Skip to main content

Complementarity, Complexity and the Fokker–Planck Equation; from the Microscale Quantum Stochastic Events to Fractal Dynamics of Cancer

  • Chapter
  • First Online:
Cancer, Complexity, Computation

Part of the book series: Emergence, Complexity and Computation ((ECC,volume 46))

  • 405 Accesses

Abstract

Tumourigenesis possesses no equivalent among known physical phenomena. It is initiated at the quantum level by thermodynamic fluctuations of macromolecules. Accumulation of non-lethal alterations in quasi-deterministic dynamic cellular network of genes and their regulatory protein elements facilitated by changes in microenvironment results in a weak emergence of non-complementary, malignant phenotype. The Weibull distribution of cancer incidence suggests that neuro-immuno-hormonal network modifies that process. Eucaryotic cells are supramolecular objects. They make use of quantum entanglement, quantum tunneling, coherence, and chirality in formation of novel molecular couplings with both multiple feedbacks, synergy, and hysteresis. Complementarity at each integration level and non-ergodicity are their distinguishing features. Quantum effects may contribute to the conjugated appearance of cancer mutations. Connectivity, that is, coupling between integration levels is associated with the emergence of at least three features: fractal geometry of space–time, in which growth occurs, conditional probability of events, which reduces sensitivity to the initial conditions, and entropy. The latter one determines both a capability of the supramolecular system for transfer of biologically relevant information and evolution of intercellular interactions. There is a limit for self-organization of cells into structures of higher order defined by the Fibonacci constant. A relationship between sigmoidal dynamics and the Feigenbaum diagram suggests that both growth and self-organization occur with parameters within the Mandelbrot set. The set of non-interacting, infiltrating cancer cells becomes topologically dense. It has the highest entropy. The global spatial fractal dimension approaches the integer value. Hence, the coefficient of cellular expansion is a novel quantitative measure of biological tumour aggressiveness. It is based on complexity of intercellular interactions. Neither biological complexity can be reduced to physical one, nor be fully mathematized. Computer simulations may help to elucidate details of tumourigenesis. The mathematical models should be expressed in the algebraic form of fractal sheaves and fractional equations.

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 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover 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

Similar content being viewed by others

References

  1. Virchow, R.: Die Cellular pathologie in ihrer Begründung auf physiologische und pathologische Gewebelehre. Verlag A. Hirschwald, Berlin (1858)

    Google Scholar 

  2. Reya, T., Morrison, S.J., Clarke, M.F., Weissman, I.L.: Stem cells, cancer, and cancer stem cells. Nature 414(6859), 105–111 (2001)

    Google Scholar 

  3. Gonzales-Villarreal, C.A., Quiros-Reyes, A.G., Islas, I.F., Garza-Trevino, E.N.: Colorectal cancer stem cells in the progression to liver metastasis. Front. Oncol. (2020). https://doi.org/10.3389/fonc.2020.01511

  4. Waliszewski, P.: Complexity, dynamic cellular network, and tumorigenesis. Pol. J. Pathol. 48(4), 235–241 (1997)

    Google Scholar 

  5. Davies, P.C., Demetrius, L., Tuszynski, J.A.: Cancer as a dynamical phase transition. Theor. Biol. Med. Model. 8(30), 1–16 (2011)

    Google Scholar 

  6. Niedergang, F.: Phagocytosis. Encycl. Cell Biol. 2, 751–757 (2016)

    Google Scholar 

  7. Waliszewski, P.: The Fibonacci constant and limits of tissue self-organization; local complexity measures in evaluation of the risk of metastasis formation. Banach Center Publ 124, 143–157 (2021). In: Banaszak G., Krason P., Milewski J., Waliszewski P. (eds.) Arithmetic Methods in Mathematical Physics and Biology II. Bedlewo, August 3–11, (2018) https://doi.org/10.4064/bc124-12

  8. Waliszewski, P., Molski, M., Konarski, J.: On the holistic approach in cellular and cancer biology: nonlinearity, complexity, and quasi-determinism of the dynamic cellular network. J. Surg. Oncol. 68(2), 70–78 (1998)

    Google Scholar 

  9. Huxley, J.: The dawn of quantum biology 474, 272–274 (2011)

    Google Scholar 

  10. McFadden, J., Al-Khalili, J.: A quantum mechanical model of adaptive mutation. Biosystems 50, 203–211 (1999)

    Google Scholar 

  11. Cooper, W.G.: Roles of evolution, quantum mechanics and point mutations in origins of cancer. Cancer Biochem. Biophys. 13(3), 147–170 (1993)

    Google Scholar 

  12. Kryachko, E.S.: The origin of spontaneous point mutations in DNA via Loewding mechanism of proton transition in DNA base pairs. Cure with covalent base parity. Int. J. Quantum Chem. (2002). https://doi.org/10.1002/qua.975

  13. Zapatka, M., Borozan, I., Brewer, D.S., Iskar, M., Grundhoff, A., Alawi, M., Desai, N., Sültmann, H., Moch, H., Cooper, C.S., Eils, R., Ferretti, V., Lichter, P.: The landscape of viral associations in human cancers. Nat. Genet. 52, 320–330 (2020)

    Google Scholar 

  14. Loewe, L., Hill, W.G.: The population genetics of mutations: good, bad, and indifferent. Philos. Trans. R Soc. B 365, 1153–1167 (2010)

    Google Scholar 

  15. Tomasetti, C., Lu, L., Vogelstein, B.: Stem cell division, somatic mutation, cancer etiology, and cancer prevention. Science 355, 1330–1334 (2017)

    Google Scholar 

  16. Robert, L., Ollion, J., Robert, J., Song, X., Matic, I., Elez, M.: Mutation dynamics and fitness effects followed in single cells. Science 359, 1283–1286 (2018)

    Google Scholar 

  17. Cairns, J., Overbay, J., Miller, S.: The origin of mutants. Nature 335, 142–145 (1988)

    Google Scholar 

  18. Moreno, P.A., Velez, P.E., Martinez, E., Garreta, L.E., Diaz, N., Amador, S., Tischer, I., Gutierrez, J.M., Naik, A.K., Tobar, F., Garcia, F.: The human genome: a multifractal analysis. BMC Genomics 12(506), 1–17 (2011)

    Google Scholar 

  19. Oliver, J.L., Bernaola-Galvan, P., Guerrero-Garcia, J., Roman-Roldan, R.: Entropic profiles of DNA sequences through chaos-game-derived images. J. Theor. Biol. 160, 457–470 (1993)

    Google Scholar 

  20. Hochberg, G.K.A., Liu, Y., Marklund, E.D., Metzger, B.P.H., Laganowsky, A., Thornton, J.W.: A hydrophobic ratchet entrenches molecular complexes. Nature 588, 503–508 (2020)

    Google Scholar 

  21. Plon, S.E., Eccles, D.M., Easton, D., Foulkes, W.D., Genuardi, M., Greenblatt, M.S., Hogervorst, F.B.L., Hoogerbrugge, N., Spurdle, A.B., Tavtigian, S.V.: Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results. Hum. Mutat. 29(11), 1282–1291 (2008)

    Google Scholar 

  22. Ononye, O.E., Sausen, Ch.W., Balakrishnan, L., Bochman, M.L.: Lysine acetylation regulates the activity of nuclear pif1. J. Biol. Chem. 295(46), 15482–15497 (2020)

    Google Scholar 

  23. Lu, Y., Brommer, B., Tian, X., Krishnan, A., Meer, M., Wang, Ch., Vera, D., Zeng, Q., Yu, D., Bonkowski, M., Yang, J.-H., Zhou, S., Hoffmann, E., Karg, M., Schultz, M., Kane, A., Davidson, N., Korobkina, E., Chwalek, K., Rajman, L., Church, G., Hochedlinger, K., Gladyshev, V., Horvath, S., Levine, M., Gregory-Ksander, M.S., Ksander, B.R., He, Z., Sinclair, D.A.: Reprogramming to recover youthful epigenetic information and restore vision. Nature 588(7836), 124–129 (2020)

    Google Scholar 

  24. Zhuang, J., Jones, A., Lee, S.H., Ng, E., Fiegl, H., Zikan, M., Cibula, D., Sargent, A., Salvesen, H.B., Jacobs, I.J., Kitchener, H.C., Teschendorff, A.E., Widschwendter, M.: The dynamics and prognostic potential of DNA methylation changes at stem cell gene loci in women’s cancer. PLoS Genet. 8(2), e1002517, 1–12 (2012)

    Google Scholar 

  25. De Craene, B., Berx, G.: Regulatory networks defining EMT during cancer initiation and progression. Nat. Rev. Cancer 13, 97–110 (2013)

    Google Scholar 

  26. Verschoor, M.L., Ungard, R., Harbottle, A., Jakupciak, J.P., Parr, R.L., Singh, G.: Mitochondria and cancer: past, present, and future. Biomed. Res. Int. 2013, 612369 (2013)

    Google Scholar 

  27. Vyas, S., Zaganjor, E., Haigis, M.C.: Mitochondria and cancer. Cell 166(3), 555–566 (2016)

    Google Scholar 

  28. Davidson, S.M., van der Heiden, M.G.: Critical functions of the lysosome in cancer biology. Ann. Rev. Pharm. Toxicol. 57, 481–507 (2016)

    Google Scholar 

  29. Terasaki, M., Shemesh, T., Kasthuri, N., Klemm, R.W., Schalek, R., Hayworth, K.J., Hand, A.R., Yankova, M., Huber, G.: Stacked endoplasmic reticulum sheets are connected by helicoidal membrane motifs. Cell 154(2), 285–296 (2013)

    Google Scholar 

  30. Oakes, S.A.: Endoplasmic stress signaling in cancer cells. Am. J. Pathol. 190, 934–946 (2020)

    Google Scholar 

  31. Zong, W.X., Rabinowitz, J.D., White, E.: Mitochondria and cancer. Mol. Cell. 61(5), 667–676 (2016)

    Google Scholar 

  32. Waliszewski, P., Konarski, J.: Neuronal differentiation and synapse formation occur in space and time with fractal dimension. Synapse 43(4), 252–258 (2002)

    Google Scholar 

  33. Fane, M., Weeraratna, A.T.: How the aging microenvironment influences tumor progression. Nat. Rev. Cancer 20(2), 89–106 (2020)

    Google Scholar 

  34. Janiszewska, M., Candido Primi, M., Izard, T.: Cell adhesion in cancer: beyond the migration of single cells. J. Biol. Chem. 295, 2495–2505 (2020)

    Google Scholar 

  35. Vignais, M.L., Nakhle, J., Griessinger, E.: Tunneling nanotubes (TNTs): intratumoral cell-to-cell communication. In: Encyclopedia of Cancer, Boffetta P., Hainaut P. (eds.) Hallmarks of Cancer, pp. 513–522. Academic (2019). ISBN 978-0-12-812485-7

    Google Scholar 

  36. Lugano, R., Ramachandran, M., Dimberg, A.: Tumor angiogenesis: causes, consequences, challenges, and opportunities. Cell Mol. Life Sci. 77, 1745–1770 (2020)

    Google Scholar 

  37. Reeves, M.Q., Kandyba, E., Harris, S., Del Rosario, R., Balmain, A.: Multicolour lineage tracing reveals clonal dynamics of squamous carcinoma evolution from initiation to metastasis. Nat. Cell Biol. 20(6), 699–709 (2018)

    Google Scholar 

  38. Allee, W.C., Bowen, E.: Studies in animal aggregation: mass protection against colloidal silver among goldfishes. J. Exp. Zool. 61(2), 185–207 (1932)

    Google Scholar 

  39. Waliszewski, P.: The quantitative criteria based on the fractal dimensions, entropy and lacunarity for the spatial distribution of cancer cell nuclei enable identification of low or high aggressive prostate carcinomas. Front. Physiol. Fract. Physiol. 7(34), 1–16 (2016)

    Google Scholar 

  40. Tanase, M., Waliszewski, P.: On complexity and homogenity measures in predicting biological aggressiveness of prostate cancer; implication of the cellular automata model of tumor growth. J. Surg. Oncol. 112(8), 791–801 (2015)

    Google Scholar 

  41. Waliszewski, P.: Computer-aided image analysis and fractal synthesis in the quantitative evaluation of tumor aggressiveness in prostate carcinomas. Front. Oncol. Genitourin. Oncol. 6, 110 (2016)

    Google Scholar 

  42. Waliszewski, P., Banaszak, G.: On fractal and topological measures in human colon carcinomas. In: Proceedings 2021 23rd International Conference on Control Systems and Computer Science, Bucharest, 26–28 May 2021. https://doi.org/10.1109/CSCS52396.2021.00042

  43. Lu, M., Jolly, M.K., Levine, H., Onuchic, J.N., Ben-Jacob, E.: MicroRNA-based regulation of epithelial-hybrid-mesenchymal fate determination. PNAS 110(45), 18144–18149 (2013)

    Google Scholar 

  44. Waliszewski, P., Konarski, J., Molski, M.: On the modification of fractal self-space during tumor progression. Fractals 8(2), 195–203 (2000)

    Google Scholar 

  45. Chandolia, B., Bajpai, M.: Epithelial Mesenchymal Interactions. Lambert Academic Publishing, Saarbrücken (2016)

    Google Scholar 

  46. Waliszewski, P., Konarski, J.: On time-space of nonlinear phenomena with Gompertzian dynamics. Biosystems 80, 91–97 (2005)

    Google Scholar 

  47. Waliszewski, P.: A principle of fractal-stochastic dualism and Gompertzian dynamics of growth and self-organization. Biosystems 82(1), 61–73 (2005)

    Google Scholar 

  48. Stewart, J.: Calculus - Early Transcendentals, 7th edn. Brooks/Cole Cengage Learning, p. 1122 (2021)

    Google Scholar 

  49. Siegel, R.L., Miller, K.D., Jemal, A.: Cancer statistics 2019. CA Cancer J. Clin. 69(1), 7–34 (2019)

    Google Scholar 

  50. Cancer Research UK Prostate cancer incidence statistics (2019). https://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/prostate-cancer/incidence#heading-One

  51. Erickson, A., Hayes, A., Rajakumar, T., Verrill, C., Bryan, R.J., Hamdy, F.C., Wege, D.C., Woodcock, D.J., Miller, I.G., Lamb, A.D.: A systemic review of prostate cancer hetrogeneity: understanding the clonal ancestry of multifocal disease. Eur. Urol. Oncol. 4(3), 358–369 (2021)

    Google Scholar 

  52. Williams, M.J., Werner, B., Barnes, Ch.P., Graham, T.A., Sottoriva, A.: Identification of neutral tumor evolution across cancer types. Nat. Genet. 48, 238–244 (2016). https://doi.org/10.1038/ng.3489

  53. Wodarz, D., Komarova, N.L.: Mutant evolution in spatially structured and fragmented expanding populations. Genetics 216(1), 191–203 (2020)

    Google Scholar 

  54. Szymanska, K., Bosman, F.T., Hainaut, P.: Bladder cancer: pathology, genetics, diagnosis and treatment. In: Boffetta P., Hainaut P. (eds.) Encyclopedia of Cancer, 3rd edn., pp. 122–133. Elsevier, Amsterdam (2019)

    Google Scholar 

  55. Gerlinger, M., Rowan, A.J., Horswell, S., Math, M., Larkin, J., Endesfelder, D., Gronroos, E., Martinez, P., Matthews, N., Stewart, A., Tarpey, P., Varela, I., Phillimore, B., Begum, S., McDonald, N.Q., Butler, A., Jones, D., Raine, K., Latimer, C., Santos, C.R., Nohadani, M., Eklund, A.C., Spencer-Dene, B., Clark, G., Pickering, L., Stamp, G., Gore, M., Szallasi, Z., Downward, J., Futreal, P.A., Swanton, C.: Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N. Engl. J. Med. 366, 883–892 (2012)

    Google Scholar 

  56. Schwann, Th.: Mikroskopische Untersuchungen über die Übereinstimmung in der Struktur und dem Wachstum der Thiere und Pflanzen. Sander, Berlin (1839) http://www.deutschestextarchiv.de/book/show/schwann_mikroskopische_1839

  57. Schwann, Th., Schleyden, M.J.: Microscopical Researches into the Accordance in the Structure and Growth of Animals and Plants. Printed for the Sydenham Society, London (1847). http://vlp.mpiwg-berlin.mpg.de/library/data/lit28715

  58. Bongrand, P.: Ligand-receptor interactions. Rep. Prog. Phys. 62, 921–968 (1999)

    Google Scholar 

  59. Stein, D.L. (ed.): Lectures in the Science of Complexity. Adison-Wesley Pub. Co., Advanced Book Program, Redwood, CA (1989)

    Google Scholar 

  60. West, B.J., Geneston, E.L., Grigolini, P.: Maximizing information exchange between complex networks. Phys. Rep. 468, 1–99 (2008)

    MathSciNet  MATH  Google Scholar 

  61. Kirilyuk, A.: New mathematics of complexity and its biomedical applications. In: Banaszak, G., Milewski, J., Waliszewski, P. (eds.) Arithmetic Methods in Mathematical Physics and Biology, vol. 109, pp. 57–81. The Banach Center Publications, Warsaw (2016). https://doi.org/10.4064/bc109-0-5

  62. Waliszewski, P., Konarski, J.: Tissue as a self-organizing system with fractal dynamics. Adv. Space Res. 28(4), 545–548 (2001)

    Google Scholar 

  63. Kim, S.Ch., Zhou, L., Zhang, W., O’Flaherty, D.K., Rondo-Broveto, V., Szostak, J.W.: A model for the emergence of RNA from a prebiotically plausible mixture of ribonucleotides, arabinonucleotides, and 2′-deoxynucleotides. J. Am. Chem. Soc. 142(5), 2317–2326 (2020)

    Google Scholar 

  64. Micura, R., Höbartner, C.: Fundamental studies of functional nucleic acids: aptamers, riboswitches, ribozymes and DNAzymes. Chem. Soc. Rev. 49, 7331–7353 (2020)

    Google Scholar 

  65. Zhang, Y., Narlikar, G.J., Kutateladze, T.G.: Enzymatic reactions inside biological condensates. J. Mol. Biol. 166624 (2020)

    Google Scholar 

  66. Meyer, S.C.: Darwin’s doubt: the explosive origin of animal life and the case for intelligent design. HarperOne (2014). ISBN-10 0062071483

    Google Scholar 

  67. Berlinski, D.: The deniable Darwin and other essays. Discovery Inst 2009 (2009). ISBN-10 0979014131

    Google Scholar 

  68. Tilokani, L., Nagashima, S., Paupe, V., Prudent, J.: Mitochondrial dynamics: overview of molecular mechanisms. Essays Biochem. 62, 341–360 (2018)

    Google Scholar 

  69. Rossi, A., Pizzo, P., Filadi, R.: Calcium, mitochondria and cell metabolism: a functional triangle in bioenergetics. Biochim. Biophys. Acta Mol. Cell Res. 1866(7), 1068–1078 (2019). https://doi.org/10.1016/j.bbamcr.2018.10.016

    Article  Google Scholar 

  70. Waliszewski, P., Skwarek, R.: Deterministic chaos and mitochondrial synthesis of reactive oxygen species. In: Proceedings 2017 21st International Conference on Control Systems and Computer Science, Bucharest, 29–31 May 2017, pp. 356–363. https://doi.org/10.1109/CSCS.2017.55

  71. Langmuir, I.: The constitution and fundamental properties of solids and liquids. J. Am. Chem. Soc. 39, 1848 (1917)

    Google Scholar 

  72. Hermann, J., DiStasio, R.A., Tkatchenko, A.: First principles models for van der Waals interactions in molecules and materials: concepts, theory, and applications. Chem. Rev. 117, 4714–4758 (2017)

    Google Scholar 

  73. Woods, L.M., Dalvit, D.A.R., Tkatchenko, A., Rodriguez-Lopez, P., Rodriguez, A.W., Podgornik, R.: Materials perspective on Casimir and van der Waals interactions. Rev. Mod. Phys. 88(4), 045003 1–48 (2016)

    Google Scholar 

  74. Lord Kelvin, P.R.S.: The Molecular Tactics of a Crystal, p. 27. The Clarendon Press, Oxford (1894)

    Google Scholar 

  75. Kurian, P., Dunston, G., Lindesay, J.: How quantum entanglement in DNA synchronizes double-strand breakage by type II restriction endonucleases. J. Theor. Biol. 391, 102–112 (2016)

    MathSciNet  MATH  Google Scholar 

  76. Hay, S., Scrutton, N.S.: Good vibrations in enzyme-catalysed reactions. Nat. Chem. 4, 161–168 (2012)

    Google Scholar 

  77. Bell, J.S.: On the Einstein-Rosen-Podolsky paradox. Physics 1(3), 195–200 (1964)

    MathSciNet  Google Scholar 

  78. Chen, E.K.: Bell’s theorem, quantum probabilities, and superdeterminism. In: Knox E., Wilson A. (eds.) The Routledge Companion to the Philosophy of Physics (2020). arXiv:2006:08609v2 [quant-phys]

  79. O’Callaghan, J.: “Schrödinger's Bacterium” Could Be a Quantum Biology Milestone. Scientific American, 29 October 2018 (2018)

    Google Scholar 

  80. Trixler, F.: Quantum tunnelling to the origin and evolution of life. Curr. Org. Chem. 17(16), 1758–1770 (2013)

    Google Scholar 

  81. Chance, B.: The energy-linked reaction of calcium with mitochondria. J. Biol. Chem. 240(6), 2729–2748 (1965)

    Google Scholar 

  82. Engel, G., Calhoun, T.R., Read, E.L., Ahn, T.K., Mancal, Th., Cheng, Y.Ch., Blankenship, R.E., Fleming, G.R.: Evidence for wave maker energy transfer through quantum coherence in photosynthetic systems. Nature 446(7137), 782–786 (2007)

    Google Scholar 

  83. Grover, L.K.: From Schrödinger’s equation to quantum search algorithm. Am. J. Phys. 69(7), 769–777 (2001)

    Google Scholar 

  84. Hoyer, S., Sarovar, M., Whaley, K.B.: Limits of quantum speedup in photosynthetic light harvesting. NJP 12, 065041 (2010)

    Google Scholar 

  85. Fletcher, D.A., Mullins, R.D.: Cell mechanics and the cytoskeleton. Nature 463(7280), 485–492 (2010)

    Google Scholar 

  86. Goldstein, R.E., van de Meent, J.W.: A physical perspective on cytoplasm in streaming. Interface Focus 5(4), 20150030 (2015)

    Google Scholar 

  87. Elbaum-Garfinkle, S., Kim, Y., Szczepaniak, K., Chih-Hiung Chen, C., Eckmann, Ch.R., Myong, S., Brangwynne, C.P.: The diordered P granule protein LAF-1 drives phase separation into droplets with tunable viscosity and dynamics. Proc. Natl. Acad. Sci. USA 112, 7189–7194 (2015)

    Google Scholar 

  88. Koenig, H.G.: Religion, spirituality, and health: a review and update. Adv. Mind Body Med. 29(3), 19–26 (2015)

    Google Scholar 

  89. Davis, P.C.W.: Time variation of the coupling constants. J. Phys. A: Math. Gen. 5, 1296–1304 (1972)

    Google Scholar 

  90. Weber, H.M., Dedekind, R.: Bernhard Riemann’s gesammelte mathematische Werke und wissenschaftlicher Nachlass. Cambridge University Press, Cambridge (2013)

    Google Scholar 

  91. Kaufmann, S.: Investigations, pp. 159–209. Oxford University Press, Oxford (2000)

    Google Scholar 

  92. Termonia, Y., Ross, J.: Oscillations and control features in glycolysis: analysis of resonance effect. PNAS 76(6), 3563–3566 (1981)

    Google Scholar 

  93. Mair, T., Warnke, Ch., Tsuji, K., Müller, S.C.: Control of glycolytic oscillations by temperature Biophys. J. 88(1), 639–646 (2005)

    Google Scholar 

  94. Nelson, D.L., Cox, M.M.: Lehninger Principles of Biochemistry, 8th edn. Freeman WH and Co. (2021)

    Google Scholar 

  95. Yang, W.J., Cho, K.S., Rha, K.H., Lee, H.Y., Chung, B.H., Hong, S.J., Yang, S.C., Choi, Y.D.: Long-term effects of ileal conduit urinary diversion on upper urinary tract in bladder cancer. Urology 68(2), 324–327 (2006)

    Google Scholar 

  96. Okon, K., Dyduch, G., Bialas, M.B., Milian-Ciesielska, K., Szpor, J., Leszczynska, I., Tyrak, K., Szopinski, T., Chlosta, P.: Image analysis discloses differences in nuclear parameters between ERG+ and ERG- prostatic carcinomas. Pol. J. Pathol. 71(1), 20–29 (2020)

    Google Scholar 

  97. Vlajnic, T., Bubendorf, L.: Molecular pathology of prostate cancer: a practical approach. Pathology 53(1), 36–43 (2021)

    Google Scholar 

  98. Lozano, R., Castro, E., Aragón, I.M., Cendon, Y., Cattrini, C., Lopes-Casas, P.P., Olmos, D.: Genetic aberrations in DNA repair pathways: a cornerstone of precision oncology in prostate cancer. Br. J. Cancer 124, 552–563 (2021)

    Google Scholar 

  99. Josefsson, A., Larsson, K., Freyhult, E., Damber, J.E., Welen, K.: Gene expression alterations during development of castration-resistant prostate cancer are detected in circulating tumor cells. Cancer 12(1), 39 (2019)

    Google Scholar 

  100. Casinello, J., Dominguez-Lubillo, T., Gomez-Barrera, M., Hernando, T., Parra, R., Asensio, I., Casado, M.A., Moreno, P.: Optimal treatment sequencing of abiraterone acetate plus prednisone and enzalutamide in patients with castration-resistant metastatic prostate cancer: a systematic review and metaanalysis. Cancer Treat Rev. 93, 102152 (2021)

    Google Scholar 

  101. Mendel, G.: Experiments in plant hybridization (1865)

    Google Scholar 

  102. Husserl, E.: Ideen zu einer reinen Phänomenologie und phänomenologischen Philosophie. Erstes Buch: Allgemeine Einführung in die reine Phänomenologie. Max Niemeyer Verlag, Halle (Saale) (1913)

    Google Scholar 

  103. Held, T., Nourmohammad, A., Lässig, M.: Adaptive evolution of molecular phenotypes. J. Stat. Mech.: Theory Exp. P09029 (2014)

    Google Scholar 

  104. Quintero-Fabián, S., Arreola, R., Becerril-Villanueva, E., Torres-Romero, J.C., Arana-Argáez, V., Lara-Riegos, J., Ramírez-Camacho, M.A., Alvarez-Sánchez, M.E.: Role of matrix metalloproteinases in angiogenesis and cancer. Front. Oncol. 9, 1370 (2019)

    Google Scholar 

  105. Waliszewski, P.: The circular fractal model of adenocarcinomas and tumor aggressiveness. Banach Center Publ. 109, 183–196 (2016). https://doi.org/10.4064/bc109-0-12

    Article  MathSciNet  MATH  Google Scholar 

  106. Baas-Becking, L.G.M., Drion, E.F.: On the origin of frequency distributions in biology. Acta. Biotheor. 1, 133–150 (1936)

    MATH  Google Scholar 

  107. Kuznetsov, V.A., Knott, G.D., Bonner, R.E.: General statistics of stochastic gene expression in eucaryotic cells. Genetics 161(3), 1321–1332 (2002)

    Google Scholar 

  108. Cao, Z., Grima, R.: Analytical distribution for detailed models of stochastic gene expression in eucaryotic cells. Proc. Natl. Acad. Sci. USA 117(9), 4682–4692 (2020)

    Google Scholar 

  109. Magin, R.L.: Fractional calculus models of complex dynamics in biological tissues. Comput. Math. Appl. 59(5), 1586–1593 (2010)

    MathSciNet  MATH  Google Scholar 

  110. Campoy, E.M., Branham, M.T., Mayorga, L.S., Rogue, M.: Intratumor heterogeneity index in breast carcinomas based on DNA methylation profile. BMC Cancer 19, 328 (2019)

    Google Scholar 

  111. Swanton, Ch.: Intratumor heterogeneity: evolution through space and time. Cancer Res. 72(19), 4875–4882 (2012)

    Google Scholar 

  112. Wu, X.R.: Urothelial tumorigenesis: a tale of divergent pathways. Nat. Rev. Cancer 5, 713–725 (2005)

    Google Scholar 

  113. Castillo-Martin, M., Domingo-Domenech, J., Karni-Schmidt, O., Matos, T.: Molecular pathways of urothelial development and bladder tumorigenesis. Urol. Oncol. 28(4), 401–408 (2010)

    Google Scholar 

  114. Andrews, B.T., Capraro, D.T., Sulkowska, J.I., Onuchic, J.N., Jennings, P.A.: Hysteresis as a marker for complex, overlapping landscapes in proteins. J. Phys. Chem. Lett. 4, 180–188 (2013)

    Google Scholar 

  115. Chatterjee, A., Kaznessis, Y.N., Hu, W.S.: Tweaking biological switches through a better understanding of bistability behavior. Curr. Opin. Biotechnol. 19, 475–481 (2008)

    Google Scholar 

  116. Angeli, D., Ferrell, J.E., Jr., Sontag, E.D.: Detection of multistability, bifurcations, and hysteresis in a large class of biological positive-feedback systems. Proc. Natl. Acad. Sci. USA 101, 1822–1827 (2004)

    Google Scholar 

  117. Eissing, T., Conzelmann, H., Gilles, E.D., Allgoewer, F., Bullinger, E., Scheurich, P.: Bistability analyses of a caspase activation model for receptor-induced apoptosis. J. Biol. Chem. 279, 36892–36897 (2004)

    Google Scholar 

  118. Pomerening, J.R., Sontag, E.D., Ferrell, J.E.: Building a cell cycle oscillator: hysteresis and bistability in the activation of Cdc2. Nat. Cell Biol. 5(4), 346–351 (2003)

    Google Scholar 

  119. Solomon, M.J.: Hysteresis meets the cell cycle. Proc. Natl. Acad. Sci. USA 100, 771–772 (2003)

    Google Scholar 

  120. Vesper, M.D., de Groot, B.L.: Collective dynamics underlying allosteric transitions in hemoglobin. PLoS Comput. Biol. 9(9), e1003232 (2013)

    Google Scholar 

  121. Peter, A.: Corning, The Synergism Hypothesis: A Theory of Progressive Evolution. McGraw Hill, New York (1983)

    Google Scholar 

  122. Waliszewski, P., Konarski, J.: A mystery of the Gompertz curve. Losa, G.A., Merlini, D., Nonnenmacher, Th.F., Weibel, R.E. (eds.): Fractals in Biology and Medicine, vol. IV, pp. 277–286. Birkhäuser, Basel (2005)

    Google Scholar 

  123. Mytych, J., Romerowicz-Misielak, M., Koziorowski, M.: Long-term culture with lipopolysaccharide induces dose-dependent cytostatic and cytotoxic effects in THP-1 monocytes. Toxicol. In Vitro 42, 1–9 (2017)

    Google Scholar 

  124. Baas Becking, L.G.M.: On the analysis of sigmoid curves. Acta. Biotheor. 8, 42–59 (1946)

    Google Scholar 

  125. West, B., Bologna, M., Grigolini, P.: Physics of Fractal Operators. Springer (2003)

    Google Scholar 

  126. Biro, T.S., Telcs, A., Neda, Z.: Entropic distance for nonlinear master equation. Universe 4, 10 (2018). https://doi.org/10.3390/universe4010010

    Article  Google Scholar 

  127. DeMarco, L., Lindsey, K.: Convex shapes and harmonic caps. Arnold Math. J. 3, 97–117 (2017)

    MathSciNet  MATH  Google Scholar 

  128. Waliszewski, P.: A principle of fractal-stochastic dualism, couplings, complementarity and growth. Control Eng. Appl. Inform. 11(4), 45–52 (2009)

    Google Scholar 

  129. Waliszewski, P., Molski, M., Konarski, J.: On the relationship between fractal geometry of space and time in which a system of interacting cells exists and dynamics of gene expression. Acta Biochim. Pol. 48(1), 209–220 (2001)

    Google Scholar 

  130. Elledge, S.J.: Cell cycle checkpoints: preventing an identity crisis. Science 274, 1664–1672 (1996)

    Google Scholar 

  131. Kullback, S.: Information Theory and Statistics. Dover Publications, New York (1997)

    MATH  Google Scholar 

  132. Waliszewski, P., Konarski, J.: The complex couplings and Gompertzian dynamics. In: Novak, M.M. (ed.) Complexus Mundi Emergent Patterns in Nature, pp. 343–344. World Scientific Publishing, Singapore (2006)

    Google Scholar 

  133. Shannon, C.E.: A mathematical theory of communication. Bell Syst. Tech. J. 27, 629–630 (1948)

    MathSciNet  Google Scholar 

  134. Borowkow, A.A.: Kurs teorii wierojatnostiej (Russian). Nauka, Moskwa (1972)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Przemyslaw Waliszewski .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Waliszewski, P. (2022). Complementarity, Complexity and the Fokker–Planck Equation; from the Microscale Quantum Stochastic Events to Fractal Dynamics of Cancer. In: Balaz, I., Adamatzky, A. (eds) Cancer, Complexity, Computation. Emergence, Complexity and Computation, vol 46. Springer, Cham. https://doi.org/10.1007/978-3-031-04379-6_2

Download citation

Publish with us

Policies and ethics