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首页> 外文期刊>Journal of biomolecular screening: The official journal of the Society for Biomolecular Screening >Development of a 3D Tissue Culture-Based High-Content Screening Platform That Uses Phenotypic Profiling to Discriminate Selective Inhibitors of Receptor Tyrosine Kinases
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Development of a 3D Tissue Culture-Based High-Content Screening Platform That Uses Phenotypic Profiling to Discriminate Selective Inhibitors of Receptor Tyrosine Kinases

机译:基于3D组织文化的高内涵筛选平台的开发,该平台使用表型分析来区分受体酪氨酸激酶的选择性抑制剂。

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3D tissue cultures provide a more physiologically relevant context for the screening of compounds, compared with 2D cell cultures. Cells cultured in 3D hydrogels also show complex phenotypes, increasing the scope for phenotypic profiling. Here we describe a high-content screening platform that uses invasive human prostate cancer cells cultured in 3D in standard 384-well assay plates to study the activity of potential therapeutic small molecules and antibody biologics. Image analysis tools were developed to process 3D image data to measure over 800 phenotypic parameters. Multiparametric analysis was used to evaluate the effect of compounds on tissue morphology. We applied this screening platform to measure the activity and selectivity of inhibitors of the c-Met and epidermal growth factor (EGF) receptor (EGFR) tyrosine kinases in 3D cultured prostate carcinoma cells. c-Met and EGFR activity was quantified based on the phenotypic profiles induced by their respective ligands, hepatocyte growth factor and EGF. The screening method was applied to a novel collection of 80 putative inhibitors of c-Met and EGFR. Compounds were identified that induced phenotypic profiles indicative of selective inhibition of c-Met, EGFR, or bispecific inhibition of both targets. In conclusion, we describe a fully scalable high-content screening platform that uses phenotypic profiling to discriminate selective and nonselective (off-target) inhibitors in a physiologically relevant 3D cell culture setting.
机译:与2D细胞培养相比,3D组织培养提供了更生理相关的化合物筛选背景。在3D水凝胶中培养的细胞也显示出复杂的表型,从而扩大了表型分析的范围。在这里,我们描述了一个高内涵的筛选平台,该平台使用在标准384孔测定板中以3D培养的侵入性人类前列腺癌细胞来研究潜在的治疗性小分子和抗体生物制剂的活性。开发了图像分析工具来处理3D图像数据,以测量800多个表型参数。使用多参数分析来评估化合物对组织形态的影响。我们应用了该筛选平台来测量3D培养的前列腺癌细胞中c-Met和表皮生长因子(EGF)受体(EGFR)酪氨酸激酶抑制剂的活性和选择性。基于各自配体,肝细胞生长因子和EGF诱导的表型,对c-Met和EGFR活性进行了定量。筛选方法应用于80种推定的c-Met和EGFR抑制剂的新收集物中。鉴定出诱导表型特征的化合物,其指示对c-Met,EGFR的选择性抑制或对两个靶标的双特异性抑制。总之,我们描述了一个完全可扩展的高内涵筛选平台,该平台使用表型分析来区分生理相关3D细胞培养环境中的选择性和非选择性(脱靶)抑制剂。

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