Collective T cell Migration within a 3D printed Immunotherapy Model

Introducing tumor RNA to T cell populations primes the immune cells to identify elusive cancers. Despite the increasing efficacy of this immunotherapeutic approach in the mouse model, the underlying mechanisms behind the ability of T cells to identify and target tumors is still being investigated. In order to systematically study the interactions of these two cell populations, we employ a method of 3D bioprinting into a bed of jammed microgels where we have control over the spatial relationship between the two cell types. With this capability, we can identify key time and lengthscales at which the T cells identify the tumor presence and generate a collective immune response. Data on the temporal evolution of T cells targeting the tumor will be shown, in which biased motion toward the tumor correlates with a diffusion time for cytokines to leave the tumor and trigger T cell targeting. By varying this spatiotemporal relationship, we determine the diffusion coefficient of this cytokine signaling response, enabling better predictive models for this immunotherapy. Furthermore, we will show indirect identification of the cytokine source and gene expression changes within the tumor cell populations that highlight their attempts at immune evasion.