A functional identification platform reveals frequent, spontaneous neoantigen-specific T cell responses in patients with cancer.

The clinical impact of tumor-specific neoantigens as both immunotherapeutic targets and biomarkers has been impeded by the lack of efficient methods for their identification and validation from routine samples. We have developed a platform that combines bioinformatic analysis of tumor exomes and transcriptional data with functional testing of autologous peripheral blood mononuclear cells (PBMCs) to simultaneously identify and validate neoantigens recognized by naturally primed CD4+ and CD8+ T cell responses across a range of tumor types and mutational burdens. The method features a human leukocyte antigen (HLA)-agnostic bioinformatic algorithm that prioritizes mutations recognized by patient PBMCs at a greater than 40% positive predictive value followed by a short-term in vitro functional assay, which allows interrogation of 50 to 75 expressed mutations from a single 50-ml blood sample. Neoantigens validated by this method include both driver and passenger mutations, and this method identified neoantigens that would not have been otherwise detected using an in silico prediction approach. These findings reveal an efficient approach to systematically validate clinically actionable neoantigens and the T cell receptors that recognize them and demonstrate that patients across a variety of human cancers have a diverse repertoire of neoantigen-specific T cells.

Linked CD4+/CD8+ T cell neoantigen vaccination overcomes immune checkpoint blockade resistance and enables tumor regression.

Therapeutic benefit to immune checkpoint blockade (ICB) is currently limited to the subset of cancers thought to possess a sufficient tumor mutational burden (TMB) to allow for the spontaneous recognition of neoantigens (NeoAg) by autologous T cells. We explored whether the response to ICB of an aggressive low-TMB squamous cell tumor could be improved through combination immunotherapy using functionally defined NeoAg as targets for endogenous CD4+ and CD8+ T cells. We found that, whereas vaccination with CD4+ or CD8+ NeoAg alone did not offer prophylactic or therapeutic immunity, vaccines containing NeoAg recognized by both subsets overcame ICB resistance and led to the eradication of large established tumors that contained a subset of PD-L1+ tumor-initiating cancer stem cells (tCSC), provided the relevant epitopes were physically linked. Therapeutic CD4+/CD8+ T cell NeoAg vaccination produced a modified tumor microenvironment (TME) with increased numbers of NeoAg-specific CD8+ T cells existing in progenitor and intermediate exhausted states enabled by combination ICB-mediated intermolecular epitope spreading. We believe that the concepts explored herein should be exploited for the development of more potent personalized cancer vaccines that can expand the range of tumors treatable with ICB.

Linked CD4 + /CD8 + T cell neoantigen vaccination overcomes immune checkpoint blockade resistance and enables tumor regression.

Therapeutic benefit to immune checkpoint blockade (ICB) is currently limited to the subset of cancers thought to possess a sufficient tumor mutational burden (TMB) to allow for the spontaneous recognition of neoantigens (NeoAg) by autologous T cells. We explored whether the response of an aggressive low TMB squamous cell tumor to ICB could be improved through combination immunotherapy using functionally defined NeoAg as targets for endogenous CD4 + and CD8 + T cells. We found that, whereas vaccination with CD4 + or CD8 + NeoAg alone did not offer prophylactic or therapeutic immunity, vaccines containing NeoAg recognized by both subsets overcame ICB resistance and led to the eradication of large established tumors that contained a subset of PD-L1 + tumor-initiating cancer stem cells (tCSC), provided the relevant epitopes were physically linked. Therapeutic CD4 + /CD8 + T cell NeoAg vaccination produced a modified tumor microenvironment (TME) with increased numbers of NeoAg-specific CD8 + T cells existing in progenitor and intermediate exhausted states enabled by combination ICB-mediated intermolecular epitope spreading. The concepts explored herein should be exploited for the development of more potent personalized cancer vaccines that can expand the range of tumors treatable with ICB.

Predicting T cell recognition of MHC class I restricted neoepitopes.

Epitopes that arise from a somatic mutation, also called neoepitopes, are now known to play a key role in cancer immunology and immunotherapy. Recent advances in high-throughput sequencing have made it possible to identify all mutations and thereby all potential neoepitope candidates in an individual cancer. However, most of these neoepitope candidates are not recognized by T cells of cancer patients when tested in vivo or in vitro, meaning they are not immunogenic. Especially in patients with a high mutational load, usually hundreds of potential neoepitopes are detected, highlighting the need to further narrow down this candidate list. In our study, we assembled a dataset of known, naturally processed, immunogenic neoepitopes to dissect the properties that make these neoepitopes immunogenic. The tools to use and thresholds to apply for prioritizing neoepitopes have so far been largely based on experience with epitope identification in other settings such as infectious disease and allergy. Here, we performed a detailed analysis on our dataset of curated immunogenic neoepitopes to establish the appropriate tools and thresholds in the cancer setting. To this end, we evaluated different predictors for parameters that play a role in a neoepitope's immunogenicity and suggest that using binding predictions and length-rescaling yields the best performance in discriminating immunogenic neoepitopes from a background set of mutated peptides. We furthermore show that almost all neoepitopes had strong predicted binding affinities (as expected), but more surprisingly, the corresponding non-mutated peptides had nearly as high affinities. Our results provide a rational basis for parameters in neoepitope filtering approaches that are being commonly used. Abbreviations: SNV: single nucleotide variant; nsSNV: nonsynonymous single nucleotide variant; ROC: receiver operating characteristic; AUC: area under ROC curve; HLA: human leukocyte antigen; MHC: major histocompatibility complex; PD-1: Programmed cell death protein 1; PD-L1 or CTLA-4: cytotoxic T-lymphocyte associated protein 4.