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Intra-tumor heterogeneity, turnover rate and karyotype space shape susceptibility to missegregation-induced extinction.
Kimmel, Gregory J; Beck, Richard J; Yu, Xiaoqing; Veith, Thomas; Bakhoum, Samuel; Altrock, Philipp M; Andor, Noemi.
Afiliação
  • Kimmel GJ; H. Lee Moffitt Cancer Center & Research Institute, Integrated Mathematical Oncology, Tampa, Florida.
  • Beck RJ; H. Lee Moffitt Cancer Center & Research Institute, Integrated Mathematical Oncology, Tampa, Florida.
  • Yu X; H. Lee Moffitt Cancer Center & Research Institute, Biostatistics & Bioinformatics, Tampa, Florida.
  • Veith T; H. Lee Moffitt Cancer Center & Research Institute, Integrated Mathematical Oncology, Tampa, Florida.
  • Bakhoum S; Memorial Sloan Kettering Cancer Center, Human Oncology & Pathogenesis Program, New York City, New York.
  • Altrock PM; Max Planck Institute for Evolutionary Biology, Department for Evolutionary Theory, Plön, Germany.
  • Andor N; H. Lee Moffitt Cancer Center & Research Institute, Integrated Mathematical Oncology, Tampa, Florida.
PLoS Comput Biol ; 19(1): e1010815, 2023 01.
Article em En | MEDLINE | ID: mdl-36689467
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Instabilidade Cromossômica / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Instabilidade Cromossômica / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article