НЕРЕШАЕМЫЕ ПРОБЛЕМЫ БИОЛОГИИ. Ключевые слова
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17, 1685–1687. 56. DeGregori, J. (2011) Evolved tumor suppression: why are we so good at not getting cancer? Cancer Res., 71, 3739–3744. 57. Chalmers, Z.R., Connelly, C.F., Fabrizio, D., Gay, L., Ali, S.M., Ennis, R., Schrock, A., Campbell, B., Shlien, A., Chmielecki, J., Huang, F., He, Y., Sun, J., Tabori, U., Kennedy, M., Lieber, D.S., Roels, S., White, J., Otto, G.A., Ross, J.S., Garraway, L., Miller, V.A., Stephens, P.J., and Frampton, G.M. (2017) Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational bur den, Genome Med., 9, 34. 58. Wood, L.D., Parsons, D.W., Jones, S., Lin, J., Sjoblom, T., Leary, R.J., Shen, D., Boca, S.M., Barber, T., Ptak, J., Silliman, N., Szabo, S., Dezso, Z., Ustyanksky, V., Nikolskaya, T., Nikolsky, Y., Karchin, R., Wilson, P.A., Kaminker, J.S., Zhang, Z., Croshaw, R., Willis, J., Dawson, D., Shipitsin, M., Willson, J.K., Sukumar, S., Polyak, K., Park, B.H., Pethiyagoda, C.L., Pant, P.V., Ballinger, D.G., Sparks, A.B., Hartigan, J., Smith, D.R., Suh, E., Papadopoulos, N., Buckhaults, P., Markowitz, S.D., Parmigiani, G., Kinzler, K.W., Velculescu, V.E., and Vogelstein, B. (2007) The genomic landscapes of human breast and colorectal cancers, Science, 318, 1108–1113. 59. Easwaran, H., Tsai, H.C., and Baylin, S.B. (2014) Cancer epigenetics: tumor heterogeneity, plasticity of stem like states, and drug resistance, Mol. Cell, 54, 716–727. 60. Pribluda, A., De la Cruz, C.C., and Jackson, E.L. (2015) Intratumoral heterogeneity: from diversity comes resis tance, Clin. Cancer Res., 21, 2916–2923. 61. Kaiser, J. (2009) Cancer research. Looking for a target on every tumor, Science, 326, 218–220. 62. Mallick, P (2015) in Cancer as a Multi Scale Complex Adaptive System Physical Sciences and Engineering Advances in Life Sciences and Oncology (Janmey, P., Fletcher, D., Gerecht, S., Levine, R., Mallick, P., McCarty, O., Munn, L., and Reinhart King, C., eds) Springer International Publishing, pp. 5–29. 63. Rickles, D., Hawe, P., and Shiell, A. (2007) A simple guide to chaos and complexity, J. Epid. Com. Health, 61, 933–937. 64. Suki, B., Bates, J.H., and Frey, U. (2011) Complexity and emergent phenomena, Compr. Physiol., 1, 995–1029. 65. Noble, D. (2013) A biological relativity view of the rela tionships between genomes and phenotypes, Prog. Biophys. Mol. Biol., 111, 59–65. 66. Korn, R. (2005) The emergence principle in biological hierarchies, Biol. Phil., 20, 137–151. 67. Van Regenmortel, M.H. (2004) Reductionism and com plexity in molecular biology. Scientists now have the tools to unravel biological and overcome the limitations of reductionism, EMBO Rep., 5, 1016–1020. 68. Greek, R., and Hansen, L.A. (2013) Questions regarding the predictive value of one evolved complex adaptive sys tem for a second: exemplified by the SOD1 mouse, Prog. Biophys. Mol. Biol., 113, 231–253. 69. Janson, N. (2012) Non l inear dynamics of biological sys tems, Contemporary Physics, 53, 137–168. НЕРЕШАЕМЫЕ ПРОБЛЕМЫ БИОЛОГИИ БИОХИМИЯ том 83 вып. 4 2018 527 70. Greek, R., and Menache, A. (2013) Systematic reviews of animal models: methodology versus epistemology, Int. J. Med. Sci., 10, 206–221. 71. Merlo, L.M., Pepper, J.W., Reid, B.J., and Maley, C.C. (2006) Cancer as an evolutionary and ecological process, Nat. Rev. Cancer, 6, 924–935. 72. Hanahan, D., and Weinberg, R.A. (2011) Hallmarks of cancer: the next generation, Cell, 144, 646–674. 73. Bissell, M.J., and Hines, W.C. (2011) Why don’t we get more cancer? A proposed role of the microenvironment in restraining cancer progression, Nat. Med., 17, 320–329. 74. Bordon, Y. (2015) Immunotherapy: checkpoint parley, Nat. Rev. Cancer, 15, 3. 75. Smyth, M.J., Ngiow, S.F., Ribas, A., and Teng, M.W. (2016) Combination cancer immunotherapies tailored to the tu mour microenvironment, Nat. Rev. Clin. Oncol., 13, 143–158. 76. Park, J., Kwon, M., and Shin, E.C. (2016) Immune check point inhibitors for cancer treatment, Arch. Pharm. Res., 39, 1577–1587. 77. Postow, M.A., Callahan, M.K., and Wolchok, J.D. (2015) Immune checkpoint blockade in cancer therapy, J. Clin. Oncol., 33, 1974–1982. 78. Diesendruck, Y., and Benhar, I. (2017) Novel immune check point inhibiting antibodies in cancer therapy oppor tunities and challenges, Drug Resist. Updat., 30, 39–47. 79. Vreeland, T., Clifton, G., Herbert, G., Hale, D., Jackson, D., Berry, J., and Peoples, G. (2016) Gaining ground on a cure through synergy: combining checkpoint inhibitors with cancer vaccines, Exp. Rev. Clin. Immunol., 12, 1347–1357. 80. Calabrese, L., and Velcheti, V. (2017) Checkpoint immunotherapy: good for cancer therapy, bad for rheumatic diseases, Ann. Rheum. Dis., 76, 1–3. 81. Postow, M., and Wolchok, J. (2016) Toxicities associated with checkpoint inhibitor immunotherapy, Wolters Kluwer. 82. Consortium, E. P. (2012) An integrated encyclopedia of DNA elements in the human genome, Nature, 489, 57–74. 83. Alberts, B. (2012) The end of «small science»? Science, 337, 1583. 84. Evans, J.P., Meslin, E.M., Marteau, T.M., and Caulfield, T. (2011) Genomics. Deflating the genomic bubble, Science, 331, 861–862. 85. Graur, D. (2016) Rubbish DNA: the functionless fraction of the human genome, arXiv:1601.06047v1 [q bio.GN]. 86. Graur, D., Zheng, Y., and Azevedo, R.B. (2015) An evolu tionary classification of genomic function, Genome Biol. Evol., 7, 642–645. 87. Doolittle, W.F., Brunet, T.D., Linquist, S., and Gregory, T.R. (2014) Distinguishing between «function» and «effect» in genome biology, Genome Biol. Evol., 6, 1234–1237. 88. Graur, D., Zheng, Y., Price, N., Azevedo, R.B., Zufall, R.A., and Elhaik, E. (2013) On the immortality of television sets: «function» in the human genome according to the evolu tion free gospel of ENCODE, Genome Biol. Evol., 5, 578–590. 89. Graur, D. (2017) An upper limit on the functional fraction of the human genome, Genome Biol. Evol., 9, 1880–1885. 90. Brunet, T.D., and Doolittle, W.F. (2014) Getting «func tion» right, Proc. Natl. Acad. Sci. USA, 111, E3365. 91. Nei, M. (2005) Selectionism and neutralism in molecular evolution, Mol. Biol. Evol., 22, 2318–2342. 92. Rands, C.M., Meader, S., Ponting, C.P., and Lunter, G. (2014) 8,2% of the нuman genome is constrained: variation in rates of turnover across functional element classes in the human lineage, PLoS Genet., 10, e1004525. 93. Brenner, S. (2010) Sequences and consequences, Philos Trans. R. Soc. Lond. B Biol. Sci., 365, 207–212. 94. Свердлов Е. (2006) Биологический редукционизм ухо дит? Что дальше? Вест. Рос. Акад. Наук, 76, 707–721. 95. Blanco Gomez, A., Castillo Lluva, S., Del Mar Saez Freire, M., Hontecillas Prieto, L., Mao, J.H., Castel lanos Martin, A., and Perez Losada, J. (2016) Missing heritability of complex diseases: enlightenment by genetic variants from intermediate phenotypes, Bioessays, 38, 664–673. 96. Gottesman, I., and McGue, M. (2015) Endophenotypes, JohnWiley & Sons, Inc. 97. Te Pas, M.F., Madsen, O., Calus, M.P., and Smits, M.A. (2017) The importance of endophenotypes to evaluate the relationship between genotype and external Phenotype, Int. J. Mol. Sci., 18, E472. UNSOLVABLE PROBLEMS OF BIOLOGY: IT IS IMPOSSIBLE TO CREATE TWO IDENTICAL ORGANISMS, TO DEFEAT CANCER, AND TO MAP ORGANISMS ONTO THEIR GENOMES E. D. Sverdlov Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia; E mail: edsverd@gmail.com Revision received November 12, 2017 This review points to the existence of three categories of unsolvable biological problems: 1) Unsolvable problems due to stochastic mutations during DNA replication that result in the impossibility of creating two identical organisms or even two identical complex cells (Sverdlov, E. D., Biochemistry (Moscow), 74, 939 944) and to the inability to «defeat» cancer; 2) Problems that cannot be resolved due to multiple interactions in complex systems that lead to unpredictable «emergent» properties that make it impossible to establish unambiguous relationships between the genetic architec ture of the genome and its phenotypic manifestation, and to predict with certainty the response of the organism, its parts, or pathological processes to the external impact; 3) Problems that cannot be solved because of the uncertainty principle and observer effect in biology, due to which it is impossible to obtain adequate information about the cells in their tissue microenvironment by isolating and analyzing single cells. In particular, it is impossible to draw conclu sions on the properties of stem cells in their niches through the properties of stem cell cultures. A strategy is proposed for constructing the pattern most closely approximated to the relationship of genotypes to their phenotypes by designing networks of intermediate phenotypes (endophenotypes). Keywords: stochastic mutations, emerging properties, heterogeneity, biological uncertainty principle, phenotype, genotype, selected function |