BEHAV3D: a 3D live imaging platform for comprehensive analysis of engineered T cell behavior and tumor response

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. BEHAV3D is a 3D live imaging platform for analyzing engineered T cell behavior and tumor response. This provides insights into the mode of action of cellular immunotherapy, capturing heterogeneity within and between tumors during treatment response.