Mass Spectrometry Based Immunopeptidomics Leads to Robust Predictions of Phosphorylated HLA Class I Ligands.

Details

Serval ID
serval:BIB_0EBACC6764B1
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Mass Spectrometry Based Immunopeptidomics Leads to Robust Predictions of Phosphorylated HLA Class I Ligands.
Journal
Molecular & cellular proteomics
Author(s)
Solleder M., Guillaume P., Racle J., Michaux J., Pak H.S., Müller M., Coukos G., Bassani-Sternberg M., Gfeller D.
ISSN
1535-9484 (Electronic)
ISSN-L
1535-9476
Publication state
Published
Issued date
02/2020
Peer-reviewed
Oui
Volume
19
Number
2
Pages
390-404
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Abstract
The presentation of peptides on class I human leukocyte antigen (HLA-I) molecules plays a central role in immune recognition of infected or malignant cells. In cancer, non-self HLA-I ligands can arise from many different alterations, including non-synonymous mutations, gene fusion, cancer-specific alternative mRNA splicing or aberrant post-translational modifications. Identifying HLA-I ligands remains a challenging task that requires either heavy experimental work for in vivo identification or optimized bioinformatics tools for accurate predictions. To date, no HLA-I ligand predictor includes post-translational modifications. To fill this gap, we curated phosphorylated HLA-I ligands from several immunopeptidomics studies (including six newly measured samples) covering 72 HLA-I alleles and retrieved a total of 2,066 unique phosphorylated peptides. We then expanded our motif deconvolution tool to identify precise binding motifs of phosphorylated HLA-I ligands. Our results reveal a clear enrichment of phosphorylated peptides among HLA-C ligands and demonstrate a prevalent role of both HLA-I motifs and kinase motifs on the presentation of phosphorylated peptides. These data further enabled us to develop and validate the first predictor of interactions between HLA-I molecules and phosphorylated peptides.
Keywords
Computational Biology, HLA peptidomics, HLA-I ligand predictions, Immunology*, Mass Spectrometry, Peptidomics, Phosphorylation, computational immunology, phosphorylated HLA-I binding motifs, phosphorylated HLA-I ligands, Mass spectrometry, computational biology, immunology, peptidomics, phosphorylation
Pubmed
Open Access
Yes
Create date
20/12/2019 10:20
Last modification date
18/02/2020 6:20
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