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支架支持的 3D 组织阵列高通量制造和分析的自动化工作流程。

An Automation Workflow for High-Throughput Manufacturing and Analysis of Scaffold-Supported 3D Tissue Arrays.

机构信息

Institute of Biomedical Engineering, University of Toronto, 164 College Street, Toronto, ON, M5S 3G9, Canada.

Department of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College Street, Toronto, ON, M5R 3S5, Canada.

出版信息

Adv Healthc Mater. 2023 Jul;12(19):e2202422. doi: 10.1002/adhm.202202422. Epub 2023 May 10.

Abstract

Patient-derived organoids have emerged as a useful tool to model tumour heterogeneity. Scaling these complex culture models while enabling stratified analysis of different cellular sub-populations, however, remains a challenge. One strategy to enable higher throughput organoid cultures is the scaffold-supported platform for organoid-based tissues (SPOT). SPOT allows the generation of flat, thin, and dimensionally-defined microtissues in both 96- and 384-well plate footprints that are compatible with longitudinal image-based readouts. SPOT is currently manufactured manually, however, limiting scalability. In this study, an automation approach to engineer tumour-mimetic 3D microtissues in SPOT using a liquid handler is optimized and comparable within- and between-sample variation to standard manual manufacturing is shown. Further, a liquid handler-supported cell extraction protocol to support single-cell-based end-point analysis using high-throughput flow cytometry and multiplexed cytometry by time of flight is developed. As a proof-of-value demonstration, 3D complex tissues containing different proportions of tumour and stromal cells are generated to probe the reciprocal impact of co-culture. It is also demonstrated that primary patient-derived organoids can be incorporated into the pipeline to capture patient-level tumour heterogeneity. It is envisioned that this automated 96/384-SPOT workflow will provide opportunities for future applications in high-throughput screening for novel personalized therapeutic targets.

摘要

患者来源的类器官已成为模拟肿瘤异质性的有用工具。然而,扩大这些复杂的培养模型规模,同时实现不同细胞亚群的分层分析仍然是一个挑战。一种能够实现更高通量类器官培养的策略是基于类器官的组织支架支持平台(SPOT)。SPOT 允许在 96 孔和 384 孔板足迹中生成扁平、薄且具有尺寸定义的微组织,这些微组织与基于图像的纵向读出兼容。然而,SPOT 目前是手动制造的,限制了其可扩展性。在这项研究中,使用液体处理机优化了一种用于在 SPOT 中构建肿瘤模拟 3D 微组织的自动化方法,并显示了与标准手动制造相当的样本内和样本间变异性。此外,开发了一种液体处理机支持的细胞提取方案,以支持使用高通量流式细胞术和飞行时间的多重化细胞术进行单细胞终点分析。作为价值验证演示,生成了含有不同比例肿瘤细胞和基质细胞的 3D 复杂组织,以探究共培养的相互影响。还证明可以将原代患者来源的类器官纳入该方案,以捕获患者水平的肿瘤异质性。可以预见,这种自动化的 96/384-SPOT 工作流程将为未来在高通量筛选新型个性化治疗靶点方面的应用提供机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/420c/11468893/8064bca6fdde/ADHM-12-2202422-g003.jpg

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