Direct identification of clinically relevant neoepitopes presented on native human melanoma tissue by mass spectrometry

By M. Bassani-Sternberg, E. Bräunlein, R. Klar, T. Engleitner, Pavel Sinitcyn, S. Audehm, M. Straub, Julia Weber, J. Slotta-Huspenina, K. Specht and 9 more. Nature Communications, 2016

643 citations recorded by the source corpus.

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. Neoantigens determine anti-cancer immunoreactivity and are important functional targets for immunotherapy. Here, the authors use deep mass spectrometry to characterize neoepitopes from human melanoma tissue and show the presence of tumour-reactive T cells with specificity for selected neoantigens.

Subfields: Immunology, Molecular Biology, Oncology

View Paper: https://www.semanticscholar.org/paper/1ed1f044ec85ebff2bf5fa93058d53d7cc474e52

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Citations in the corpus

NetMHCpan 4.0: Improved peptide-MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data (2017, background): “Thus, identification of MHC-bound peptides by MS holds great promise for the generation of large-scale data sets characterizing the peptidome specific for individual MHC molecules (15, 17) and potentially for the identification of T cell epitopes (18).”
Development of tumor mutation burden as an immunotherapy biomarker: utility for the oncology clinic (2018, background): “Therefore, not all neopeptides presented on the cell surface are immunogenic [48-50].”
Neoantigens: promising targets for cancer therapy (2023, background): “Based on cancer genomic data, the immunogenomic technique predicted millions of possible mutation-derived neoantigens, but the vast majority of them did not manifest in proteomic profiling of HLA-bound peptides.(233,234) The high-throughput identification of peptides attached to MHC is made possible”
Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients (2018, background): “An important improvement will be to replace this step; e.g., with MS-based immunopeptidomics (Bassani-Sternberg et al., 2016).”
A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding prediction (2020, background): “Up until recently, most of these data have been generated using in vitro binding assays [15, 16], but the use of mass spectrometry (MS)-based identification of purified HLA-binding peptides has now come into the forefront [17–19].”