IMMU-63. MESSENGER RNA CHALLENGE PREDICTS CANCER IMMUNOGENICITY AND RESPONSE TO CHECKPOINT INHIBITORS

Abstract BACKGROUND Checkpoint inhibition has emerged as a promising cancer therapeutic approach. Checkpoint inhibitors (CIs) function by overcoming the adaptive T cell exhaustion induced by solid tumor microenvironment including brain tumors, particularly in the neoadjuvant setting. Unfortunately, not every patient who receives CIs will unlock effective antitumor immunity. Objectives: Microsatellite instability and high mutational burden are considered key criteria to predict response to CIs. However, only a minority of patients will fulfill these criteria suggesting the need to develop innovative technologies to identify CI responsive patients. METHODS To determine whether glioma tumors will respond to CIs, we have developed a novel multilamellar mRNA-lipid particle tool to predict response ex vivo. Messenger RNA is complexed into multilamellar lipid particles to form aggregates (RNA-LPAs) to induce pathogen recognition receptor signaling in tumor cells to define an inflammatory profile as an indirect predictor to CI response. RESULTS In naïve mice, we found that multilamellar RNA-LPAs induce activation of Type I IFN system as supported by decreased secretion of IFN-α in MyD88 KO mice compared with wild type mice. We next selected murine glioma cell lines with known response profile to CIs (responders – GL261 and SMA560 vs non-responders – KR158b and CT2A). Prior to evaluation of cytokine profiling, successful uptake of RNA-LPAs was achieved in all cell lines. In 2D cell lines cultures and their corresponding 3D tumor spheroids, we demonstrated that treatment of CI responsive murine glioma models showed a differential cytokine signature (increased secretion of IFN-β/IL-6/CCL4 versus non-responsive models). CONCLUSION We identified a unique inflammatory signature after ex vivo RNA-LPAs challenge that correlates with checkpoint blockade activity. These findings allow for creation of a diagnostic assay to quickly assess tumor immunogenicity, allowing for informed immunotherapeutic treatment.