IMMU-47. THE ANTIGENIC PROFILE OF MURINE AND HUMAN MEDULLOBLASTOMA

Abstract

Abstract BACKGROUND Cancer immunogenomics represents a complementary approach to the application of genomics in developing novel immunotherapies. We performed a multi-faceted computer algorithm, the Open Reading Frame Antigen Network (O.R.A.N.), on medulloblastoma transcription profiles and predicted antigens across a broad array of antigen classes. METHODS Patient-specific HLA haplotypes were called via customized Optitype and Phlat algorithms. Preclinical models- sonic hedgehog driven (Ptch1) and Group 3 MYC-driven (NSC) medulloblastoma were derived from C57BL6 murine strain with known MHC haplotypes. Only expressed mutations such as single nucleotide variations, small indels, gene fusions, and personalized TAAs were used for antigenic epitope predictions. Patient-specific or murine tumor associated antigens (TAA) were selected only if expressed >1 transcript per million (TPM) in tumor and the standardized expression across a human tissue database (29 organs or sub-regions, n=9,141) or a mouse normal tissue database (ENCODE, n=99) was below 1 TPM, respectively. TAA sequences were passed through eight MHC class I and four MHC class II affinity algorithms. All epitopes were screened against a customized human or murine proteomic library to guarantee that epitopes were not shared by other expressed isoforms or genes. Immune deconvolution with single cell RNASeq integration was leveraged for teasing out medulloblastoma immunologic landscape. RESULTS MB patients harbor MHC-I restricted 1.9 SNV, 0.1 Indel, 0.5 gene fusions and MHC-II restricted 2.5 SNV, 0.1 Indel and 0.5 gene fusion. 79.4% patients have at least 1 neoantigen. 88.2% patients have at least one immunogenic TAA. Importantly, cancer testis antigens and previously unappreciated neurodevelopmental antigens were found expressed across all medulloblastoma subgroups. We predicted 6 neoantigens and 14 TAAs for murine NSC tumor and 19 neoantigens and 13 TAAs for Ptch1 tumor. CONCULSION: Using a custom antigen prediction pipeline, we identified potential human and murine tumor rejection antigens with important implications for development of medulloblastoma cellular therapies.