Skip to main content

Advertisement

SpringerLink
Log in

Using evolvable genetic cellular automata to model breast cancer

  • Original Paper
  • Published:
Genetic Programming and Evolvable Machines Aims and scope Submit manuscript

Abstract

Cancer is an evolutionary process. Mutated cells undergo selection for abnormal growth and survival creating a tumor. We model this process with cellular automata that use a simplified genetic regulatory network simulation to control cell behavior and predict cancer etiology. Our genetic model gives us the ability to relate genetic mutation to cancerous outcomes. The simulation uses known histological morphology, cell types, and stochastic behavior to specifically model ductal carcinoma in situ (DCIS), a common form of non-invasive breast cancer. Using this model we examine the effects of hereditary predisposition on DCIS incidence and aggressiveness. Results show that we are able to reproduce in vivo pathological features to hereditary forms of breast cancer: earlier incidence and increased aggressiveness. We also show that a contributing factor to the different pathology of hereditary breast cancer results from the ability of progenitor cells to pass cancerous mutations on to offspring.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Alarcon, T., Byrne, H.M., Maini, P.K.: A cellular automaton model for tumour growth in inhomogeneous environment. J. Theor. Biol. 225, 257–274 (2003)

    Article  MathSciNet  Google Scholar 

  2. Bankhead, A. III, Magnuson, N.S., Heckendorn, R.B.: Modeling multicellular and tumorous existence with genetic cellular automata. In: Pollack, J., Bedau, M.A., Husbands, P., Ikegami, T., Watson, R.A. (eds.) Artificial Life IX, pp. 220–225. MIT Press (2004)

  3. Bankhead, A. III, Magnuson, N.S., Heckendorn, R.B.: Cellular automaton simulation examining progenitor hierarchy structure effects on mammary ductal carcinoma. J. Theor. Biol. 246(3), 491–498 (2007)

    Article  Google Scholar 

  4. Beckmann, M.W., Niederacher, D., Schnurch, H.-G., Gusterson, B.A, Bender, H.G.: Multistep carcinogenesis of breast cancer and tumour heterogeneity. J. Mol.Med. 75, 429–439 (1997)

    Article  Google Scholar 

  5. Birnbaum, D., Bertucci, F., Ginestier, C., Tagett, R., Jacquemier, J., Charafe-Jauffret, E.: Basal and luminal breast cancers: basic or luminous. Int. J. Oncol. 25, 249–258 (2004)

    Google Scholar 

  6. Byrne, H.M., Chaplain, M.A.J.: Growth of nonnecrotic tumours in the presence and absence of inhibitors. Math. Biosci. 14, 151–181 (1995)

    Article  Google Scholar 

  7. Cao, Y., Paner, G.P., Kahn, L.B., Rajan, P.B.: Noninvasive carcinoma of the breast. Arch. Pathol. Lab. Med. 128, 893–896 (2004)

    Google Scholar 

  8. Coppock, H.A., Clarke, R.B.: Mammary stem cells: the root of breast cancer? Breast Cancer Online 7(9), 4 pp (2004)

    Google Scholar 

  9. van Diest, P.J., Baak, J.P.A., van der Wall, E.: Prognostic value of proliferation in invasive breast cancer: a review. J. Clin. Pathol. 57(7):675–681 (2004)

    Article  Google Scholar 

  10. Eerola, H., Keikkila, P., Tamminen, A., Aittomaki, K., Blomqvist, C., Nevanlinna, H.: Histopathological features of breast tumours in brca1, brca2 and mutation-negative breast cancer families. Breast Cancer Res. 7, R93–R100 (2005)

    Article  Google Scholar 

  11. Erbas, B., Provenzano, E., Armes, J., Gertig, D.: The natural history of ductal carcinoma in situ of the breast: a review. Breast Cancer Res. Treat. 97, 135–144 (2006)

    Article  Google Scholar 

  12. Evan, G.I., Vousden, K.H.: Proliferation, cell cycle and apoptosis in cancer. Nature 411, 342–348 (2001)

    Article  Google Scholar 

  13. Fairbanks, D.J., Andersen, R.W.: Genetics: The Continuity of Life. Brooks/Cole Publishing Company (1999)

  14. Frank, S.A., Nowak, M.A.: Problems of somatic mutation and cancer. BioEssays: Adv. Mol. Cell. Devel. Biol. 26, 291–299 (2004)

    Google Scholar 

  15. Franks, S.J., Byrne, H.M., Lewis, C.E., Underwood, J.C.E.: Biological inferences from a mathematical model of comedo ductal carcinoma in situ of the breast. J. Theor. Biol. 232, 523–543 (2005)

    Article  MathSciNet  Google Scholar 

  16. Gwen, D.C.: Nonlactating mammary gland. online http://microanatomy.net/ 1998. with permission of author.

  17. Kansal, A.R., Torquoato, S., Harsh, G.R. IV, Chiocca, E.A., Deisboeck, T.S.: Simulated brain tumor growth dynamics using a three-dimensional cellular automaton. J. Theor. Biol. 203, 367–382 (2000)

    Article  Google Scholar 

  18. Knudson, A.G. Jr.: Mutation and cancer: statistical study of retinoblastoma. Proc. Natl. Acad. Sci. 68, 820–823 (1971)

    Article  Google Scholar 

  19. Leonard, G.D., Swain, S.M.: Ductal carcinoma in situ, complexities and challenges. J. Natl. Cancer Inst. 96(12), 906–920 (2004)

    Article  Google Scholar 

  20. Louwman, W.J., van Beek, M.W.P.M., Schapers, R.F.M., Tutein Nolthenius-Puylaert, M.B.C.J.E, van Diest, P.J., Roumen, R.M., Coebergh, J.W.W. (2006) Long-term survival of t1 and t2 lymph node-negative breast cancer patients according to mitotic activity index: a population-based study. Int. J. Cancer 118, 2310–2314.

    Article  Google Scholar 

  21. Lux, M.P., Fasching, P.A., Beckmann, M.W.: Hereditary breast and ovarian cancer: review and future perspectives. J. Mol. Med. 84, 16–24 (2006)

    Article  Google Scholar 

  22. Lynch, B.J., Holden, J.A., Buys, S.S., Neuhausen, S.L., Gaffney, D.K.: Pathobiologic characteristics of hereditary breast cancer. Hereditary Breast Cancer 29(10):1140–1144 (1998)

    Google Scholar 

  23. Maley, C.C., Forrest, S.: Exploring the relationship between neutral and selective mutations in cancer. Artif. Life 6, 325–345 (2000)

    Article  Google Scholar 

  24. Man, Y.-G., Tai, L., Barner, R., Vang, R., Saenger, J.S., Shekitka, K.M., Bratthauer, G.L., Wheeler, D.T., Liang, C.Y., Vinh, T.N., Strauss, B.L.: Cell clusters overlying focally disrupted mammary myoepethelial cell layers and adjacent cells within the same duct display different immunohistochemical and genetic features: implications for tumor progression and invasion. Breast Cancer Res. 5, 231–241 (2003)

    Article  Google Scholar 

  25. Marcus, J.N., Watson, P., Page, D.L., Narod, S.A., Lenoir, G.M., Tonin, P., Linder-Stephenson, L., Salerno, G., Conway, T.A., Lynch, H.T.: Hereditary breast cancer—pathobiology, prognosis, and brca1 and brca2 gene linkage. cancer 77(4):697–709 (1996)

    Article  Google Scholar 

  26. Misell, L.M., Hwang, E.S., Au, A., Esserman, L., Hellerstein, M.K.: Development of a novel method for measuring in vivo breast epithelial cell proliferation in humans. Breast Cancer Res. Treat. 89, 257–264 (2005)

    Article  Google Scholar 

  27. Moreira, J., Deutsch, A.: Cellular automaton models of tumor development: a critical review. Adv. Complex Syst. 5, 247–267 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  28. Oborny, B., Czaran, T., Kun, A.: Exploration and exploitation of resource patches by clonal growth: a spatial model on the effects of transport between modules. Ecol. Modell. 141, 151–169 (2001)

    Article  Google Scholar 

  29. Reya, T., Morrison, S.J., Clarke, M.F., Weissman, I.L.: Stem cells, cancer, and cancer stem cells. Nature 414, 105–111 (2001)

    Article  Google Scholar 

  30. Rice, A.R., Hamilton, M.A., Camper, A.K.: Movement, replication, and emigration rates of individual bacteria in biofilm. Microb. Ecol. 45, 163–172 (2003)

    Article  Google Scholar 

  31. Schmitz, J.E., Kansal, A.R., Torquato, S.: A cellular automaton model of brain tumor treatment and resistance. J. Theor. Med. 4, 223–239 (2002)

    Article  MATH  Google Scholar 

  32. Smalley, M., Ashworth, A.: Stem cells and breast cancer: a field in transit. Nature 3, 832–844 (2003)

    Google Scholar 

  33. Stingl, J., Raouf, A., Emerman, J.T., Eaves, C.J.: Epithelial progenitors in the normal human mammary gland. J. Mammary Gland Biol. Neoplasia 10(1), 49–59 (2005)

    Google Scholar 

  34. Xu, Y.: A free boundary problem of ductal carcinoma in situ. Disc. Continuous Dynamic. Syst. B 4(1):337–348 (2004)

    MATH  Google Scholar 

Download references

Acknowledgments

This work is supported by NIH COBRE Grant P20 RR15587, NIH INBRE Grant P20 RR16448-01, NIH R01 CA104470 and NSF Grant EPS80935.

Author information

Authors and Affiliations

  1. Bioinformatics and Computational Biology, University of Idaho, Moscow, ID, 83843, USA

    Armand Bankhead III & Robert B. Heckendorn

Authors
  1. Armand Bankhead III
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Robert B. Heckendorn
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Armand Bankhead III.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bankhead, A., Heckendorn, R.B. Using evolvable genetic cellular automata to model breast cancer. Genet Program Evolvable Mach 8, 381–393 (2007). https://doi.org/10.1007/s10710-007-9042-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10710-007-9042-x

Keywords

Search

Navigation