ArticlePLoS computational biology2012
Proteome sampling by the HLA class I antigen processing pathway.
Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 40 citations in OpenAlex.
- Inhibition of cellular NEDDylation partially alters the MHC class I immunopeptidome.Journal of immunology (Baltimore, Md. : 1950) · 2026Article
- A poxvirus model reveals general correlates of antigen presentation and immunogenicity for viral CD8Science advances · 2025Article
- Development of mesothelioma-specific oncolytic immunotherapy enabled by immunopeptidomics of murine and human mesothelioma tumors.Nature communications · 2023Article
- The immunopeptidome landscape associated with T cell infiltration, inflammation and immune editing in lung cancer.Nature cancer · 2023Article
- Article
- Characterization of the Class I MHC Peptidome Resulting From DNCB Exposure of HaCaT Cells.Toxicological sciences : an official journal of the Society of Toxicology · 2021Article
- Immunoinformatics: Predicting Peptide-MHC Binding.Annual review of biomedical data science · 2020Article
- Alterations in the HLA-B*57:01 Immunopeptidome by Flucloxacillin and Immunogenicity of Drug-Haptenated Peptides.Frontiers in immunology · 2020Article
- Pro-inflammatory Cytokines Alter the Immunopeptidome Landscape by Modulation of HLA-B Expression.Frontiers in immunology · 2019Article
- Mapping the MHC Class I-Spliced Immunopeptidome of Cancer Cells.Cancer immunology research · 2019Article
- The canine MHC class Ia allele DLA-88*508:01 presents diverse self- and canine distemper virus-origin peptides of varying length that have a conserved binding motif.Veterinary immunology and immunopathology · 2018Article
- MHC class I-associated peptides derive from selective regions of the human genome.The Journal of clinical investigation · 2016Article
- Human Leukocyte Antigen (HLA) Peptides Derived from Tumor Antigens Induced by Inhibition of DNA Methylation for Development of Drug-facilitated Immunotherapy.Molecular & cellular proteomics : MCP · 2016Article
- Proteogenomic-based discovery of minor histocompatibility antigens with suitable features for immunotherapy of hematologic cancers.Leukemia · 2016Article
- Sizing up the key determinants of the CD8(+) T cell response.Nature reviews. Immunology · 2015Review
- Generation of MANAbodies specific to HLA-restricted epitopes encoded by somatically mutated genes.Proceedings of the National Academy of Sciences of the United States of America · 2015Article
- Mass spectrometry of human leukocyte antigen class I peptidomes reveals strong effects of protein abundance and turnover on antigen presentation.Molecular & cellular proteomics : MCP · 2015Article
- Lymphocyte repertoire selection and intracellular self/non-self-discrimination: historical overview.Immunology and cell biology · 2015Review
- Comprehensive Analysis of the Naturally Processed Peptide Repertoire: Differences between HLA-A and B in the Immunopeptidome.PloS one · 2015Article
- In silico Derivation of HLA-Specific Alloreactivity Potential from Whole Exome Sequencing of Stem-Cell Transplant Donors and Recipients: Understanding the Quantitative Immunobiology of Allogeneic Transplantation.Frontiers in immunology · 2014Review
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The peptide repertoire that is presented by the set of HLA class I molecules of an individual is formed by the different players of the antigen processing pathway and the stringent binding environment of the HLA class I molecules. Peptide elution studies have shown that only a subset of the human proteome is sampled by the antigen processing machinery and represented on the cell surface. In our study, we quantified the role of each factor relevant in shaping the HLA class I peptide repertoire by combining peptide elution data, in silico predictions of antigen processing and presentation, and data on gene expression and protein abundance. Our results indicate that gene expression level, protein abundance, and rate of potential binding peptides per protein have a clear impact on sampling probability. Furthermore, once a protein is available for the antigen processing machinery in sufficient amounts, C-terminal processing efficiency and binding affinity to the HLA class I molecule determine the identity of the presented peptides. Having studied the impact of each of these factors separately, we subsequently combined all factors in a logistic regression model in order to quantify their relative impact. This model demonstrated the superiority of protein abundance over gene expression level in predicting sampling probability. Being able to discriminate between sampled and non-sampled proteins to a significant degree, our approach can potentially be used to predict the sampling probability of self proteins and of pathogen-derived proteins, which is of importance for the identification of autoimmune antigens and vaccination targets.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.