Chaos and cancers. Theories concerning carcinogenesis
, 2, 1, 3
Abstract
One of the most intriguing problems in biomedical sciences is the theory explaining cancer formation. It is known that
cancer is the result of many molecular processes, the presence of oncogenic factors and the loss of apoptosis of affected
cells. We currently have hypotheses based on carcinogenesis because of a single cell gene mutation, i.e. somatic mutation
theory (SMT), or disorders in tissue architecture and intercellular communication called (TOFT) Tissue Organization Field
Theory. An attempt to combine these separate and compatible cause and effect pathways into one unified theory of cancer
transformation is the theory of chaotic adaptation. The new interpretative model is the systemic-evolution theory of cancer
(SETOC) which postulates disintegration between the symbiosis of “energy” and “information” in normal cells. There are also
epidemiological studies confirming that some types of cancer arise from viral infection. So, let us ask the question, can one
hypothesis explain all the features of cancer?
Keywords: carcinogenesissomatic mutation theorytissue organization field theorychaotic adaptationsystemic-evolution theory of cancergenomechaosinformation
References
- Sonnenschein C, Soto AM. Theories of carcinogenesis: an emerging perspective. Semin Cancer Biol. 2008; 18(5): 372–377.
- Vaux D. In defense of the somatic mutation theory of cancer. BioEssays. 2011; 33(5): 341–343.
- Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011; 144(5): 646–674.
- Ye CJ, Sharpe Z, Alemara S, et al. Micronuclei and Genome Chaos: Changing the System Inheritance. Genes (Basel). 2019; 10(5).
- Duesberg P, Li R, Fabarius A, et al. The Chromosomal Basis of Cancer. Anal Cell Pathol. 2005; 27(5-6): 293–318.
- Baker SG, Vaux DL, Soto AM, et al. The tissue organization field theory of cancer: a testable replacement for the somatic mutation theory. Bioessays. 2011; 33(5): 332–340.
- Vong S, Kalluri R. The role of stromal myofibroblast and extracellular matrix in tumor angiogenesis. Genes Cancer. 2011; 2(12): 1139–1145.
- Li JW, Yang D, Yang D, et al. Tumors arise from the excessive repair of damaged stem cells. Med Hypotheses. 2017; 102: 112–122.
- Bedessem B, Ruphy S, Bedessem B, et al. SMT or TOFT? How the two main theories of carcinogenesis are made (artificially) incompatible. Acta Biotheor. 2015; 63(3): 257–267.
- Tomasetti C, Vogelstein B. Cancer etiology. Variation in cancer risk among tissues can be explained by the number of stem cell divisions. Science. 2015; 347(6217): 78–81.
- Mangel M, Bonsall MB. Phenotypic evolutionary models in stem cell biology: replacement, quiescence, and variability. PLoS One. 2008; 3(2): e1591.
- Braun E. The unforeseen challenge: from genotype-to-phenotype in cell populations. Rep Prog Phys. 2015; 78(3): 036602.
- Suzuki Y, Lu M, Ben-Jacob E, et al. Periodic, Quasi-periodic and Chaotic Dynamics in Simple Gene Elements with Time Delays. Sci Rep. 2016; 6: 21037.
- Agur Z, Kogan Y, Levi L, et al. Disruption of a Quorum Sensing mechanism triggers tumorigenesis: a simple discrete model corroborated by experiments in mammary cancer stem cells. Biol Direct. 2010; 5: 20.
- Weiss H. A Mathematical Introduction to Population Dynamics. IMPA Publicacões Matemáticas 2009.
- Tez M, Tez S. Chaos, Adaptation and Information are the Main Pillars of Carcinogenesis. .
- Heng HHQ, Liu G, Stevens JB, et al. Karyotype heterogeneity and unclassified chromosomal abnormalities. Cytogenet Genome Res. 2013; 139(3): 144–157.
- Khlebodarova TM, Kogai VV, Fadeev SI, et al. Chaos and hyperchaos in simple gene network with negative feedback and time delays. J Bioinform Comput Biol. 2017; 15(2): 1650042.
- Liu D, Albergante L, Newman TJ. Universal attenuators and their interactions with feedback loops in gene regulatory networks. Nucleic Acids Res. 2017; 45(12): 7078–7093.
- Luo G, Liu Na. An integrative theory for cancer (Review). Int J Mol Med. 2018.
- Poljsak B, Kovac V, Dahmane R, et al. Cancer Etiology: A Metabolic Disease Originating from Life's Major Evolutionary Transition? Oxid Med Cell Longev. 2019; 2019: 7831952.
- Seyfried TN. Cancer as a mitochondrial metabolic disease. Front Cell Dev Biol. 2015; 3: 43.
- Neagu M, Constantin C, Popescu ID, et al. Inflammation and Metabolism in Cancer Cell-Mitochondria Key Player. Front Oncol. 2019; 9: 348.
- Mazzocca A. The Systemic-Evolutionary Theory of the Origin of Cancer (SETOC): A New Interpretative Model of Cancer as a Complex Biological System. Int J Mol Sci. 2019; 20(19).
- Seyfried TN, Flores RE, Poff AM, et al. Cancer as a metabolic disease: implications for novel therapeutics. Carcinogenesis. 2014; 35(3): 515–527.
- Xia M, Zhang Y, Jin Ke, et al. Communication between mitochondria and other organelles: a brand-new perspective on mitochondria in cancer. Cell Biosci. 2019; 9: 27.
- Mello T, Simeone I, Galli A. Mito-Nuclear Communication in Hepatocellular Carcinoma Metabolic Rewiring. Cells. 2019; 8(5).
- Tommasino M. The biology of beta human papillomaviruses. Virus Res. 2017; 231: 128–138.
- Mazzocca A, Ferraro G, Misciagna G, et al. Moving the systemic evolutionary approach to cancer forward: Therapeutic implications. Med Hypotheses. 2018; 121: 80–87.
