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Patterns of basal signaling heterogeneity can distinguish cellular populations with different drug sensitivities

机译:基础信号异质性的模式可以区分具有不同药物敏感性的细胞群

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摘要

Phenotypic heterogeneity has been widely observed in cellular populations. However, the extent to which heterogeneity contains biologically or clinically important information is not well understood. Here, we investigated whether patterns of basal signaling heterogeneity, in untreated cancer cell populations, could distinguish cellular populations with different drug sensitivities. We modeled cellular heterogeneity as a mixture of stereotyped signaling states, identified based on colocalization patterns of activated signaling molecules from microscopy images. We found that patterns of heterogeneity could be used to separate the most sensitive and resistant populations to paclitaxel within a set of H460 lung cancer clones and within the NCI-60 panel of cancer cell lines, but not for a set of less heterogeneous, immortalized noncancer human bronchial epithelial cell (HBEC) clones. Our results suggest that patterns of signaling heterogeneity, characterized as ensembles of a small number of distinct phenotypic states, can reveal functional differences among cellular populations.
机译:表型异质性已在细胞群体中广泛观察到。但是,对于异质性包含生物学或临床重要信息的程度尚不十分了解。在这里,我们调查了未经处理的癌细胞群中基础信号异质性的模式是否可以区分具有不同药物敏感性的细胞群。我们将细胞异质性建模为定型信号状态的混合物,基于显微镜图像中激活的信号分子的共定位模式进行鉴定。我们发现异质性模式可用于分离一组H460肺癌克隆中以及NCI-60癌细胞系中对紫杉醇最敏感和耐药的种群,但不适用于一组异质性较低,永生化的非癌分子人支气管上皮细胞(HBEC)克隆。我们的结果表明,信号异质性的模式(以少量不同表型状态的集合为特征)可以揭示细胞群体之间的功能差异。

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