Krausz Eberhard, de Hoogt Ronald, Gustin Emmanuel, Cornelissen Frans, Grand-Perret Thierry, Janssen Lut, Vloemans Nele, Wuyts Dirk, Frans Sandy, Axel Amy, Peeters Pieter Johan, Hall Brett, Cik Miroslav
Janssen R&D, a Division of Janssen Pharmaceutica NV, Beerse, Belgium.
J Biomol Screen. 2013 Jan;18(1):54-66. doi: 10.1177/1087057112456874. Epub 2012 Aug 24.
For drug discovery, cell-based assays are becoming increasingly complex to mimic more realistically the nature of biological processes and their diversifications in diseases. Multicellular co-cultures embedded in a three-dimensional (3D) matrix have been explored in oncology to more closely approximate the physiology of the human tumor microenvironment. High-content analysis is the ideal technology to characterize these complex biological systems, although running such complex assays at higher throughput is a major endeavor. Here, we report on adapting a 3D tumor co-culture growth assay to automated microscopy, and we compare various imaging platforms (confocal vs. nonconfocal) with correlating automated image analysis solutions to identify optimal conditions and settings for future larger scaled screening campaigns. The optimized protocol has been validated in repeated runs where established anticancer drugs have been evaluated for performance in this innovative assay.
在药物研发中，基于细胞的检测方法正变得越来越复杂，以便更逼真地模拟生物过程的本质及其在疾病中的多样性。三维（3D）基质中嵌入的多细胞共培养已在肿瘤学领域得到探索，以更接近人类肿瘤微环境的生理学特征。高内涵分析是表征这些复杂生物系统的理想技术，尽管以更高通量运行此类复杂检测是一项重大挑战。在此，我们报告了将3D肿瘤共培养生长检测方法应用于自动显微镜，并比较了各种成像平台（共聚焦与非共聚焦）以及相关的自动图像分析解决方案，以确定未来更大规模筛选活动的最佳条件和设置。经过优化的方案已在重复实验中得到验证，在此类创新检测中对已有的抗癌药物的性能进行了评估。
