Skip to main content

Games with Resources and Their Use in Modeling Effects of Anticancer Treatment

  • Conference paper
  • First Online:
Information Technology in Biomedicine (ITIB 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 762))

Included in the following conference series:

Abstract

In this work, we study an extension to evolutionary game models with the possibility to model the change and influence of the environment fluctuations for the fitness of the players. Using spatial games, those changes can be taken into account as an additional lattice dimension. In classical spatial evolutionary games (SEGT) each position on the lattice is represented by a single player or single phenotype (strategy). The local payoff for this player arises from the interactions with the neighbouring cells. With the newer approach each cell represents heterogeneous subpopulation, so can be considered as mixed or multidimensional spatial games (MSEG). This allows performing the game on a multidimensional lattice where an additional dimension is representing the evolution of resources.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bach, L., Bentzen, S., Alsner, J., Christiansen, F.: An evolutionary-game model of tumour-cell interactions: possible relevance to gene therapy. Eur. J. Cancer 37(16), 2116–2120 (2001). https://doi.org/10.1016/S0959-8049(01)00246-5

    Article  Google Scholar 

  2. Bach, L.A., Sumpter, D.J.T., Alsner, J., Loeschcke, V.: Spatial evolutionary games of interaction among generic cancer cells. J. Theor. Med. 5(1), 47–58 (2003). https://doi.org/10.1080/10273660310001630443

    Article  MATH  Google Scholar 

  3. Basanta, D., Gatenby, R.A., Anderson, A.R.A.: Exploiting evolution to treat drug resistance: combination therapy and the double bind. Mol. Pharm. 9(4), 914–921 (2012). https://doi.org/10.1021/mp200458e

    Article  Google Scholar 

  4. Basanta, D., Hatzikirou, H., Deutsch, A.: Studying the emergence of invasiveness in tumours using game theory. Eur. Phy. J. B 63, 393–397 (2008). https://doi.org/10.1140/epjb/e2008-00249-y

    Article  MathSciNet  MATH  Google Scholar 

  5. Basanta, D., Scott, J.G., Fishman, M.N., Ayala, G., Hayward, S.W., Anderson, A.R.A.: Investigating prostate cancer tumour-stroma interactions: clinical and biological insights from an evolutionary game. Br. J. Cancer 106(1), 174–181 (2012). https://doi.org/10.1038/bjc.2011.517

    Article  Google Scholar 

  6. Hofbauer, J., Schuster, P., Sigmund, K.: A note on evolutionary stable strategies and game dynamics. J. Theor. Biol. 81(3), 609–612 (1979). https://doi.org/10.1016/0022-5193(79)90058-4

    Article  MathSciNet  Google Scholar 

  7. Krześlak, M., Borys, D., Świerniak, A.: Angiogenic switch - mixed spatial evolutionary game approach. Intell. Inf. Database Syst. 9621, 420–429 (2016). https://doi.org/10.1007/978-3-662-49381-6_40

  8. Krześlak, M., Świerniak, A.: Spatial evolutionary games and radiation induced bystander effect. Arch. Control Sci. 21(2), 135–151 (2011). https://doi.org/10.2478/v10170-010-0036-1

    Article  MathSciNet  MATH  Google Scholar 

  9. Krześlak, M., Świerniak, A.: Multidimensional extended spatial evolutionary games. Comput. Biol. Med. 69, 315–327 (2016). https://doi.org/10.1016/j.compbiomed.2015.08.003

    Article  Google Scholar 

  10. Sigmund, K., Nowak, M.A.: Evolutionary game theory. Curr. Biol. 9(14), R503–R505 (1999). https://doi.org/10.1016/S0960-9822(99)80321-2

    Article  Google Scholar 

  11. Smith, J.M.: Evolution and the Theory of Games. Cambridge University Press, Cambridge (1982). https://doi.org/10.1017/CBO9780511806292

    Book  MATH  Google Scholar 

  12. Smith, J.M., Price, G.R.: The logic of animal conflict. Nature 246, 15–18 (1973). https://doi.org/10.1038/246015a0

    Article  MATH  Google Scholar 

  13. Świerniak, A., Krześlak, M.: Application of evolutionary games to modeling carcinogenesis. Math. Biosci. Eng. MBE 10(3), 873–911 (2013). https://doi.org/10.3934/mbe.2013.10.873

    Article  MathSciNet  MATH  Google Scholar 

  14. Świerniak, A., Krześlak, M.: Cancer heterogeneity and multilayer spatial evolutionary games. Biol. Direct 11(1), 53 (2016). https://doi.org/10.1186/s13062-016-0156-z

    Article  Google Scholar 

  15. Świerniak, A., Krześlak, M., Student, S., Rzeszowska-Wolny, J.: Development of a population of cancer cells: observation and modeling by a mixed spatial evolutionary games approach. J. Theor. Biol. 405, 94–103 (2016). https://doi.org/10.1016/j.jtbi.2016.05.027

    Article  Google Scholar 

  16. Tomlinson, I., Bodmer, W.: Modelling the consequences of interactions between tumour cells. Br. J. Cancer 75(2), 157–160 (1997). https://doi.org/10.1038/bjc.1997.26

    Article  Google Scholar 

Download references

Acknowledgement

This work was supported by the Polish National Science Centre Grant no. DEC-2016/21/B/ST7/02241 (AS), the Institute of Automatic Control, Silesian University of Technology under Grant No. BK-204/RAU1/2017 (MK) and the National Centre for Research and Development Grant no. STRATEGMED2/ 267398/4/NCBR/2015 (MILESTONE – Molecular diagnostics and imaging in individualized therapy for breast, thyroid and prostate cancer) (DB). Calculations were performed on the Ziemowit computer cluster in the Laboratory of Bioinformatics and Computational Biology, created in the EU Innovative Economy Programme POIG.02.01.00-00-166/08 and expanded in the POIG.02.03.01-00-040/13 project.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Andrzej Swierniak .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Swierniak, A., Krzeslak, M., Borys, D. (2019). Games with Resources and Their Use in Modeling Effects of Anticancer Treatment. In: Pietka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technology in Biomedicine. ITIB 2018. Advances in Intelligent Systems and Computing, vol 762. Springer, Cham. https://doi.org/10.1007/978-3-319-91211-0_26

Download citation

Publish with us

Policies and ethics