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


Authors: Kimmel, G. J.; Beck, R. J.; Yu, X.; Veith, T.; Bakhoum, S.; Altrock, P. M.; Andor, N.
Article Title: Intra-tumor heterogeneity, turnover rate and karyotype space shape susceptibility to missegregation-induced extinction
Abstract: 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 missegregations 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. Turnoverand 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. © 2023 Kimmel et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Keywords: genetics; neoplasm; neoplasms; gene amplification; prediction; tumors; chromosomal instability; karyotype; karyotyping; chromosomes; theoretical study; dna copy number variations; copy number variation; stochastic models; tumor heterogeneity; point mutations; base pairs; copy-number alterations; orders of magnitude; humans; human; article; stochastic systems; single cell rna seq; turnover rate; segregation (metallography); deterministics; extinction curves; mitotic events; stochastic-modeling
Journal Title: PLoS Computational Biology
Volume: 19
Issue: 1
ISSN: 1553-7358
Publisher: Public Library of Science  
Date Published: 2023-01-01
Start Page: e1010815
Language: English
DOI: 10.1371/journal.pcbi.1010815
PUBMED: 36689467
PROVIDER: scopus
PMCID: PMC9917311
DOI/URL:
Notes: Article -- Export Date: 1 March 2023 -- Source: Scopus
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  1. Samuel F Bakhoum
    81 Bakhoum