N.
TI - Mathematical Modelling of Cancer Stem Cells Population Behavior
JO - Mathematical Modelling of Natural Phenomena
DA - 2012/1//
PB - EDP Sciences
VL - 7
IS - 1
SP - 279
EP - 305
AB - Recent discovery of cancer stem cells in tumorigenic tissues has raised many questions about their nature, origin, function and their behavior in cell culture. Most of current experiments reporting a dynamics of cancer stem cell populations in culture show the eventual stability of the percentages of these cell populations in the whole population of cancer cells, independently of the starting conditions. In this paper we propose a mathematical model of cancer stem cell population behavior, based on specific features of cancer stem cell divisions and including, as a mathematical formalization of cell-cell communications, an underlying field concept. We compare the qualitative behavior of mathematical models of stem cells evolution, without and with an underlying signal. In absence of an underlying field, we propose a mathematical model described by a system of ordinary differential equations, while in presence of an underlying field it is described by a system of delay differential equations, by admitting a delayed signal originated by existing cells. Under realistic assumptions on the parameters, in both cases (ODE without underlying field, and DDE with underlying field) we show in particular the stability of percentages, provided that the delay is sufficiently small. Further, for the DDE case (in presence of an underlying field) we show the possible existence of, either damped or standing, oscillations in the cell populations, in agreement with some existing mathematical literature. The outcomes of the analysis may offer to experimentalists a tool for addressing the issue regarding the possible non-stem to stem cells transition, by determining conditions under which the stability of cancer stem cells population can be obtained only in the case in which such transition can occur. Further, the provided description of the variable corresponding to an underlying field may stimulate further experiments for elucidating the nature of “instructive" signals for cell divisions, underlying a proper pattern of the biological system.
LA - eng
KW - cancer stem cells; delay differential equations; qualitative behavior; stability; oscillations
UR - http://eudml.org/doc/222434
ER -

References

top
  1. M. Al-Hajj, M.S. Wicha, A. Benito-Hernandez, S.J. Morrison, M.F. Clarke. Prospective identification of tumorigenic breast cancer cells. Proc. Natl Acad. Sci. USA, 100 (2003), 3983–3988.  
  2. S. Bao, Q. Wu, R.E. McLendon, Y. Hao, Q. Shi, A.B. Hjelmeland, M.W. Dewhirst, D.D. Bigner, J.N. Rich. Glioma stem cells promote radioresistance by preferential activation of the DNA damage response. Nature, 444 (2006), 756–760.  
  3. B. Barrilleaux, D.G. Phinney, D.J. Prockop, K.C. O’Connor. Review : ex vivo engineering of living tissues with adult stem cells. Tissue Eng., 12 (2006), 3007–3019.  
  4. D. Bonnet, J.E. Dick. Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat. Med., 3 (1997), 730–737.  
  5. M.F. Clarke, J.E. Dick, P.B. Dirks, C.J. Eaves, C.H. Jamieson, D.L. Jones, J. Visvader, I.L. Weissman, G.M. Wahl. Cancer stem cells-Perspectives on current status and future directions : AACR workshop on cancer stem cells. Cancer Res., 66 (2006), 9339–9344.  
  6. M. Dean, T. Fojo, S. Bates. Tumour stem cells and drug resistance. Nat. Rev. Cancer, 5 (2005), 275–284.  
  7. M. Diehn, M.F. Clarke. Cancer stem cells and radiotherapy : new insights into tumor radioresistance. J. Natl. Cancer Inst., 98 (2006), 1755–1757.  
  8. G. Dontu, W.M. Abdallah, J.M. Foley, K.W. Jackson, M.F. Clarke, M.J. Kawamura, M.S. Wicha. In vitro propagation and transcriptionalprofiling of human mammary stem/progenitor cells. Genes Dev., 17 (2003), 1253–1270.  
  9. A. D’Onofrio, I.P.M. Tomlison. A nonlinear mathematical model of cell renewal, turnover and tumorigenesys in colon crypts. J. Theor. Biol., 244 (2007), 367–374.  
  10. C.E. Eyler, J.N. Rich. Survival of the fittest : cancer stem cells in therapeutic resistance and angiogenesis. J. Clin. Oncol., 26 (2008), 2839–2845.  
  11. H.I. Freedman, Y. Kuang. Stability switches in linear scalar neutral delay equations. Funkcial. Ekvac., 34 (1991), 187–209.  
  12. R.L. Gardner. Stem cells : potency, plasticity and public perception. J. Anat., 200 (2002), 277–282.  
  13. J.M. Gimble, A.J. Katz, B.A. Bunnell. Adipose-derived stem cells for regenerative medicine. Circ. Res., 100 (2007), 1249–1260.  
  14. C. Ginestier, M.S. Wicha. Mammary stem cell number as a determinate of breast cancer risk. Breast Cancer Res., 9 (2007), 109.  
  15. J. Guckenheimer, Ph. Holmes. Nonlinear oscillations, dynamical systems, and bifurcation of vector fields. Springer-Verlag, New York, 1983.  
  16. P.B. Gupta, T.T. Onder, G. Jiang, K. Tao, C. Kuperwasser, R.A. Weinberg, E.S. Lander. Identification of selective inhibitors of cancer stem cells by high-throughput screening. Cell, 138 (2009), 645–659.  
  17. M.D. Johnston, C.M. Edwards, W.F. Bodmer, P.K. Maini, S.J. Chapman. Mathematical modelling of cell population dynamics in the colonic crypt and in colorectal cancer. PNAS, 104 (2007), 4008–4013.  
  18. S.H. Lang, F. Frame, A. Collins, Prostate cancer stem cells. J. Pathol., 217 (2009), 299–306.  
  19. C. Li, D.G. Heidt, P. Dalerba, C.F. Burant, L. Zhang, V. Adsay, M. Wicha, M.F. Clarke, D.M. Simeone. Identification of pancreatic cancer stem cells. Cancer Res., 67 (2007), 1030–1037.  
  20. X. Li, M.T. Lewis, J. Huang, C. Gutierrez, C.K. Osborne, M.F. Wu, S.G. Hilsenbeck, A. Pavlick, X. Zhang, G.C. Chamness, et al.Intrinsic resistance of tumorigenic breast cancer cells to chemotherapy. J. Natl. Cancer Inst., 100 (2008), 672–679.  
  21. N.J. Maitland, A.T. Collins. Prostate cancer stem cells : a new target for therapy. J. Clin. Oncol., 26 (2008), 2862–2870.  
  22. S.A. Mani, W. Guo, M.J. Liao, E.N. Eaton, A. Ayyanan, A.Y. Zhou, M. Brooks, F. Reinhard, C.C. Zhang, M. Shipitsin, L.L. Campbell, K. Polyak, C. Brisken, J. Yang, R.A. Weinberg. The epithelial-mesenchymal transition generates cells with properties of stem cells. Cell, 133 (2008), 704–715.  
  23. F. Michor. Mathematical models of cancer stem cells. J. Clin. Oncol., 26 (2008), 2854–2861.  
  24. C.A. O’Brien, A. Pollett, S. Gallinger, J.E. Dick. A human colon cancer cell capable of initiating tumour growth in immunodeficient mice. Nature, 445 (2007), 106–110.  
  25. M.Z. Ratajczak, B. Machalinski, W. Wojakowski, J. Ratajczak, M. Kucia. A hypothesis for an embryonic origin of pluripotent Oct-4(+) stem cells in adult bone marrow and other tissues. Leukemia, 21 (2007), 860–867.  
  26. T. Reya, S.J. Morrison, M.F. Clarke, I.L. Weissman. Stem cells, cancer, and cancer stem cells. Nature, 414 (2001), 105–111.  
  27. L. Ricci-Vitiani, D.G. Lombardi, E. Pilozzi, M. Biffoni, M. Todaro, C. Peschle, R. De Maria. Identification and expansion of human colon-cancer-initiating cells. Nature, 445 (2007), 111–115.  
  28. I. Roeder, M. Herberg, M. Horn. An "Age" structured model of hemapoietic stem cell organization with application to chronic myeloid leukemia. Bull. Math. Biol., 71 (2009), 602–626.  
  29. S.K. Singh, I.D. Clarke, M. Terasaki, V.E. Bonn, C. Hawkins, J. Squire, P.B. Dirks. Identification of a cancer stem cell in human brain tumors. Cancer Res.63 (2003), 5821–5828.  
  30. H. Smith. An introduction to delay differential equations with applications to the life sciences. Springer, New York, 2010.  
  31. F. M. Watt, B. L. Hogan. Out of Eden : stem cells and their niches. Science, 287 (2000), 1427–1430 
  32. R.A. Weinberg. The biology of cancer. Garland Science, New York, 2007.  
  33. A. D. Whetton, G. J. Graham. Homing and mobilization in the stem cell niche. Trends Cell Biol., 9 (1999), 233–238 
  34. L. Wolpert. Positional information and the spatial pattern of cellular differentiation. J. Theor. Biol., 25 (1969), 1–47 
  35. W.A. Woodward, M.S. Chen, F. Behbod, M.P. Alfaro, T.A. Buchholz, J.M. Rosen. WNT/beta-catenin mediates radiation resistance of mouse mammary progenitor cells. Proc. Natl. Acad. Sci. USA104 (2007), 618–623.  
  36. V.P. Zhdanov. Effect of cell-cell communication on the kinetics of proliferation and differentiation of stem cells. Chemical Physics Letters, 437 (2007), 253–256.  
  37. S. Zhang, C. Balch, M.W. Chan, H.C. Lai, D. Matei, J.M. Schilder, P.S. Yan, T.H. Huang, K.P. Nephew. Identification and characterization of ovarian cancer-initiating cells from primary human tumors. Cancer Res., 68 (2008), 4311–4320.  

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