Ex Vivo Models to Study the Interaction of Immune Cells and Cancer Cells under Therapy

Recent developments in cancer therapeutics have focused on modulating the immune component of the tumor microenvironment in order to activate anti-tumoral effector functions and induce cytotoxic immune responses. To further advance the design of treatment strategies, it is essential to understand what factors within the tumor microenvironment limit therapeutic efficacy and immune responses. Intravital imaging is a pioneering technology that has been utilized to study these processes in an intact environment(1), successfully highlighting the importance of cancer cell-immune cell interactions such as cancer cell killing caused by longitudinal and repeated interactions with immune cells(2). Despite the clear advantages that intravital imaging provides, its low throughput limits the variety of drugs, genetically altered parameters, and cell-cell interactions that can be studied(3-5). In other fields, a complementary approach has been to turn to ex vivo models which offer greater throughput and simpler experimental protocols(6-8). Here, we describe the setup of an ex vivo technique to study dynamic interactions within an intact environment. This chapter will, in detail, 1) demonstrate strategies to generate fluorescently tagged cancer and immune cells using genetic as well as dye-based approaches; 2) present a method for how to best generate lung metastasis for ex vivo imaging; and 3) describe the protocol to generate precision cut lung metastasis slices; and 4) detail how to prepare them for intravital imaging. This protocol can be utilized for following the effect of therapeutics on tumor growth within the lung microenvironment ex vivo, and on the interaction of cancer cells with immune cells. Ex vivo lung slices are an excellent model to 1) prepare the design of follow on intravital imaging experiments (e.g. determine appropriate fluorophores, drug concentrations, or cell types to label), 2) study immune and cancer cell interactions in a complete environment, 3) select promising drugs from a pool of targets, and 4) select the best timing for intravital imaging experiments.