Cell Cycle as a Fault Tolerant Control System

  • Jaroslaw SmiejaEmail author
  • Andrzej Swierniak
  • Roman Jaksik
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1196)


We present models focused on the control mechanisms in cell cycle, allowing to predict the propagation of faults and its consequences for the cell fate. Development of such models is a two-stage process. First a graph representing molecules and interaction among them is built, through an extensive search of bioinformatic databases and publications. Such graph can be subsequently used to find cutting nodes, representing proteins or complexes or cutting edges, representing biochemical processes that are needed by control mechanisms. The second step is modeling and development of a dynamical model, e.g. in the form of ordinary differential equations that describe changes in concentration of the molecules involved in control mechanisms.


DNA damage-repair Fault-tolerant control system Cell cycle Mutations Cancer 



This work was partially supported by Silesian University of Technology internal grant in the year 2020.


  1. 1.
    Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., Walter, P.: Molecular Biology of the Cell, 4th edn. Garland Science, New York (2002)Google Scholar
  2. 2.
    Neurath, H., Walsh, K.A.: Role of proteolytic enzymes in biological regulation (a review). Proc. Natl. Acad. Sci. 73(11), 3825–3832 (1976)CrossRefGoogle Scholar
  3. 3.
    Saier, M.J.: Classification of transmembrane transport systems in living organisms. In: Van Winkle, L. (ed.) Biomembrane transport. Academic Press, San Diego (1999)Google Scholar
  4. 4.
    Todeschini, A.L., Georges, A., Veitia, R.A.: Transcription factors: specific DNA binding and specific gene regulation. Trends Genet. 30(6), 211–219 (2014)CrossRefGoogle Scholar
  5. 5.
    Glisovic, T., Bachorik, J.L., Yong, J., Dreyfuss, G.: RNA-binding proteins and post-transcriptional gene regulation. FEBS Lett. 582(14), 1977–1986 (2008)CrossRefGoogle Scholar
  6. 6.
    Pomerening, J.R.: Positive-feedback loops in cell cycle progression. FEBS Lett. 583(21), 3388–3396 (2009)CrossRefGoogle Scholar
  7. 7.
    Puszynski, K., Hat, B., Lipniacki, T.: Oscillations and bistability in the stochastic model of p53 regulation. J. Theor. Biol. 254(2), 452–465 (2008)zbMATHCrossRefGoogle Scholar
  8. 8.
    Jonak, K., Kurpas M., Puszynski, K.: Prediction of the behavior of mammalian cells after exposure to ionizing radiation based on the new mathematical model of ATM-Mdm2-p 53 regulatory pathway. In: Piętka, E. Kawa, J., Wieclawek, W. (eds.) Information Technologies in Biomedicine, pp. 349–362. Springer, Cham (2014)Google Scholar
  9. 9.
    De Bont, R., van Larebeke, N.: Endogenous DNA damage in humans: a review of quantitative data. Mutagenesis 19(3), 169–185 (2004)CrossRefGoogle Scholar
  10. 10.
    Houtgraaf, J.H., Versmissen, J., van der Giessen, W.J.: A concise review of DNA damage checkpoints and repair in mammalian cells. Cardiovasc Revasc. Med. 7(3), 165–172 (2006)CrossRefGoogle Scholar
  11. 11.
    Dolbniak, M., Kimmel, M., Smieja, J.: Modeling epigenetic regulation of PRC1 protein accumulation in the cell cycle. Biol. Direct 10, 62 (2015)CrossRefGoogle Scholar
  12. 12.
    Jonak, K., Kurpas, M., Szoltysek, K., Janus, P., Abramowicz, A., Puszynski, K.: A novel mathematical model of ATM/p53/NF- κB pathways points to the importance of the DDR switch-off mechanisms. BMC Syst. Biol. 10(1), 75 (2016)CrossRefGoogle Scholar
  13. 13.
    Hat, B., Kochańczyk, M., Bogdał, M.N., Lipniacki, T.: Feedbacks, bifurcations, and cell fate decision-making in the p53 system. PLoS Comput. Biol. 12(2), e1004787 (2016)CrossRefGoogle Scholar
  14. 14.
    Wang, D.G., Wang, S., Huang, B., Liu, F.: Roles of cellular heterogeneity, intrinsic and extrinsic noise in variability of p53 oscillation. Sci Rep. 9(1), 5883 (2019)CrossRefGoogle Scholar
  15. 15.
    Goldbeter, A.: A minimal cascade model for the mitotic oscillator involving cyclin and cdc2 kinase. Proc. Natl. Acad. Sci. 88(20), 9107–9111 (1991)CrossRefGoogle Scholar
  16. 16.
    Pietenpol, J.A., Stewart, Z.A.: Cell cycle checkpoint signaling: cell cycle arrest versus apoptosis. Toxicology 181–182, 475–481 (2002)CrossRefGoogle Scholar
  17. 17.
    Branzei, D., Foiani, M.: Regulation of DNA repair throughout the cell cycle. Nat. Rev. Mol. Cell Biol. 9(4), 297–308 (2008)CrossRefGoogle Scholar
  18. 18.
    Hat, B., Puszynski, K., Lipniacki, T.: Exploring mechanisms of oscillations in p53 and nuclear factor-β systems. IET Syst. Biol. 3, 342–355 (2009)CrossRefGoogle Scholar
  19. 19.
    Cooper, G., Hausman, R.: The Cell: A Molecular Approach, 6th edn. Sinauer Associates, Sunderland (2013)Google Scholar
  20. 20.
    DeMars, R., Held, K.R.: The spontaneous azaguanine-resistant mutants of diploid human fibroblasts. Humangenetik 16(1), 87–110 (1972). Scholar
  21. 21.
    Loeb, L.A.: A mutator phenotype in cancer. Cancer Res. 61(8), 3230–3239 (2001)Google Scholar
  22. 22.
    Rohlin, A., Zagoras, T., Nilsson. S., Lundstam, U., Wahlström, J., Hultén, L., Martinsson, T., Karlsson, G.B., Nordling, M.: A mutation in POLE predisposing to a multi-tumour phenotype. Int. J. Oncol. 45(1), 77–81 (2014)Google Scholar
  23. 23.
    Popat, S., Hubner, R., Houlston, R.S.: Systematic review of microsatellite instability and colorectal cancer prognosis. J. Clin. Oncol. 23(3), 609–618 (2005)CrossRefGoogle Scholar
  24. 24.
    Kohn, K., Bohr, V.: Genomic instability and DNA repair. In: Alison, M. (ed.) The Cancer Handbook. Macmillan, Palgrave (2005)Google Scholar
  25. 25.
    Widel, M., Krzywon, A., Gajda, K., Skonieczna, M., Rzeszowska-Wolny, J.: Induction of bystander effects by UVA, UVB, and UVC radiation in human fibroblasts and the implication of reactive oxygen species. Free Radic. Biol. Med. 68, 278–287 (2014)CrossRefGoogle Scholar
  26. 26.
    Puszynski, K., Jaksik, R., Swierniak, A.: Regulation of P53 by Sirna in radiation treated cells: simulation studies. Int. J. Appl. Math. Comput. Sci. 22(4), 1011–1018 (2012)zbMATHCrossRefGoogle Scholar
  27. 27.
    Cieslar-Pobuda, A., Saenko, Y., Rzeszowska-Wolny, J.: PARP-1 inhibition induces a late increase in the level of reactive oxygen species in cells after ionizing radiation. Mutation Res. Fundam. Mol. Mech. Mutagenesis 732(1–2), 9–15 (2012)CrossRefGoogle Scholar
  28. 28.
    Harris, S.L., Levine, A.J.: The p53 pathway: positive and negative feedback loops. Oncogene 24(17), 2899–2908 (2005)CrossRefGoogle Scholar
  29. 29.
    Haupt, Y., et al.: Mdm2 promotes the rapid degradation of p 53. Nature 387(6630), 296–299 (1997)Google Scholar
  30. 30.
    Cantley, L.C., Neel, B.G.: New insights into tumor suppression: PTEN suppresses tumor formation by restraining the phosphoinositide 3-kinase AKT pathway. Proc. Natl. Acad. Sci. 96(8), 4240–4245 (1999)CrossRefGoogle Scholar
  31. 31.
    Johnson, D.G., Schneider-Broussard, R.: Role of E2F in cell cycle control and cancer. Front Biosci 3, 447–448 (1998)CrossRefGoogle Scholar
  32. 32.
    Lee, M., Rivera-Rivera, Y., Moreno, C.S., Saavedra, H.I.: The E2F activators control multiple mitotic regulators and maintain genomic integrity through Sgo1 and BubR1. Oncotarget 8(44), 77649–77672 (2017)CrossRefGoogle Scholar
  33. 33.
    Swierniak, A., Kimmel, M., Smieja, J., Puszynski, K., Psiuk-Maksymowicz, K.: System Engineering Approach to Planning Anticancer Therapies. Springer International Publishing, Cham (2016). Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Systems Biology and EngineeringSilesian University of TechnologyGliwicePoland

Personalised recommendations