Robust prediction of HLA class II epitopes by deep motif deconvolution of immunopeptidomes

Nat Biotechnol. 2019 Nov;37(11):1283-1286. doi: 10.1038/s41587-019-0289-6. Epub 2019 Oct 14.

Abstract

Predictions of epitopes presented by class II human leukocyte antigen molecules (HLA-II) have limited accuracy, restricting vaccine and therapy design. Here we combined unbiased mass spectrometry with a motif deconvolution algorithm to profile and analyze a total of 99,265 unique peptides eluted from HLA-II molecules. We then trained an epitope prediction algorithm with these data and improved prediction of pathogen and tumor-associated class II neoepitopes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Cell Line
  • Computational Biology / methods
  • Epitopes / metabolism*
  • Histocompatibility Antigens Class II / chemistry
  • Histocompatibility Antigens Class II / metabolism*
  • Humans
  • Mass Spectrometry
  • Peptides / analysis*
  • Peptides / immunology

Substances

  • Epitopes
  • Histocompatibility Antigens Class II
  • Peptides