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An imaging-based platform for high-content, quantitative evaluation of therapeutic response in 3D tumour models

机译:基于影像的平台,可对3D肿瘤模型中的治疗反应进行高内涵,定量评估

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摘要

While it is increasingly recognized that three-dimensional (3D) cell culture models recapitulate drug responses of human cancers with more fidelity than monolayer cultures, a lack of quantitative analysis methods limit their implementation for reliable and routine assessment of emerging therapies. Here, we introduce an approach based on computational analysis of fluorescence image data to provide high-content readouts of dose-dependent cytotoxicity, growth inhibition, treatment-induced architectural changes and size-dependent response in 3D tumour models. We demonstrate this approach in adherent 3D ovarian and pancreatic multiwell extracellular matrix tumour overlays subjected to a panel of clinically relevant cytotoxic modalities and appropriately designed controls for reliable quantification of fluorescence signal. This streamlined methodology reads out the high density of information embedded in 3D culture systems, while maintaining a level of speed and efficiency traditionally achieved with global colorimetric reporters in order to facilitate broader implementation of 3D tumour models in therapeutic screening.
机译:尽管人们越来越认识到,三维(3D)细胞培养模型比单层培养具有更高的保真度来概括人类癌症的药物反应,但缺乏定量分析方法限制了它们对新兴疗法的可靠和常规评估的实施。在这里,我们介绍一种基于荧光图像数据的计算分析的方法,以提供3D肿瘤模型中剂量依赖性细胞毒性,生长抑制,治疗诱导的结构变化和尺寸依赖性反应的高含量读数。我们证明了这种方法在坚持3D卵巢和胰腺多孔细胞外基质肿瘤覆盖物中的临床相关的细胞毒性模式和适当设计的控件,以可靠地量化荧光信号的一组面板。这种简化的方法可以读出嵌入3D培养系统中的信息的高密度,同时保持传统上使用全球比色报告仪所能达到的速度和效率,以促进在治疗筛选中更广泛地实施3D肿瘤模型。

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