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微阵列嵌入/切片用于 3D 细胞球体的平行分析。

Microarray Embedding/Sectioning for Parallel Analysis of 3D Cell Spheroids.

机构信息

Department of Mechanical Engineering, Rowan University, Glassboro, NJ, USA.

Department of Biomedical Engineering, Rowan University, Glassboro, NJ, USA.

出版信息

Sci Rep. 2019 Nov 8;9(1):16287. doi: 10.1038/s41598-019-52007-w.

Abstract

Three-dimensional cell spheroid models can be used to predict the effect of drugs and therapeutics and to model tissue development and regeneration. The utility of these models is enhanced by high throughput 3D spheroid culture technologies allowing researchers to efficiently culture numerous spheroids under varied experimental conditions. Detailed analysis of high throughput spheroid culture is much less efficient and generally limited to narrow outputs, such as metabolic viability. We describe a microarray approach that makes traditional histological embedding/sectioning/staining feasible for large 3D cell spheroid sample sets. Detailed methodology to apply this technology is provided. Analysis of the technique validates the potential for efficient histological analysis of up to 96 spheroids in parallel. By integrating high throughput 3D spheroid culture technologies with advanced immunohistochemical techniques, this approach will allow researchers to efficiently probe expression of multiple biomarkers with spatial localization within 3D structures. Quantitative comparison of staining will have improved inter- and intra-experimental reproducibility as multiple samples are collectively processed, stained, and imaged on a single slide.

摘要

三维细胞球体模型可用于预测药物和治疗方法的效果,并模拟组织发育和再生。通过高通量 3D 球体培养技术,可以高效地在各种实验条件下培养大量球体,从而提高了这些模型的实用性。高通量球体培养的详细分析效率要低得多,通常仅限于狭窄的输出,例如代谢活力。我们描述了一种微阵列方法,该方法使传统的组织学包埋/切片/染色技术适用于大型 3D 细胞球体样本集。提供了应用该技术的详细方法。该技术的分析验证了在平行条件下对多达 96 个球体进行高效组织学分析的潜力。通过将高通量 3D 球体培养技术与先进的免疫组织化学技术相结合,该方法将使研究人员能够高效地探测多个生物标志物在 3D 结构内的空间定位表达。由于对多个样本进行了集体处理、染色和在单个载玻片上成像,因此对染色的定量比较将提高实验内和实验间的可重复性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd82/6841729/ce99a0661917/41598_2019_52007_Fig1_HTML.jpg

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