vavilovВавиловский журнал генетики и селекцииVavilov Journal of Genetics and Breeding2500-3259Institute of Cytology and Genetics of Siberian Branch of the RAS10.18699/VJGB-23-94vavilov-3981Research ArticleЭВОЛЮЦИОННАЯ КОМПЬЮТЕРНАЯ БИОЛОГИЯEVOLUTIONARY COMPUTATIONAL BIOLOGYВнутриопухолевая гетерогенность: модели возникновения и эволюции злокачественных опухолейIntratumor heterogeneity: models of malignancy emergence and evolutionhttps://orcid.org/0000-0002-4369-356XИвановР. А.IvanovR. A.

Новосибирск

Novosibirsk

ivanovromanart@bionet.nsc.ruhttps://orcid.org/0000-0003-3138-381XЛашинС. А.LashinS. A.

Новосибирск

Novosibirsk

Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наукРоссияInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of SciencesRussian FederationФедеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук; Новосибирский национальный исследовательский государственный университетРоссияInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Novosibirsk State UniversityRussian Federation202311122023277815­-819Copyright © Иванов Р.А., Лашин С.А., 20232023Иванов Р.А., Лашин С.А.Ivanov R.A., Lashin S.A.This work is licensed under a Creative Commons Attribution 4.0 License.https://vavilov.elpub.ru/jour/article/view/3981

Рак – сложное и гетерогенное заболевание, характеризующееся накоплением генетических изменений, которые приводят к неконтролируемому росту и пролиферации клеток. Эволюционная динамика играет решающую роль в возникновении и развитии раковых опухолей, формируя гетерогенность и адаптивность раковых клеток. С точки зрения теории эволюции опухоли представляют собой сложные экосистемы, которые развиваются в процессе микроэволюции под воздействием генетических мутаций, эпигенетических изменений и факторов микроокружения опухолей. Такая динамичная природа опухолей создает значительные проблемы для эффективного лечения рака, и ее понимание необходимо для разработки эффективных и персонализированных методов лечения. Раскрывая механизмы, определяющие гетерогенность опухоли, исследователи могут выявить ключевые генетические и эпигенетические изменения, которые способствуют прогрессированию опухоли и устойчивости к лечению. Эти знания позволяют разрабатывать инновационные стратегии воздействия на конкретные клоны опухоли, минимизируя риск рецидива и улучшая результаты лечения пациентов. Для изучения эволюционной динамики рака ученые используют широкий спектр экспериментальных и вычислительных подходов. Традиционные экспериментальные методы включают в себя геномное профилирование, такое как секвенирование нового поколения и флуоресцентная гибридизация in situ, и позволяют выявлять соматические мутации, изменения числа копий генов и структурные перестройки в геномах раковых опухолей. Помимо того, методы одноклеточного секвенирования стали мощным инструментом для изучения внутриопухолевой гетерогенности и отслеживания клональной эволюции. На основании экспериментальных данных разрабатываются вычислительные модели и алгоритмы для моделирования и анализа эволюции рака. Эти модели объединяют данные из различных источников для предсказания закономерностей роста опухоли, выявления драйверных мутаций и построения эволюционных деревьев развития раковых клеток. В настоящей работе мы поставили задачу описать существующие на сегодняшний день подходы к изучению эволюционной динамики развития рака и теории ее возникновения.

 

Cancer is a complex and heterogeneous disease characterized by the accumulation of genetic alterations that drive uncontrolled cell growth and proliferation. Evolutionary dynamics plays a crucial role in the emergence and development of tumors, shaping the heterogeneity and adaptability of cancer cells. From the perspective of evolutionary theory, tumors are complex ecosystems that evolve through a process of microevolution influenced by genetic mutations, epigenetic changes, tumor microenvironment factors, and therapy­induced changes. This dynamic nature of tumors poses significant challenges for effective cancer treatment, and understanding it is essential for developing effective and personalized therapies. By uncovering the mechanisms that determine tumor heterogeneity, researchers can identify key genetic and epigenetic changes that contribute to tumor progression and resistance to treatment. This knowledge enables the development of innovative strategies for targeting specific tumor clones, minimizing the risk of recurrence and improving patient outcomes. To investigate the evolutionary dynamics of cancer, researchers employ a wide range of experimental and computational approaches. Traditional experimental methods involve genomic profiling techniques such as next­generation sequencing and fluorescence in situ hybridization. These techniques enable the identification of somatic mutations, copy number alterations, and structural rearrangements within cancer genomes. Furthermore, single­cell sequencing methods have emerged as powerful tools for dissecting intratumoral heterogeneity and tracing clonal evolution. In parallel, computational models and algorithms have been developed to simulate and analyze cancer evolution. These models integrate data from multiple sources to predict tumor growth patterns, identify driver mutations, and infer evolutionary trajectories. In this paper, we set out to describe the current approaches to address this evolutionary complexity and theories of its occurrence.

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The authors declare that there are no conflicts of interest present.