Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Instituto de Investigaciones Biomédicas Sols-Morreale (IIBM), CSIC-UAM, Madrid, Spain.
Nat Protoc. 2024 Jul;19(7):2052-2084. doi: 10.1038/s41596-024-00972-6. Epub 2024 Mar 19.
Modeling immuno-oncology by using patient-derived material and immune cell co-cultures can advance our understanding of immune cell tumor targeting in a patient-specific manner, offering leads to improve cellular immunotherapy. However, fully exploiting these living cultures requires analysis of the dynamic cellular features modeled, for which protocols are currently limited. Here, we describe the application of BEHAV3D, a platform that implements multi-color live 3D imaging and computational tools for: (i) analyzing tumor death dynamics at both single-organoid or cell and population levels, (ii) classifying T cell behavior and (iii) producing data-informed 3D images and videos for visual inspection and further insight into obtained results. Together, this enables a refined assessment of how solid and liquid tumors respond to cellular immunotherapy, critically capturing both inter- and intratumoral heterogeneity in treatment response. In addition, BEHAV3D uncovers T cell behavior involved in tumor targeting, offering insight into their mode of action. Our pipeline thereby has strong implications for comparing, prioritizing and improving immunotherapy products by highlighting the behavioral differences between individual tumor donors, distinct T cell therapy concepts or subpopulations. The protocol describes critical wet lab steps, including co-culture preparations and fast 3D imaging with live cell dyes, a segmentation-based image processing tool to track individual organoids, tumor and immune cells and an analytical pipeline for behavioral profiling. This 1-week protocol, accessible to users with basic cell culture, imaging and programming expertise, can easily be adapted to any type of co-culture to visualize and exploit cell behavior, having far-reaching implications for the immuno-oncology field and beyond.
利用患者来源的材料和免疫细胞共培养物来模拟免疫肿瘤学,可以以患者特异性的方式推进我们对免疫细胞肿瘤靶向的理解,为改善细胞免疫疗法提供线索。然而,充分利用这些活体培养物需要分析建模的动态细胞特征,而目前这方面的方案有限。在这里,我们描述了 BEHAV3D 的应用,该平台实施多色活 3D 成像和计算工具,用于:(i)分析单个类器官或细胞和群体水平的肿瘤死亡动力学,(ii)分类 T 细胞行为,(iii)生成数据驱动的 3D 图像和视频,用于视觉检查和进一步深入了解获得的结果。总之,这可以更精细地评估实体瘤和液体瘤对细胞免疫疗法的反应,关键是在治疗反应中捕捉到肿瘤内和肿瘤间的异质性。此外,BEHAV3D 揭示了参与肿瘤靶向的 T 细胞行为,为了解其作用模式提供了线索。我们的方法对比较、优先考虑和改进免疫疗法产品具有重要意义,突出了个体肿瘤供体、不同的 T 细胞治疗概念或亚群之间的行为差异。该方案描述了关键的湿实验室步骤,包括共培养物的准备和使用活细胞染料的快速 3D 成像、基于分割的图像处理工具来跟踪单个类器官、肿瘤和免疫细胞,以及用于行为分析的分析管道。这个为期 1 周的方案,对具有基本细胞培养、成像和编程专业知识的用户来说是容易访问的,可以轻松地适应任何类型的共培养物,以可视化和利用细胞行为,对免疫肿瘤学领域及其他领域具有深远的影响。