Tumor Immune System Interactions: The Kinetic Cellular Theory

  • Chapter
A Survey of Models for Tumor-Immune System Dynamics

Abstract

The growth of a tumor and its relationships with the host environment are complex events that kinetically mutate during tumor progression. Several aspects of these interactions and their dynamical evolution can be modeled through equations that take into account a few key variables related to microscopic interacting populations: tumor, host, immune cells, cytokine signals.

This paper provides a review of the state of the art on the so called kinetic (cellular) theory. The development of the modeling starts from observation of the phenomenological behavior of the system and, in particular, of the cell populations and their cellular interactions. This analysis is followed by derivation of the evolution equations in the framework of nonequilibrium statistical mechanics. The following step is the development of simulation and validation techniques, which has to be related to the experimental activity in the field. The final part of the survey provides a critical analysis of this type of methodological approach and of its conceivable developments, which may hopefully contribute to medical research addressed to the competition against tumor aggression.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
EUR 29.95
Price includes VAT (France)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
EUR 117.69
Price includes VAT (France)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
EUR 158.24
Price includes VAT (France)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info
Hardcover Book
EUR 158.24
Price includes VAT (France)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Abbas A.K., Lichtmann A.H., and Pober J.S., Cellular and Molecular Immunology, Saunders (1991).

    Google Scholar 

  2. Ackleh A.S., Fitzpatrick B.G., and Hallam T.G., Approximation and parameter estimation problems for algal aggregation models, Math. Models Meth. Appl. Sci., 4 (1994), 291–312.

    Article  MathSciNet  MATH  Google Scholar 

  3. Adam J.A., A simplified mathematical model of tumor growth, Math. Biosci., 81 (1986), 229–244.

    Article  MATH  Google Scholar 

  4. Adam J.A., A mathematical model of tumor growth II: Effects of geometry and spatial nonuniformity on stability, Math. Biosci., 86 (1987), 183–211.

    Article  MATH  Google Scholar 

  5. Adam J.A., A mathematical model of tumor growth III: Comparison with experiment, Math. Biosci., 86 (1987), 213–227.

    Article  MATH  Google Scholar 

  6. Adam J.A., Diffusion models of prevascular and vascular tumor growth-A review, in Mathematical Population Dynamics, Arino O. et al. eds., Dekker (1991).

    Google Scholar 

  7. Adam J.A. and Noren R., Equilibrium model of a vascularized spherical carcinoma with central necrosis-Some properties of the solution, J. Math. Biol, 81 (1993), 735–745.

    Article  MathSciNet  Google Scholar 

  8. Adam J.A., Effects of vascularization on lymphocyte/tumor cell dynamics: Qualitative features, Math. Comp. Modelling-Special Issue on Modelling and Simulation Problems on Tumor-immune System Dynamics, Bellomo N. ed., 23 (1996), 1–10.

    Google Scholar 

  9. Albert A., Freedman M., and Perelson A.S., Tumors and the immune system: The effects of a tumor growth modulator, Math. Biosci., 50 (1980), 25–58.

    Article  MathSciNet  MATH  Google Scholar 

  10. Allione A., Consalvo M., Nanni P., Lollini P.L., Cavallo F., Gio-varelli M., Forni M., Gulino A., Colombo M.P., Dellabona P., Hock H., Blanckstain T., Rosenthal F., Gansbacher B., Colombo M.C., Musso T., Gusella L., and Forni G., Immunizing and curative potential of replicating and nonreplicating murine mammary adenocarcinoma cells engineered with IL2, IL4, IL6, IL7, IL10, TNFα, GM-CSF and IFNγ gene or admixed with conventional adjuvants, Cancer Res., 54 (1994), 6022–6026.

    Google Scholar 

  11. Arlotti L. and Bellomo N., On a new model of population dynamics with stochastic interaction, Transp. Theory Statist. Phys., 24 (1995), 431–443.

    Article  MathSciNet  MATH  Google Scholar 

  12. Arlotti L. and Lachowicz M., Qualitative analysis of a nonlinear integro-differential equation modelling tumor-host dynamics, Math. Comp. Modelling-Special Issue on Modelling and Simulation Problems on Tumor-immune System Dynamics, Bellomo N. ed., 23 (1996), 11–30.

    Google Scholar 

  13. Arlotti L. and Bellomo N., On the Cauchy problem for a nonlinear integral differential equation in population dynamics, Appl. Math. Letters, 9 (1996), 65–70.

    Article  MathSciNet  MATH  Google Scholar 

  14. Ash R. and Gardner M., Topics in Stochastic Processes, Academic Press (1975).

    Google Scholar 

  15. Bellomo N. and Forni G., Dynamics of tumor interaction with the host immune system, Math. Comp. Modelling, 20 (1994), 107–122.

    Article  MATH  Google Scholar 

  16. Bellomo N. and Preziosi L., Modelling, Mathematical Methods and Scientific Computation, CRC Press (1995).

    Google Scholar 

  17. Bellomo N. ed., Modelling and Simulation Problems on Tumor Immune System Dynamics, Special Issue Math. Comp. Modelling, 23 (1996).

    Google Scholar 

  18. Bellomo N. ed., Lecture Notes on the Mathematical Theory of the Boltzmann Equation, World Sci. (1995).

    Google Scholar 

  19. Beltrami E., Mathematics for Dynamic Modelling, Academic Press (1987).

    Google Scholar 

  20. Boon T., Gajewski T., and Coulie G., From defined human tumor antigens to effective immunization, Immunol. Today, 16 (1955), 334–335.

    Article  Google Scholar 

  21. Bosco M., Giovarelli M., Forni M., Scarpa S., Masuelli L., and Forni G., Low doses of IL-4 injected perilymphatically in tumor-bearing mice inhibit the growth of poorly and apparently nonimmunogenic tumors and induce a tumor specific immune memory, J. Immunol, 145 (1990), 3136–3143.

    Google Scholar 

  22. Cavallo F., Giovarelli M., Gulino A., Vacca A., Stoppacciaro A., Modesti A., and Forni G., Role of Neutrophils and CD4+T lymphocytes in the primary and memory response to nonimmunogenic mammary adenocarcinoma made immunogenic by IL-2 gene trans-fection, J. Immunol, 149 (1992), 3627–3635.

    Google Scholar 

  23. Chaplain M. and Stuart A.M., A model mechanism for the chemo-tactic response of endothelial cells to tumor angiogenesis factor, IMA J. Math. Appl Med. Biol., 8 (1991), 191–220.

    Article  MATH  Google Scholar 

  24. Chaplain M. and Britton N.F., On the concentration profile of a growth inhibitory factor in multicell spheroids, Math. Biosci., 115 (1993), 233–245.

    Article  MATH  Google Scholar 

  25. Chaplain M. and Sleeman B.D., Modelling the growth of solid tumors and incorporating a method for their classification using nonlinear elasticity theory, J. Math. Biol, 31 (1993), 431–479.

    Article  MathSciNet  MATH  Google Scholar 

  26. Chaplain M., Benson D.L., and Maini P.K., Nonlinear diffusion of a growth inhibitory factor in multicell spheroids, Math. Bioscl, 121 (1994), 1–13.

    Article  MATH  Google Scholar 

  27. Chaplain M., A vascular growth, angiogenesis, and vascular growth in solid tumors: The mathematical modelling of stages of tumor developments, Math. Comp. Modelling-Special Issue on Modelling and Simulation Problems on Tumor-immune System Dynamics, Bellomo N. ed., 23 (1996), 47–88.

    Google Scholar 

  28. De Boer R.J. and Högeweg P., Tumor escape from immune elimination: Simplified precursor bound cytotoxicity models, J. Theor. Biol., 113 (1985), 719–736.

    Article  Google Scholar 

  29. De Boer R.J. and Högeweg P., Interactions between macrophages and T-lymphocytes, J. Theor. Biol., 120 (1986), 331–354.

    Article  Google Scholar 

  30. Den Otter W. and Ruitenberg E.J. eds., Tumor Immunology. Mechanisms, Diagnosis, Therapy, Elsevier (1987).

    Google Scholar 

  31. Folkman J. and Klagsbrun M., Angiogenic factors, Science, 235 (1987), 442–447.

    Article  Google Scholar 

  32. Forni G. and Comoglio P.M., Growth of syngenetic tumors in unim-munized newborn and adult hosts, Brit. J. Cancer, 27 (1973), 120–127.

    Article  Google Scholar 

  33. Forni G., Giovarelli M., Santoni A., Modesti A., and Forni M., Interleukin-2 activated tumor inhibition in vivo depends on the systemic involvement of host immunoreactivity, J. Immunol., 138 (1987), 4031–4033.

    Google Scholar 

  34. Forni G., Varesio L., Giovarelli M., and Cavallo G., Dynamic state of a spontaneous immune reactivity towards a mammary adenocarcinoma, in Tumor Associate Antigens and Their Specific Immune Response, Spreafico F. and Arnon R. eds., Academic Press (1979), 167–192.

    Google Scholar 

  35. Forni G., Foa R., Santoni A., and Frati L. eds., Cytokine Induced Tumor Immunogeneticity, Academic Press (1994).

    Google Scholar 

  36. Green I., Cohen S., and McCluskey R. eds., Mechanisms of Tumor Immunity, Wiley (1977).

    Google Scholar 

  37. Grossman Z. and Berke G., Tumor escape from immune elimination, J. Theor. Biol, 83 (1980), 276–296.

    Article  Google Scholar 

  38. Greenspan H., On the growth and stability of cell cultures and solid tumors, J. Theor. Biol, 56 (1976), 229–242.

    Article  MathSciNet  Google Scholar 

  39. Gyllenberg M. and Webb G., A nonlinear structured population model of tumor growth with quiescence, J. Math. Biol, 28 (1990), 671–694.

    Article  MathSciNet  MATH  Google Scholar 

  40. Herberman R.B., NK Cells and Other Natural Effector Cells, Academic Press (1982).

    Google Scholar 

  41. Iversen O., What’s new in endogenous growth stimulators and inhibitors (chalones), Path. Res. Pract., 180 (1985), 77–80.

    Article  Google Scholar 

  42. Iversen O., The hunt for endogenous growth-inhibitory and tumor suppression factors-Their role in physiological and pathological growth-regulation, Adv. Cancer Res., 57 (1991), 413–453.

    Article  Google Scholar 

  43. Jager E. and Segel L., On the distribution of dominance in a population of interacting anonymous organisms, SIAM J. Appl. Math., 52 (1992), 1442–1468.

    Article  MathSciNet  Google Scholar 

  44. Janeway C.A. and Travers P., Immunobiology, Current Biology (1994).

    Google Scholar 

  45. Kuznetsov V.A., Dynamics of Immune Processes During Tumor Growth, Nauka (1992), in Russian.

    Google Scholar 

  46. Kuznetsov V.A., Malakin A.M., Taylor M.A., and Perelson A.S., Nonlinear dynamics of immunogenic tumors: Parameter estimation and global bifurcation analysis, Bull. Math. Biol., 56 (1994), 295–321.

    MATH  Google Scholar 

  47. Landry J., Freyer J.P., and Sutherland R.M., A model for the growth of multicell spheroids, Cell Tissue Kinet., 15 (1982), 585–594.

    Google Scholar 

  48. Levin S., Frontiers in Mathematical Biology, Springer (1994).

    Google Scholar 

  49. Lefever R.J., Hiernaux J., Urbain J., and Meyers P., On the kinetics and optimal specificity of cytotoxic reactions mediated by T-lymphocytes clones, Bull. Math. Biol., 54 (1992), 839–873.

    MATH  Google Scholar 

  50. Lin C.C. and Segel L.A., Mathematics Applied to Deterministic Problems in Applied Sciences, SIAM Publ. (1988).

    Google Scholar 

  51. Lollini P., Bosco M., Cavallo F., De Giovanni C., Giovarelli M., Landuzzi L., Musiani P., Modesti A., Nicoletti G., Palmieri G., Santoni A., Young H., Forni G., and Nanni P., Inhibition of tumor growth and enhancement of metastasis after transfection of the γ-Interferon gene, Int. J. Cancer, 55 (1993), 320–329.

    Article  Google Scholar 

  52. Lo Schiavo M., Discrete kinetic cellular models of tumors immune system interactions, Math. Models Meth. Appl. Sci., 6 (1996), to appear.

    Google Scholar 

  53. Maggelakis S. and Adam J.A., Mathematical model for prevascu-lar growth of a spherical carcinoma, Math. Comp. Modelling, 13 (1990), 23–38.

    Article  MATH  Google Scholar 

  54. Maggelakis S., Type α and type ß transforming growth factors as regulators of cancer cellular growth: A mathematical model, Math. Comp. Modelling, 18 (1993), 9–16.

    Article  MATH  Google Scholar 

  55. Mueller-Klieser W., Multicellular spheroids: A review on cellular aggregates in cancer research, J. Cancer Res. Clin. Oncol., 113 (1987), 101–122.

    Article  Google Scholar 

  56. Michelson S. and Leith J., Growth factors and growth control of heterogeneous cell populations, Bull. Math. Biol., 55 (1993), 993–1011.

    MATH  Google Scholar 

  57. Michelson S. and Leith J., Autocrine and paracrine growth factors in tumor growth: A mathematical model, Bull. Math. Biol., 53 (1991), 639–656.

    Google Scholar 

  58. Markovitch S., The particular role of cell loss in tumor growth, Math. Comp. Modelling, 18 (1993), 83–89.

    Article  MathSciNet  MATH  Google Scholar 

  59. Mule J., Shu S., Schwarz S., and Rosenberg S., Successful adoptive immunotherapy of established pulmonary metastases with LAK cells and recombinant IL-2, Science, 255 (1993), 1487–1489.

    Google Scholar 

  60. Marusic M., Bajzer Z., Freyer J.P., and Vuk-Pavlovic S., Modelling autostimulation of growth in multicellular tumor spheroids, Int. J. Biomed. Comp., 149 (1991), 149–158.

    Article  Google Scholar 

  61. Marusic M. and Vuk-Pavlovic S., Prediction power of mathematical models for tumor growth, J. Biological Systems, 1 (1993), 69–78.

    Article  Google Scholar 

  62. Marusic M., Bajzer Z., Freyer J.P., and Vuk-Pavlovic S., Tumor growth in vivo and as multicellular spheroids compared by mathematical models, Bull. Math. Biol., 56 (1994), 617–631.

    MATH  Google Scholar 

  63. Murray J., Mathematical Biology, Springer (1994).

    Google Scholar 

  64. Nanni P., De Giovanni C., Lollini P., Nicoletti G., and Prodi G., TS/A: A new metastasiging cell line originated from a BALB/c spontaneous mammary adenocarcinoma, Clin. Exp. Med., 1 (1983), 373–380.

    Article  Google Scholar 

  65. Nossal G.J.V., Life, death and the immune system, Scientific American, 269 (1993), 53–72.

    Article  Google Scholar 

  66. Perelson A.S. and Bell G.I., Delivery of lethal hits by cytotoxic ? lymphocytes in multicellular conjugates occurs sequentially but randomly, J. Immunol, 129 (1982), 2796–2801.

    Google Scholar 

  67. Perelson A.S. and MacKean C.A., Kinetics of cell-mediated cytotoxicity: Stochastic and deterministic multistage models, J. Math. Biol, 170 (1984), 161–194.

    Google Scholar 

  68. Perelson A.S. ed., Theoretical Immunology, Addison-Wesley (1988).

    Google Scholar 

  69. Prehn R.T, Stimulatory effects of immune reactions upon the growth of transplanted tumors, Cancer Res., 55 (1994), 908–914.

    Google Scholar 

  70. Preziosi L., From population dynamics to the competition between tumors and immune system, Math. Comp. Modelling-Special Issue on Modelling and Simulation Problems on Tumor-immune System Dynamics, Bellomo N. ed., 23 (1996), 135–152.

    Google Scholar 

  71. Rosenberg S., Lotze M., Yang J., Aebersold P., Linehan W., Seipp C., and White D., Experience with the use of high-dose interleukin-2 in the treatment of 652 cancer patients, Ann. Surg., 210 (1989), 474–484.

    Article  Google Scholar 

  72. Segel L., Modelling Dynamic Phenomena in Molecular and Cellular Biology, Cambridge University Press (1984).

    Google Scholar 

  73. Segel L. and Perelson A.S., Computations in phase space. A new approach to immune network theory, in Theoretical Immunology II, Addison-Wesley (1988), 321–342.

    Google Scholar 

  74. Steel G.G., Growth Kinetics of Tumors, Clarendon (1977).

    Google Scholar 

  75. Smoluchowski M.V., Versuch einer mathematischen theorie der ko-agulationskinetik, Z. Phys. Chem., 92 (1917), 129–168.

    Google Scholar 

  76. Stewart I.W., Global existence theorem for the general coagulation fragmentation equation with unbounded kernels, Math. Meth. Appl. Sci., 11 (1989), 627–648.

    Article  MATH  Google Scholar 

  77. Stewart I.W., On the coagulation-fragmentation equation, J. Appl. Math. Phys., 41 (1990), 746–756.

    Google Scholar 

  78. Stewart I.W., Density conservation for a coagulation equation, J. Appl. Math. Phys., 42 (1991), 746–756.

    Article  MATH  Google Scholar 

  79. Sutherland R.M. and Durand R.E., Growth and cellular characteristics of multicell spheroids, Recent Results in Cancer Research, 95 (1984), 24–49.

    Article  Google Scholar 

  80. Sutherland R.M., Cell and environment interactions in tumor mi-croregions: The multicell spheroid model, Science, 240 (1988), 177–184.

    Article  Google Scholar 

  81. Swan G.W., The diffusion of an inhibitor in a spherical tumor, Math. Biosci., 108 (1992), 75–79.

    Article  Google Scholar 

  82. Taubes G., Do immunologists dream of electric mice?, Science, 265 (1994), 886–888.

    Article  Google Scholar 

  83. Tomlison I.P. and Bodmer W.F., Failure of programmed cell death and differentiation as causes of tumors: Some simple mathematical models, Proc. Natl. Acad. Sci. USA, 92 (1995), 11130–11134.

    Article  Google Scholar 

  84. Truesdell C. and Muncaster R., Fundamentals of Maxwell Kinetic Theory of a Simple Monoatomic Gas, Academic Press (1980).

    Google Scholar 

  85. Yakovlev A.Yu., Tsodikov A., and Asselain B., Stochastic Models of Tumor Latency and their Applications, World Sci. (1995).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer Science+Business Media New York

About this chapter

Cite this chapter

Bellomo, N., Preziosi, L., Forni, G. (1997). Tumor Immune System Interactions: The Kinetic Cellular Theory. In: Adam, J.A., Bellomo, N. (eds) A Survey of Models for Tumor-Immune System Dynamics. Modeling and Simulation in Science, Engineering, & Technology. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-0-8176-8119-7_4

Download citation

  • DOI: https://doi.org/10.1007/978-0-8176-8119-7_4

  • Publisher Name: Birkhäuser, Boston, MA

  • Print ISBN: 978-1-4612-6408-8

  • Online ISBN: 978-0-8176-8119-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Navigation