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  Intra-tumor heterogeneity, turnover rate and karyotype space shape susceptibility to missegregation-induced extinction

Kimmel, G. J., Beck, R. J., Yu, X., Veith, T., Bakhoum, S., Altrock, P. M., & Andor, N. (2023). Intra-tumor heterogeneity, turnover rate and karyotype space shape susceptibility to missegregation-induced extinction. PLoS Computational Biology, 19(1):. doi:10.1371/journal.pcbi.1010815.

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アイテムのパーマリンク: https://hdl.handle.net/21.11116/0000-000C-A258-A 版のパーマリンク: https://hdl.handle.net/21.11116/0000-000E-9D83-D
資料種別: 学術論文

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journal.pcbi.1010815.pdf (出版社版), 2MB
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https://hdl.handle.net/21.11116/0000-000C-A25A-8
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journal.pcbi.1010815.pdf
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Copyright: © 2023 Kimmel et al.

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 作成者:
Kimmel, Gregory J., 著者
Beck, Richard J., 著者
Yu, Xiaoqing, 著者
Veith, Thomas, 著者
Bakhoum, Samuel, 著者
Altrock, Philipp M.1, 著者                 
Andor, Noemi, 著者
所属:
1Department Evolutionary Theory (Traulsen), Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445641              

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 要旨: The phenotypic efficacy of somatic copy number alterations (SCNAs) stems from their incidence per base pair of the genome, which is orders of magnitudes greater than that of point mutations. One mitotic event stands out in its potential to significantly change a cell’s SCNA burden–a chromosome missegregation. A stochastic model of chromosome mis-segregations has been previously developed to describe the evolution of SCNAs of a single chromosome type. Building upon this work, we derive a general deterministic framework for modeling missegregations of multiple chromosome types. The framework offers flexibility to model intra-tumor heterogeneity in the SCNAs of all chromosomes, as well as in missegregation- and turnover rates. The model can be used to test how selection acts upon coexisting karyotypes over hundreds of generations. We use the model to calculate missegregation-induced population extinction (MIE) curves, that separate viable from non-viable populations as a function of their turnover- and missegregation rates. Turnover- and missegregation rates estimated from scRNA-seq data are then compared to theoretical predictions. We find convergence of theoretical and empirical results in both the location of MIE curves and the necessary conditions for MIE. When a dependency of missegregation rate on karyotype is introduced, karyotypes associated with low missegregation rates act as a stabilizing refuge, rendering MIE impossible unless turnover rates are exceedingly high. Intra-tumor heterogeneity, including heterogeneity in missegregation rates, increases as tumors progress, rendering MIE unlikely.

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言語: eng - English
 日付: 2022-01-282022-12-282023-01-232023
 出版の状態: 出版
 ページ: -
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 査読: 査読あり
 識別子(DOI, ISBNなど): DOI: 10.1371/journal.pcbi.1010815
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出版物 1

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出版物名: PLoS Computational Biology
種別: 学術雑誌
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出版社, 出版地: San Francisco, CA : Public Library of Science
ページ: - 巻号: 19 (1) 通巻号: e1010815 開始・終了ページ: - 識別子(ISBN, ISSN, DOIなど): ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1