Mathematical Modeling of Clonal Interference by Density-Dependent Selection in Heterogeneous Cancer Cell Lines.
Mathematical Modeling of Clonal Interference by Density-Dependent Selection in Heterogeneous Cancer Cell Lines.
复制标题
异质癌细胞系密度依赖选择克隆干扰的数学模型。
DOI：
10.3390/cells12141849
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发表时间：
2023-07-14
期刊：
影响因子：
6
通讯作者：
Andor, Noemi
中科院分区：
文献类型：
--
作者：
Veith, Thomas;Schultz, Andrew;Alahmari, Saeed;Beck, Richard;Johnson, Joseph;Andor, Noemi
关键词：
许多肿瘤细胞系是非整倍体和异质性的，同一细胞系内共存多种核型。核型异质性已被证明表现为表型，从而影响细胞对药物的反应或对培养液中的微小差异的反应。了解如何解释核型异质性表型将有助于在细胞表型在时间上展开之前对其进行洞察。在这里，我们通过将基因表达程序置于表型背景下，重新分析了来自八个胃癌细胞系的单细胞RNA(ScRNA)和scDNA测序数据。使用活细胞成像，我们量化了八种细胞系之间生长速度和接触抑制的差异，并利用这些差异来优先考虑生长速度和携带能力的转录生物标记物。使用这些生物标志物，我们发现在同一细胞系中检测到的多个核型之间的预测生长速度或承载能力存在显著差异。我们使用这些预测来模拟在体外实验中，细胞系的克隆组成将如何根据密度条件发生变化。一旦得到验证，这些模型可以帮助设计实验，通过密度依赖的选择来引导进化。
Many cancer cell lines are aneuploid and heterogeneous, with multiple karyotypes co-existing within the same cell line. Karyotype heterogeneity has been shown to manifest phenotypically, thus affecting how cells respond to drugs or to minor differences in culture media. Knowing how to interpret karyotype heterogeneity phenotypically would give insights into cellular phenotypes before they unfold temporally. Here, we re-analyzed single cell RNA (scRNA) and scDNA sequencing data from eight stomach cancer cell lines by placing gene expression programs into a phenotypic context. Using live cell imaging, we quantified differences in the growth rate and contact inhibition between the eight cell lines and used these differences to prioritize the transcriptomic biomarkers of the growth rate and carrying capacity. Using these biomarkers, we found significant differences in the predicted growth rate or carrying capacity between multiple karyotypes detected within the same cell line. We used these predictions to simulate how the clonal composition of a cell line would change depending on density conditions during in-vitro experiments. Once validated, these models can aid in the design of experiments that steer evolution with density-dependent selection.
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影响因子：
7.7
作者：
Kinsler G;Geiler-Samerotte K;Petrov DA
通讯作者：
Petrov DA
影响因子：
64.8
作者：
Chen, Guangbo;Bradford, William D.;Seidel, Chris W.;Li, Rong
通讯作者：
Li, Rong
染色体不稳定性通过胞质DNA反应驱动转移。
影响因子：
64.8
作者：
Bakhoum SF;Ngo B;Laughney AM;Cavallo JA;Murphy CJ;Ly P;Shah P;Sriram RK;Watkins TBK;Taunk NK;Duran M;Pauli C;Shaw C;Chadalavada K;Rajasekhar VK;Genovese G;Venkatesan S;Birkbak NJ;McGranahan N;Lundquist M;LaPlant Q;Healey JH;Elemento O;Chung CH;Lee NY;Imielenski M;Nanjangud G;Pe'er D;Cleveland DW;Powell SN;Lammerding J;Swanton C;Cantley LC
通讯作者：
Cantley LC
影响因子：
--
作者：
Aubry M;de Tayrac M;Etcheverry A;Clavreul A;Saikali S;Menei P;Mosser J
通讯作者：
Mosser J
影响因子：
8
作者：
Li, Bailiang;Jiang, Yuming;Li, Ruijiang
通讯作者：
Li, Ruijiang