A functional identification platform reveals frequent spontaneous neoantigen-specific T cell responses in cancer patients
The clinical impact of tumor-specific neoantigens (NeoAg) as both immunotherapeutic targets and biomarkers has been impeded by the absence of efficient methods for their identification and validation from routine samples. We have developed a novel platform that combines bioinformatic analysis of tumor exome and RNA data with functional testing of autologous PBMC to simultaneously identify and validate NeoAg recognized by naturally-primed CD4+ and CD8+ T cells immune responses across a range of tumor histologies and mutational burdens (TMB). The method features an HLA-agnostic bioinformatic algorithm that prioritizes mutations recognized by patient PBMC at a >40% PPV followed by a short-term culture in a functional assay which allows interrogation of 50-75 expressed mutations from a single 50 ml blood sample. NeoAg validated by this method include both driver and passenger mutations, and those that would not have been otherwise identifiable using in silico prediction of antigen processing and HLA class I binding. These findings reveal a new and efficient approach to the systematic validation of clinically-actionable NeoAg and the T cell receptors (TCRs) that recognize them, and demonstrate that patients across a variety of human cancers possess a diverse repertoire of NeoAg-specific T cells.