H. Lee Moffitt Cancer Center & Research Institute, Integrated Mathematical Oncology, Tampa, Florida.
H. Lee Moffitt Cancer Center & Research Institute, Biostatistics & Bioinformatics, Tampa, Florida.
PLoS Comput Biol. 2023 Jan 23;19(1):e1010815. doi: 10.1371/journal.pcbi.1010815. eCollection 2023 Jan.
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.
体细胞拷贝数改变(SCNAs)的表型功效源于其在基因组每个碱基对中的发生率,这比点突变的发生率要高出几个数量级。有一个有丝分裂事件因其有可能显著改变细胞的 SCNAs 负担而引人注目——染色体错分。以前已经开发了一种用于描述单个染色体类型的 SCNAs 演变的染色体错分的随机模型。在此基础上,我们推导出了一种用于对多种染色体类型的错分进行建模的一般确定性框架。该框架具有灵活性,可以对所有染色体的 SCNAs 以及错分和周转率中的肿瘤内异质性进行建模。该模型可用于测试选择如何在数百代中对共存的核型起作用。我们使用该模型计算由错分引起的种群灭绝(MIE)曲线,该曲线将具有周转率和错分率的可行种群与不可行种群分开。然后将从 scRNA-seq 数据估计的周转率和错分率与理论预测进行比较。我们发现,无论是在 MIE 曲线的位置还是在 MIE 的必要条件方面,理论和经验结果都趋于一致。当引入错分率与核型的依赖性时,与低错分率相关的核型充当稳定的避难所,除非周转率极高,否则 MIE 是不可能的。随着肿瘤的进展,肿瘤内异质性(包括错分率的异质性)增加,使得 MIE 不太可能发生。