Nephrology Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States of America.
Harvard Medical School, Boston, MA, United States of America.
Biofabrication. 2024 Apr 8;16(3). doi: 10.1088/1758-5090/ad38df.
High-throughput drug screening is crucial for advancing healthcare through drug discovery. However, a significant limitation arises from availablemodels using conventional 2D cell culture, which lack the proper phenotypes and architectures observed in three-dimensional (3D) tissues. Recent advancements in stem cell biology have facilitated the generation of organoids-3D tissue constructs that mimic human organs. Kidney organoids, derived from human pluripotent stem cells, represent a significant breakthrough in disease representation. They encompass major kidney cell types organized within distinct nephron segments, surrounded by stroma and endothelial cells. This tissue allows for the assessment of structural alterations such as nephron loss, a characteristic of chronic kidney disease. Despite these advantages, the complexity of 3D structures has hindered the use of organoids for large-scale drug screening, and the drug screening pipelines utilizing these complexmodels remain to be established for high-throughput screening. In this study, we address the technical limitations of kidney organoids through fully automated 3D imaging, aided by a machine-learning approach for automatic profiling of nephron segment-specific epithelial morphometry. Kidney organoids were exposed to the nephrotoxic agent cisplatin to model severe acute kidney injury. An U.S. Food and Drug Administration (FDA)-approved drug library was tested for therapeutic and nephrotoxicity screening. The fully automated pipeline of 3D image acquisition and analysis identified nephrotoxic or therapeutic drugs during cisplatin chemotherapy. The nephrotoxic potential of these drugs aligned with previousand human reports. Additionally, Imatinib, a tyrosine kinase inhibitor used in hematological malignancies, was identified as a potential preventive therapy for cisplatin-induced kidney injury. Our proof-of-concept report demonstrates that the automated screening process, using 3D morphometric assays with kidney organoids, enables high-throughput screening for nephrotoxicity and therapeutic assessment in 3D tissue constructs.
高通量药物筛选对于通过药物发现推进医疗保健至关重要。然而,由于传统的二维细胞培养可用模型缺乏在三维(3D)组织中观察到的适当表型和结构,因此存在重大限制。干细胞生物学的最新进展促进了类器官的产生——模拟人体器官的 3D 组织构建体。源自人类多能干细胞的肾类器官代表了疾病表现的重大突破。它们包含组织在不同肾单位段内的主要肾细胞类型,并被基质和内皮细胞包围。这种组织允许评估结构改变,如肾单位丢失,这是慢性肾脏病的特征。尽管有这些优势,但 3D 结构的复杂性阻碍了类器官在大规模药物筛选中的应用,并且利用这些复杂模型进行高通量筛选的药物筛选管道仍有待建立。在这项研究中,我们通过全自动 3D 成像解决了肾类器官的技术限制,该成像得到了机器学习方法的辅助,用于自动分析肾单位段特异性上皮形态计量学。肾类器官暴露于肾毒性药物顺铂中,以模拟严重急性肾损伤。测试了美国食品和药物管理局 (FDA) 批准的药物库,以进行治疗和肾毒性筛选。全自动 3D 图像采集和分析流水线在顺铂化疗期间识别出肾毒性或治疗性药物。这些药物的肾毒性潜力与之前的和人类报告一致。此外,伊马替尼,一种用于血液恶性肿瘤的酪氨酸激酶抑制剂,被确定为顺铂诱导的肾损伤的潜在预防治疗药物。我们的概念验证报告表明,使用肾类器官的 3D 形态计量学测定的自动筛选过程能够在 3D 组织构建体中进行高通量的肾毒性筛选和治疗评估。