Detecting Cell Growth and Drug Response in Heterogeneous Populations: A Dynamic Imaging Approach

Chao Sima, Jianping Hua, Rosana Lopes, A. Datta, M. Bittner
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引用次数: 2

Abstract

Tumor heterogeneity has been increasingly recognized as one of the potentially contributing factors in explaining drug resistance. In order to gain better understanding of heterogeneous cancer cell populations and different cells' responses to various drugs, we use fluorescent proteins to mark the cells and a live-cell dynamic imaging platform to collect cell-by-cell measurements. After addressing the issue of fluorescent reporter variance in a Bayesian inference framework, we decompose the different cell types in the mixture and calculate their proportions and counts over time responding to different drug treatments. Additionally, the drug response as characterized by the cell death rate was also computed for these cells, and their different sensitivity was demonstrated. Overall, this work represents an important advancement toward evaluating cancer heterogeneity and drug responses in heterogeneous cancer cell populations.
在异质人群中检测细胞生长和药物反应:一种动态成像方法
肿瘤异质性越来越被认为是解释耐药的潜在因素之一。为了更好地了解异质性癌细胞群和不同细胞对各种药物的反应,我们使用荧光蛋白标记细胞,并使用活细胞动态成像平台收集细胞间的测量数据。在贝叶斯推理框架中解决了荧光报告变量的问题后,我们分解了混合物中的不同细胞类型,并计算了它们随时间对不同药物治疗的反应比例和计数。此外,还计算了这些细胞的以细胞死亡率为特征的药物反应,并证明了它们的不同敏感性。总的来说,这项工作代表了评估异质癌细胞群中癌症异质性和药物反应的重要进展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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