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

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. HLA class II epitopes are accurately predicted by analysis of a large peptide dataset.

[1]  J. Voorberg,et al.  Analysis of the HLA‐DR peptidome from human dendritic cells reveals high affinity repertoires and nonconventional pathways of peptide generation , 2017, Journal of leukocyte biology.

[2]  A. M. Houghton,et al.  Tumor-infiltrating BRAFV600E-specific CD4+ T cells correlated with complete clinical response in melanoma , 2018, The Journal of clinical investigation.

[3]  Søren Brunak,et al.  Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach , 2004, Bioinform..

[4]  George Coukos,et al.  The Length Distribution and Multiple Specificity of Naturally Presented HLA-I Ligands , 2018, The Journal of Immunology.

[5]  Michael R Stratton,et al.  High-throughput epitope discovery reveals frequent recognition of neo-antigens by CD4+ T cells in human melanoma , 2014, Nature Medicine.

[6]  Gary D Bader,et al.  The multiple-specificity landscape of modular peptide recognition domains. , 2011 .

[7]  J. Neefjes,et al.  Towards a systems understanding of MHC class I and MHC class II antigen presentation , 2011, Nature Reviews Immunology.

[8]  Andreas Handel,et al.  Dominant protection from HLA-linked autoimmunity by antigen-specific regulatory T cells , 2017, Nature.

[9]  Charles Elkan,et al.  Fitting a Mixture Model By Expectation Maximization To Discover Motifs In Biopolymer , 1994, ISMB.

[10]  J. Gartner,et al.  Enhanced detection of neoantigen-reactive T cells targeting unique and shared oncogenes for personalized cancer immunotherapy. , 2018, JCI insight.

[11]  Morten Nielsen,et al.  Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification , 2015, Immunogenetics.

[12]  M. Ciudad,et al.  Composition of the HLA‐DR‐associated human thymus peptidome , 2013, European journal of immunology.

[13]  J. Castle,et al.  Mutant MHC class II epitopes drive therapeutic immune responses to cancer , 2015, Nature.

[14]  M. Nielsen,et al.  NetMHCpan-4.0: Improved Peptide–MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data , 2017, The Journal of Immunology.

[15]  David Gfeller,et al.  Unsupervised HLA Peptidome Deconvolution Improves Ligand Prediction Accuracy and Predicts Cooperative Effects in Peptide–HLA Interactions , 2016, The Journal of Immunology.

[16]  J. Gartner,et al.  Immune recognition of somatic mutations leading to complete durable regression in metastatic breast cancer , 2018, Nature Medicine.

[17]  Markus Müller,et al.  High-throughput and Sensitive Immunopeptidomics Platform Reveals Profound Interferonγ-Mediated Remodeling of the Human Leukocyte Antigen (HLA) Ligandome* , 2017, Molecular & Cellular Proteomics.

[18]  J. Gartner,et al.  Immunogenicity of somatic mutations in human gastrointestinal cancers , 2015, Science.

[19]  S. Rosenberg,et al.  CD8+ Enriched “Young” Tumor Infiltrating Lymphocytes Can Mediate Regression of Metastatic Melanoma , 2010, Clinical Cancer Research.

[20]  Jennifer G. Abelin,et al.  Mass Spectrometry Profiling of HLA‐Associated Peptidomes in Mono‐allelic Cells Enables More Accurate Epitope Prediction , 2017, Immunity.

[21]  Brian J. Stevenson,et al.  Sensitive and frequent identification of high avidity neo-epitope specific CD8+ T cells in immunotherapy-naive ovarian cancer , 2018, Nature Communications.

[22]  Morten Nielsen,et al.  GibbsCluster: unsupervised clustering and alignment of peptide sequences , 2017, Nucleic Acids Res..

[23]  Morten Nielsen,et al.  Footprints of antigen processing boost MHC class II natural ligand predictions , 2018, Genome Medicine.

[24]  Morten Nielsen,et al.  NNAlign: a platform to construct and evaluate artificial neural network models of receptor–ligand interactions , 2017, Nucleic Acids Res..

[25]  P. Chattopadhyay,et al.  Live-cell assay to detect antigen-specific CD4+ T-cell responses by CD154 expression , 2006, Nature Protocols.

[26]  J. Utikal,et al.  Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer , 2017, Nature.

[27]  Catherine E Costello,et al.  Immunogenic HLA-DR-Presented Self-Peptides Identified Directly from Clinical Samples of Synovial Tissue, Synovial Fluid, or Peripheral Blood in Patients with Rheumatoid Arthritis or Lyme Arthritis. , 2017, Journal of proteome research.

[28]  Hans-Georg Rammensee,et al.  Pool sequencing of natural HLA-DR, DQ, and DP ligands reveals detailed peptide motifs, constraints of processing, and general rules , 2004, Immunogenetics.

[29]  Charles H. Yoon,et al.  An immunogenic personal neoantigen vaccine for patients with melanoma , 2017, Nature.

[30]  Ash A. Alizadeh,et al.  Antigen Presentation Profiling Reveals Recognition of Lymphoma Immunoglobulin Neoantigens , 2017, Nature.

[31]  M. Mann,et al.  MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification , 2008, Nature Biotechnology.

[32]  Morten Nielsen,et al.  Improved peptide-MHC class II interaction prediction through integration of eluted ligand and peptide affinity data , 2019, Immunogenetics.

[33]  J. Greenbaum,et al.  Improved methods for predicting peptide binding affinity to MHC class II molecules , 2018, Immunology.

[34]  José A. Dianes,et al.  2016 update of the PRIDE database and its related tools , 2015, Nucleic Acids Res..

[35]  L. Stern,et al.  HLA-DM Constrains Epitope Selection in the Human CD4 T Cell Response to Vaccinia Virus by Favoring the Presentation of Peptides with Longer HLA-DM–Mediated Half-Lives , 2012, The Journal of Immunology.

[36]  Morten Nielsen,et al.  Different binding motifs of the celiac disease-associated HLA molecules DQ2.5, DQ2.2, and DQ7.5 revealed by relative quantitative proteomics of endogenous peptide repertoires , 2014, Immunogenetics.

[37]  Valerio Zolla,et al.  The Dendritic Cell Major Histocompatibility Complex II (MHC II) Peptidome Derives from a Variety of Processing Pathways and Includes Peptides with a Broad Spectrum of HLA-DM Sensitivity* , 2016, The Journal of Biological Chemistry.

[38]  M. Donia,et al.  Simplified protocol for clinical-grade tumor-infiltrating lymphocyte manufacturing with use of the Wave bioreactor. , 2014, Cytotherapy.

[39]  Michele A. Busby,et al.  Supplementary Materials for Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification , 2018 .

[40]  Morten Nielsen,et al.  An automated benchmarking platform for MHC class II binding prediction methods , 2018, Bioinform..

[41]  D. Neri,et al.  Membranal and Blood‐Soluble HLA Class II Peptidome Analyses Using Data‐Dependent and Independent Acquisition , 2018, Proteomics.

[42]  José A. Dianes,et al.  2016 update of the PRIDE database and its related tools , 2016, Nucleic Acids Res..

[43]  Omar Wagih,et al.  ggseqlogo: a versatile R package for drawing sequence logos , 2017, Bioinform..

[44]  M. Mann,et al.  Direct identification of clinically relevant neoepitopes presented on native human melanoma tissue by mass spectrometry , 2016, Nature Communications.

[45]  Alessandro Sette,et al.  The Immune Epitope Database (IEDB): 2018 update , 2018, Nucleic Acids Res..

[46]  David Gfeller,et al.  Deciphering HLA-I motifs across HLA peptidomes improves neo-antigen predictions and identifies allostery regulating HLA specificity , 2017, bioRxiv.

[47]  A. M. Houghton,et al.  Endogenous CD4+ T Cells Recognize Neoantigens in Lung Cancer Patients, Including Recurrent Oncogenic KRAS and ERBB2 (Her2) Driver Mutations , 2019, Cancer Immunology Research.