Although mutations may represent attractive targets for immunotherapy, direct identification of mutated peptide ligands isolated from human leucocyte antigens (HLA) on the surface of native tumour tissue has so far not been successful. Using advanced mass spectrometry (MS) analysis, we survey the melanoma-associated immunopeptidome to a depth of 95,500 patient-presented peptides. We thereby discover a large spectrum of attractive target antigen candidates including cancer testis antigens and phosphopeptides. Most importantly, we identify peptide ligands presented on native tumour tissue samples harbouring somatic mutations. Four of eleven mutated ligands prove to be immunogenic by neoantigen-specific T-cell responses. Moreover, tumour-reactive T cells with specificity for selected neoantigens identified by MS are detected in the patient's tumour and peripheral blood. We conclude that direct identification of mutated peptide ligands from primary tumour material by MS is possible and yields true neoepitopes with high relevance for immunotherapeutic strategies in cancer.
Characterizing the human leukocyte antigen (HLA) bound ligandome by mass spectrometry (MS) holds great promise for developing vaccines and drugs for immune-oncology. Still, the identification of non-tryptic peptides presents substantial computational challenges. To address these, we synthesized and analyzed >300,000 peptides by multi-modal LC-MS/MS within the ProteomeTools project representing HLA class I & II ligands and products of the proteases AspN and LysN. The resulting data enabled training of a single model using the deep learning framework Prosit, allowing the accurate prediction of fragment ion spectra for tryptic and non-tryptic peptides. Applying Prosit demonstrates that the identification of HLA peptides can be improved up to 7-fold, that 87% of the proposed proteasomally spliced HLA peptides may be incorrect and that dozens of additional immunogenic neo-epitopes can be identified from patient tumors in published data. Together, the provided peptides, spectra and computational tools substantially expand the analytical depth of immunopeptidomics workflows.
BackgroundNeoantigens derived from somatic mutations correlate with therapeutic responses mediated by treatment with immune checkpoint inhibitors. Neoantigens are therefore highly attractive targets for the development of therapeutic approaches in personalized medicine, although many aspects of their quality and associated immune responses are not yet well understood. In a case study of metastatic malignant melanoma, we aimed to perform an in-depth characterization of neoantigens and respective T-cell responses in the context of immune checkpoint modulation.MethodsThree neoantigens, which we identified either by immunopeptidomics or in silico prediction, were investigated using binding affinity analyses and structural simulations. We isolated seven T-cell receptors (TCRs) from the patient’s immune repertoire recognizing these antigens. TCRs were compared in vitro by multiparametric analyses including functional avidity, multicytokine secretion, and cross-reactivity screenings. A xenograft mouse model served to study in vivo functionality of selected TCRs. We investigated the patient’s TCR repertoire in blood and different tumor-related tissues over 3 years using TCR beta deep sequencing.ResultsSelected mutated peptide ligands with proven immunogenicity showed similar binding affinities to the human leukocyte antigen complex and comparable disparity to their wild-type counterparts in molecular dynamic simulations. Nevertheless, isolated TCRs recognizing these antigens demonstrated distinct patterns in functionality and frequency. TCRs with lower functional avidity showed at least equal antitumor immune responses in vivo. Moreover, they occurred at high frequencies and particularly demonstrated long-term persistence within tumor tissues, lymph nodes and various blood samples associated with a reduced activation pattern on primary in vitro stimulation.ConclusionsWe performed a so far unique fine characterization of neoantigen-specific T-cell responses revealing defined reactivity patterns of neoantigen-specific TCRs. Our data highlight qualitative differences of these TCRs associated with function and longevity of respective T cells. Such features need to be considered for further optimization of neoantigen targeting including adoptive T-cell therapies using TCR-transgenic T cells.
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