Cancers avoid immune surveillance through an array of mechanisms, including perturbation of HLA class I antigen presentation. Merkel cell carcinoma (MCC) is an aggressive, HLA-I–low, neuroendocrine carcinoma of the skin often caused by the Merkel cell polyomavirus (MCPyV). Through the characterization of 11 newly generated MCC patient-derived cell lines, we identified transcriptional suppression of several class I antigen presentation genes. To systematically identify regulators of HLA-I loss in MCC, we performed parallel, genome-scale, gain- and loss-of-function screens in a patient-derived MCPyV-positive cell line and identified MYCL and the non-canonical Polycomb repressive complex 1.1 (PRC1.1) as HLA-I repressors. We observed physical interaction of MYCL with the MCPyV small T viral antigen, supporting a mechanism of virally mediated HLA-I suppression. We further identify the PRC1.1 component USP7 as a pharmacologic target to restore HLA-I expression in MCC.

Prediction of HLA epitopes is important for the development of cancer immunotherapies and vaccines. However, current prediction algorithms have limited predictive power, in part because they were not trained on high-quality epitope datasets covering a broad range of HLA alleles. To enable prediction of endogenous HLA class I-associated peptides across a large fraction of the human population, we used mass spectrometry to profile >185,000 peptides eluted from 95 HLA-A, -B, -C and -G mono-allelic cell lines. We identified canonical peptide motifs per HLA allele, unique and shared binding submotifs across alleles and distinct motifs associated with different peptide lengths. By integrating these data with transcript abundance and peptide processing, we developed HLAthena, providing allele-and-length-specific and pan-allele-pan-length prediction models for endogenous peptide presentation. These models predicted endogenous HLA class I-associated ligands with 1.5-fold improvement in positive predictive value compared with existing tools and correctly identified >75% of HLA-bound peptides that were observed experimentally in 11 patient-derived tumor cell lines.

Personal vaccines directed at neoantigens arising from tumor mutations can induce neoepitope-specific T cell responses in patients with highly mutated tumors such as melanoma. It remains unknown if this approach can be successfully applied in tumors with low mutation frequency. We conducted a phase 1/1b study to determine the safety and feasibility of patient-specific neoantigen-targeting vaccination in patients with newly diagnosed, methylguanine methyltransferase (MGMT) unmethylated glioblastoma, administered following maximum surgical resection and conventional radiotherapy. Tumor-specific mutations were identified by whole-exome sequencing. Each vaccine, composed of up to 20 synthetic long peptides containing predicted tumor neoepitopes admixed with poly-ICLC, was administered subcutaneously on a prime-boost schedule. Among 8 treated patients, adverse events were limited to mild injection site reactions. Seven patients (88%) received a vaccine with ≥10 neoepitope peptides (median 12, range, 7-20), with median time to vaccine initiation of 18.6 weeks from surgery. All patients died from progressive disease. Median progression-free and overall survival was 7.5 months (95% CI: 6.2, 9.7) and 16.8 months (90% CI: 9.6, 21.3), respectively. 3 patients dropped out of the study due to disease progression. We analyzed vaccine responses on 5 patients that got at least one booster immunization. All 3 patients who required dexamethasone during vaccine priming failed to generate interferon-γ responses in peripheral blood mononuclear cells. In contrast, 2 patients who did not receive dexamethasone during vaccine priming, generated robust de novo immune responses against multiple personal neoantigens. Circulating vaccine-induced polyfunctional neoantigen-specific CD4+ and CD8+ T cell responses were enriched for memory and activated phenotypes, and increased numbers of tumor-infiltrating CD4+ and CD8+ T cells were detected in these 2 patients. T cell receptor analysis identified identical clonotypes isolated from post-vaccination glioblastoma tissue and peripheral blood including a clonotype specific for ARHGAP35, a neoantigen targeted by vaccination. To our knowledge we provide the first evidence that tumor specific T cells can traffic from the periphery into glioblastoma tumors and that neoantigen-targeting vaccines can favorably alter the tumor immune milieu of glioblastoma. In conclusion, individualized, multi-neoepitope vaccination is feasible, safe, and generates neoantigen-specific T cell responses in the periphery and intracranial tumors of patients with glioblastoma. Citation Format: Derin B. Keskin, Itay Tirosh, Annabelle Anandappa, Jing Sun, Nathan D. Mathewson, Sachet A. Shukla, Evisa Gjini, Shuqiang Li, Letitia Li, Anita Giobbie-Hurder, Phuong M. Le, Zhuting Hu, Wandi Zhang, Oriol Olive, Christine McCluskey, Heather Daley, Patrick Y. Wen, Antonio E. Chiocca, Maegan Harden, Niall Lennon, Stacey Gabriel, Gad Getz, Donna Neuberg, Jerome Ritz, Eric S. Lander, Aviv Regev, Kai Wucherpfennig, Mario Suva, Edward F. Fritsch, Rodig Scott, Keith L. Ligon, Kenneth J. Livak, Hacohen Nir, Patrick A. Ott, Catherine J. Wu, David A. Reardon. Personal neoantigen-targeting vaccination generates neoepitope-specific T cell responses in tumors of patients with glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5631.

Accurate predictive algorithms have required elucidation of HLA-peptide binding motifs from extensive HLA binding peptide ligand databases. Historically, however, little attention has been paid to HLA-C because of its perceived lower surface expression, even as newer studies have identified important HLA-C restricted viral epitopes. Robust predictive algorithms for HLA-C are thus lacking and yet, if improved, could markedly expand the spectrum of immune targets contributing to protective immune responses. We generated 21 distinct single HLA-C allele-expressing cell lines and subjected them to immunoaffinity purification and MS-based sequencing. From 33851 peptides identified from the 21 HLA-C expressing cell lines, we discovered novel anchor motifs. These data were used to train machine-learning algorithms to generate an accurate and novel HLA-C epitope prediction tool. Finally, we used our novel algorithm to predict HLA-C restricted neo-epitopes out of tumor biopsies.

Neoantigens, which are derived from tumour-specific protein-coding mutations, are exempt from central tolerance, can generate robust immune responses1,2 and can function as bona fide antigens that facilitate tumour rejection3. Here we demonstrate that a strategy that uses multi-epitope, personalized neoantigen vaccination, which has previously been tested in patients with high-risk melanoma4-6, is feasible for tumours such as glioblastoma, which typically have a relatively low mutation load1,7 and an immunologically 'cold' tumour microenvironment8. We used personalized neoantigen-targeting vaccines to immunize patients newly diagnosed with glioblastoma following surgical resection and conventional radiotherapy in a phase I/Ib study. Patients who did not receive dexamethasone-a highly potent corticosteroid that is frequently prescribed to treat cerebral oedema in patients with glioblastoma-generated circulating polyfunctional neoantigen-specific CD4+ and CD8+ T cell responses that were enriched in a memory phenotype and showed an increase in the number of tumour-infiltrating T cells. Using single-cell T cell receptor analysis, we provide evidence that neoantigen-specific T cells from the peripheral blood can migrate into an intracranial glioblastoma tumour. Neoantigen-targeting vaccines thus have the potential to favourably alter the immune milieu of glioblastoma.