Intratumor heterogeneity: models of malignancy emergence and evolution

Author:

Ivanov R. A.1ORCID,Lashin S. A.2ORCID

Affiliation:

1. Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences

2. Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Novosibirsk State University

Abstract

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.

Publisher

Institute of Cytology and Genetics, SB RAS

Subject

General Biochemistry, Genetics and Molecular Biology,General Agricultural and Biological Sciences

Reference37 articles.

1. Augustin R.C., Delgoffe G.M., Najjar Y.G. Characteristics of the tumor microenvironment that influence immune cell functions: hypoxia, oxidative stress, metabolic alterations. Cancers (Basel). 2020; 12(12):3802. DOI 10.3390/cancers12123802

2. Baca S.C., Prandi D., Lawrence M.S., Mosquera J.M., Romanel A., Drier Y., Park K., Kitabayashi N., MacDonald T.Y., Ghandi M., Van Allen E., Kryukov G.V., Sboner A., Theurillat J.-P., Soong T.D., Nickerson E., Auclair D., Tewari A., Beltran H., Onofrio R.C., Boysen G., Guiducci C., Barbieri C.E., Cibulskis K., Sivachenko A., Carter S.L., Saksena G., Voet D., Ramos A.H., Winckler W., Cipicchio M., Ardlie K., Kantoff P.W., Berger M.F., Gabriel S.B., Golub T.R., Meyerson M., Lander E.S., Elemento O., Getz G., Demichelis F., Rubin M.A., Garraway L.A. Punctuated evolution of prostate cancer genomes. Cell. 2013;153(3):666-677. DOI 10.1016/j.cell.2013.03.021

3. Besse A., Clapp G.D., Bernard S., Nicolini F.E., Levy D., Lepoutre T. Stability analysis of a model of interaction between the immune system and cancer cells in chronic myelogenous leukemia. Bull. Math. Biol. 2018;80(5):1084-1110. DOI 10.1007/s11538-017-0272-7

4. Bonnet D., Dick J.E. Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat. Med. 1997;3(7):730-737. DOI 10.1038/nm0797-730

5. Deng G., Zhang X., Chen Y., Liang S., Liu S., Yu Z., Lü M. Singlecell transcriptome sequencing reveals heterogeneity of gastric cancer: progress and prospects. Front. Oncol. 2023;13:1074268. DOI 10.3389/fonc.2023.1074268

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