LAUSR

Proteins that can serve as effective tumor rejection antigens within brain tumors are poorly characterized. Current prediction algorithms relying on identification of mutated epitopes as neoantigens are limited in low mutational burden tumors. We have developed a multi-faceted computer algorighm for identifying tumor rejection antigens called the Open Reading Frame Antigen Network (ORAN). This pipeline provides a comprehensive solution for predicting brain tumor immunogenic targetable epitopes/transcripts. Human and murine RNASeq and WES data were QCed. Patients individual HLA-I and HLA-II haplotypes were predicted by highly customized Optitype and Phlat Algorithms. SNPs and Indels were called from tumors WES and read through matched RNASeq data. 19,131 transcripts expression were counted per TOIL algorithm. Tumor associate antigens(TAA) of individual patient or murine tumors were selected by setting a cutoff of Transcripts Per Million (TPM) > 1 on individual patient’s tumor, while RNA Seq data from 7000 normal tissues was used to identify tumor unique transcripts. Actual sequence of HLA and SNPed Consenses TAA(CTAA) were called. Only expressed mutations and personalized TAAs were used for antigenic epitope predictions. All neoepitopes were screened against a human reference proteomic library to guarantee that epitopes were not shared by other expressed isoforms or genes. In silico validation were preformed to cross validate predictions made by ORAN. In medullobastoma (N=121 samples), ORAN gives an average of 15.6 MHC class I restricted neoepitopes,11.9 epitopes encoded by Indels and with 33.2 MHC class II restricted neoepitopes and 16.2 Indel antigens per patient. The TAAs of each patient reaches average 256 antigenic epitopes per patient. ORAN also predicts the exact HLA and neo-antigens from a validated neoantigens vaccine dataset (Gros A Nat Med 2016). ORAN accurately identifies validated neoantigens and provides a comprehensive list of potential tumor rejection antigens within human and murine brain tumors.