Mathematical Biosciences and Engineering, 2013, 10(1): 167-184. doi: 10.3934/mbe.2013.10.167.

Primary: 92C42, 92C45, 92E20; Secondary: 65L99.

Export file:

Format

  • RIS(for EndNote,Reference Manager,ProCite)
  • BibTex
  • Text

Content

  • Citation Only
  • Citation and Abstract

A structural model of the VEGF signalling pathway: Emergence of robustness and redundancy properties

1. INRIA, Project-team NUMED, Ecole Normale Supérieure de Lyon, 46 allée d'Italie, 69007 Lyon Cedex 07

The vascular endothelial growth factor (VEGF) is known as one of the main promoter of angiogenesis - the process of blood vessel formation. Angiogenesis has been recognized as a key stage for cancer development and metastasis. In this paper, we propose a structural model of the main molecular pathways involved in the endothelial cells response to VEGF stimuli. The model, built on qualitative information from knowledge databases, is composed of 38 ordinary differential equations with 78 parameters and focuses on the signalling driving endothelial cell proliferation, migration and resistance to apoptosis. Following a VEGF stimulus, the model predicts an increase of proliferation and migration capability, and a decrease in the apoptosis activity. Model simulations and sensitivity analysis highlight the emergence of robustness and redundancy properties of the pathway. If further calibrated and validated, this model could serve as tool to analyse and formulate new hypothesis on th e VEGF signalling cascade and its role in cancer development and treatment.
  Figure/Table
  Supplementary
  Article Metrics

Keywords Vascular Endothelial Growth Factor (VEGF) signalling.; networks; molecular reactions; ordinary differential equations; kinetics in biochemical problems; Systems biology

Citation: Floriane Lignet, Vincent Calvez, Emmanuel Grenier, Benjamin Ribba. A structural model of the VEGF signalling pathway: Emergence of robustness and redundancy properties. Mathematical Biosciences and Engineering, 2013, 10(1): 167-184. doi: 10.3934/mbe.2013.10.167

References

  • 1. Multiscale Modeling and Simulation, 3 (2005), 440-475.
  • 2. Journal of The Royal Society Interface, 4 (2007), 283-304.
  • 3. Nature Cell Biology, 8 (2006), 1195-1203.
  • 4. Nature Biotechnology, 24 (2006), 667-672.
  • 5. Bulletin of Mathematical Biology, 60 (1998), 857-899.
  • 6. Bulletin of Mathematical Biology, 66 (2004) 1039-1091.
  • 7. Science, 283 (1999), 381-387.
  • 8. Journal of Theoretical Biology, 241 (2006), 903-918.
  • 9. Journal of Theoretical Biology, 260 (2009), 545-562.
  • 10. Progress in Biophysics and Molecular Biology, 97 (2008), 28-39.
  • 11. Mathematical Biosciences, 130 (1995), 151-181.
  • 12. Nature, 407 (2000), 249-257.
  • 13. Cellular and Molecular Life Sciences, 63 (2006), 601-615.
  • 14. Nature Reviews Molecular Cell Biology, 7 (2006), 505-516.
  • 15. Trends in Biochemical Sciences, 28 (2003), 488-494.
  • 16. Oncogene, 30 (2010), 1631-1642.
  • 17. Nature Reviews Drug Discovery, 6 (2007), 734-745.
  • 18. Nature Reviews Cancer, 2 (2002), 795-803.
  • 19. Endocrine Reviews, 25 (2004), 581-611.
  • 20. Biochemical and Biophysical Research Communications, 333 (2005), 326-335.
  • 21. Cancer Research, 34 (1974), 2109.
  • 22. European Journal of Cancer (Oxford, England: 1990), 32 (1996), 2534.
  • 23. Microcirculation, 15 (2008), 715-738.
  • 24. Journal of Clinical Oncology, 23 (2005), 1295-1311.
  • 25. Journal of Biological Chemistry, 273 (1998), 30336-30343.
  • 26. Physical Review Letters, 69 (1992), 2013-2016.
  • 27. Biochemical Journal, 373 (2003), 451-463.
  • 28. Biotechnology Progress, 24 (2008), 96-109.
  • 29. Proceedings of the National Academy of Sciences, 93 (1996), 10078-10083.
  • 30. Journal of Cell Science, 117 (2004), 4619-4628.
  • 31. Nature Medicine, 7 (2001), 987-989.
  • 32. Science, 307 (2005), 58-62.
  • 33. Nature, 420 (2002), 206-210.
  • 34. Nature, 426 (2003), 125-125.
  • 35. Nature Biotechnology, 23 (2005), 961-966.
  • 36. Physics in Medicine and Biology, 52 (2007), 3665-3677.
  • 37. Journal of Biological Chemistry, 274 (1999), 30169-30181.
  • 38. European Journal of Biochemistry, 267 (2001), 1583-1588.
  • 39. Circulation Research, 100 (2007), 782-794.
  • 40. Physical Review Letters, 96 (2006), 58104.
  • 41. Molecular Cancer Therapeutics, 7 (2008), 3670-3684.
  • 42. Journal of Mathematical Biology, 49 (2004), 111-187.
  • 43. Clinical Cancer Research, 9 (2003), 327-337.
  • 44. Blood (2012), 5599-5607.
  • 45. Endocrine-related cancer, 16 (2009), 675-702.
  • 46. Nature Biotechnology, 23 (2005), 1509-1515.
  • 47. Nat. Rev. Mol. Cell. Biol., 7 (2006), 357-371.
  • 48. International Journal of Radiation Oncology, Biology, Physics, 59 (2004), 928-942.
  • 49. Experimental Eye Research, 83 (2006), 1005-1016.
  • 50. Journal of Theoretical Biology, 243 (2006), 532-541.
  • 51. IET Systems Biology, 3 (2009), 180-190.
  • 52. Theoretical Biology and Medical Modelling, 3 (2006).
  • 53. Expert review of anticancer therapy, 6 (2006), 1361-1376.
  • 54. Nature biotechnology, 20 (2002), 370-375.
  • 55. Progress in Biophysics and Molecular Biology, 106 (2011), 450-462.
  • 56. The Oncologist, 12 (2007), 465-477.
  • 57. Journal of biochemistry and molecular biology, 39 (2006), 469-478.
  • 58. Experimental cell research, 312 (2006), 549-560.
  • 59. Cancer Research, 64 (2004), 1094-1101.
  • 60. Clinical Science, 109 (2005), 227-241.
  • 61. Cancer research, 64 (2004), 3731-3736.
  • 62. Cancer Research, 35 (1975), 2619-2630.
  • 63. Nature Reviews. Cancer, 2 (2002), 489-501.
  • 64. Theoretical Biology and Medical Modelling, 4 (2007), 50.
  • 65. Frontiers in Computational Physiology And Medicine, 2 (2011) .
  • 66. Journal of Theoretical Biology, 250 (2008), 257-280.
  • 67. Nature medicine, 10 (2004), 145-147.
  • 68. Cancer Cell, 6 (2004), 553-563.
  • 69. Bulletin of mathematical biology, 67 (2005), 211-259.

 

This article has been cited by

  • 1. Andrea Weiss, Xianting Ding, Judy R. van Beijnum, Ieong Wong, Tse J. Wong, Robert H. Berndsen, Olivier Dormond, Marchien Dallinga, Li Shen, Reinier O. Schlingemann, Roberto Pili, Chih-Ming Ho, Paul J. Dyson, Hubert van den Bergh, Arjan W. Griffioen, Patrycja Nowak-Sliwinska, Rapid optimization of drug combinations for the optimal angiostatic treatment of cancer, Angiogenesis, 2015, 18, 3, 233, 10.1007/s10456-015-9462-9
  • 2. P. Guerrero, T. Alarcón, A. Stephanou, V. Volpert, Stochastic Multiscale Models of Cell Population Dynamics: Asymptotic and Numerical Methods, Mathematical Modelling of Natural Phenomena, 2015, 10, 1, 64, 10.1051/mmnp/201510104

Reader Comments

your name: *   your email: *  

Copyright Info: 2013, , licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

Download full text in PDF

Export Citation

Copyright © AIMS Press All Rights Reserved