Advertisement

Structural Adaptation in Normal and Cancerous Vasculature

  • Philip K. Maini
  • Tomás Alarcón
  • Helen M. Byrne
  • Markus R. Owen
  • James Murphy

Abstract

The dynamics of cancerous tissue growth involves the complex interaction of a number of phenomena interacting over a range of temporal and spatial scales. While several processes involved have been studied, the adaptation of the vasculature within a growing tumour has thus far received little attention. We consider a hybrid cellular automaton model which analyses the interaction between the tumour vascular network and tissue growth. We compute the temporal behaviour of the cancerous cell population under different hypotheses of structural adaptation in the vasculature. This may provide a possible method of determining experimentally which adaptation mechanisms are at work.

Keywords

Wall Shear Stress Tumour Vasculature Adaptation Mechanism Structural Adaptation Hypoxic Region 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    T. Alarcón, H.M. Byrne, P.K. Maini. A cellular automaton model for tumour growth in a heterogeneous environment. J. theor. Biol. 225, 257–274 (2003).CrossRefGoogle Scholar
  2. 2.
    T. Alarcón, H.M. Byrne, P.K. Maini. A multiple scale model for tumour growth. SIAM Multiscale Model. Simul. 3, 440–475 (2005).zbMATHCrossRefGoogle Scholar
  3. 3.
    T. Alarcón, H.M. Byrne, P.K. Maini. A design principle for vascular beds: The effects of complex blood rheology. Microvasc. Res. 69, 156–172 (2005).CrossRefGoogle Scholar
  4. 4.
    D.M. Collins, W.T. McCullough, M.L. Ellsworth. Conducted vascular responses: Communication across the capillary bed. Microvasc. Res. 56, 43–53 (1998).CrossRefGoogle Scholar
  5. 5.
    A. Deutsch, S. Dormann. Modeling of avascular tumor growth with a hybrid cellular automaton. In Silico Biol. 2, 1–14 (2002).Google Scholar
  6. 6.
    P.J. Hunter, P. Robbins, D. Noble. The IUPS human physiome project. Pflügers Archiv- Eur. J. Physiol. 445, 1–9 (2002).CrossRefGoogle Scholar
  7. 7.
    M. LaBarbera. Principles of design of fluid transport systems in zoology. Science. 249, 992–1000 (1990).CrossRefGoogle Scholar
  8. 8.
    C.D. Murray. The physiological principle of minimom work I The vascular system and the cost of blood volume. Proc. Nat. Acad. Sci. USA. 12, 207 (1977).CrossRefGoogle Scholar
  9. 9.
    A.A. Patel, E.T. Gawlinski, S.K. Lemieux, R.A. Gatenby. A cellular automaton model of early tumor growth and invasion: The effects of native tissue vascularity and increased anaerobic tumor metabolism. J. theor. Biol. 213, 315–331 (2001).CrossRefGoogle Scholar
  10. 10.
    A.R. Pries, T.W. Secomb, P. Gaehtgens. Design principles of vascular beds. Circ. Res. 77, 1017–1023 (1995).Google Scholar
  11. 11.
    A.R. Pries, T.W. Secomb, P. Gaehtgens. Structural adaptation and stability of microvascular networks: theory and simulations. Am. J. Physiol. 275, H349–H360 (1998).Google Scholar
  12. 12.
    A.R. Pries, B. Reglin, T.W. Secomb. Structural adaptation of microvascular networks: functional response to adaptive responses. Am. J. Physiol. 281, H1015–H1025 (2001).Google Scholar
  13. 13.
    N. Resnick, H. Yahav, A. Shay-Salit, M. Shushy, S. Schubert, L.C.M. Zilberman, E. Wofovitz. Fluid shear stress and the vascular endothelium: for better and for worse. Progress Biophys. Mol. Biol. 81, 177–199 (2003).CrossRefGoogle Scholar
  14. 14.
    G.D. Yancopoulos, S. Davis, N.W. Gale, J.S. Rudge, S.J. Wiegand, J. Holash. Vascular-specific growth factors and blood vessel formation. Nature. 407, 242–248 (2000).CrossRefGoogle Scholar
  15. 15.
    M. Zamir. Shear forces and blood vessel radii in vardiovascular-system. J. Gen. Physiol. 69, 449–461 (1977).CrossRefGoogle Scholar

Copyright information

© Springer 2007

Authors and Affiliations

  • Philip K. Maini
    • 1
  • Tomás Alarcón
    • 2
  • Helen M. Byrne
    • 3
  • Markus R. Owen
    • 3
  • James Murphy
    • 3
  1. 1.Centre for Mathematical Biology, Mathematical InstituteUniversity of OxfordOxfordUK
  2. 2.Bioinformatics Unit, Department of Computer ScienceUniversity College LondonLondonUK
  3. 3.Centre for Mathematical Medicine, School of Mathematical SciencesUniversity of NottinghamNottinghamUK

Personalised recommendations