Mass Spectrometry of Human Leukocyte Antigen Class I Peptidomes Reveals Strong Effects of Protein Abundance and Turnover on Antigen Presentation

Abstract

HLA class I molecules reflect the health state of cells to cytotoxic T cells by presenting a repertoire of endogenously derived peptides. However, the extent to which the proteome shapes the peptidome is still largely unknown. Here we present a high-throughput mass-spectrometry-based workflow that allows stringent and accurate identification of thousands of such peptides and direct determination of binding motifs. Applying the workflow to seven cancer cell lines and primary cells, yielded more than 22,000 unique HLA peptides across different allelic binding specificities. By computing a score representing the HLA-I sampling density, we show a strong link between protein abundance and HLA-presentation (p < 0.0001). When analyzing overpresented proteins - those with at least fivefold higher density score than expected for their abundance - we noticed that they are degraded almost 3 h faster than similar but nonpresented proteins (top 20% abundance class; median half-life 20.8h versus 23.6h, p < 0.0001). This validates protein degradation as an important factor for HLA presentation. Ribosomal, mitochondrial respiratory chain, and nucleosomal proteins are particularly well presented. Taking a set of proteins associated with cancer, we compared the predicted immunogenicity of previously validated T-cell epitopes with other peptides from these proteins in our data set. The validated epitopes indeed tend to have higher immunogenic scores than the other detected HLA peptides. Remarkably, we identified five mutated peptides from a human colon cancer cell line, which have very recently been predicted to be HLA-I binders. Altogether, we demonstrate the usefulness of combining MS-analysis with immunogenesis prediction for identifying, ranking, and selecting peptides for therapeutic use.

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• High-throughput and Sensitive Immunopeptidomics Platform Reveals Profound Interferonγ-Mediated Remodeling of the Human Leukocyte Antigen (HLA) Ligandome · 2018
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• Differential binding affinity of mutated peptides for MHC class I is a predictor of survival in advanced lung cancer and melanoma · 2018
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• Deciphering HLA-I motifs across HLA peptidomes improves neo-antigen predictions and identifies allostery regulating HLA specificity · 2017
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• GibbsCluster: unsupervised clustering and alignment of peptide sequences · 2017
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• Direct identification of clinically relevant neoepitopes presented on native human melanoma tissue by mass spectrometry · 2016
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