Related Experiment Video

Updated: Jun 24, 2025

Immunopeptidomics: Isolation of Mouse and Human MHC Class I- and II-Associated Peptides for Mass Spectrometry Analysis
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Immunopeptidomics: Isolation of Mouse and Human MHC Class I- and II-Associated Peptides for Mass Spectrometry Analysis

Published on: October 15, 2021

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Gene and protein sequence features augment HLA class I ligand predictions

Kaspar Bresser1, Benoit P Nicolet2, Anita Jeko3

  • 1Department of Molecular Oncology and Immunology, Netherlands Cancer Institute, Oncode Institute, Amsterdam, the Netherlands; Department of Hematology, Leiden University Medical Center, Leiden, the Netherlands.

Cell Reports
|June 13, 2024
PubMed

The sensitivity of malignant tissues to T cell-based immunotherapies depends on the presence of targetable human leukocyte antigen (HLA) class I ligands. Peptide-intrinsic factors, such as HLA class I affinity and proteasomal processing, have been established as determinants of HLA ligand presentation. However, the role of gene and protein sequence features as determinants of epitope presentation has not been systematically evaluated. We perform HLA ligandome mass spectrometry to evaluate the contribution of 7,135 gene and protein sequence features to HLA sampling. This analysis reveals that a number of predicted modifiers of mRNA and protein abundance and turnover, including predicted mRNA methylation and protein ubiquitination sites, inform on the presence of HLA ligands. Importantly, integration of such "hard-coded" sequence features into a machine learning approach augments HLA ligand predictions to a comparable degree as experimental measures of gene expression. Our study highlights the value of gene and protein features for HLA ligand predictions.

Keywords:
CP: ImmunologyHLA class IHLA ligand predictionsHLA ligandomeXGBoostantigen presentationepitope predictionepitopesmachine learning

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