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Human leukocyte antigen (HLA) molecules present small peptide antigens to T cells, thereby allowing them to recognize pathogen-infected and cancer cells. A central dogma over the last 50+ y is that peptide binding to HLA molecules is mediated by the docking of side chains of particular amino acids in the peptide into pockets in the HLA molecules in a conserved N- to C-terminal orientation. Whether peptides can be presented in a reversed C- to N-terminal orientation remains unclear. Here, we performed large-scale identification of peptides bound to HLA-DP molecules and observed that in addition to peptide binding in an N- to C-terminal orientation, in 9 out of 14 HLA-DP allotypes, reverse motifs are found, compatible with C- to N-terminal peptide binding. Moreover, we isolated high-avidity human cytomegalovirus (CMV)-specific HLA-DP-restricted CD4 + T cells from the memory repertoire of healthy donors and demonstrate that such T cells recognized CMV-derived peptides bound to HLA-DPB1*01:01 or *05:01 in a reverse C- to N-terminal manner. Finally, we obtained a high-resolution HLA-DPB1*01:01-CMVpp65 (142-158) peptide crystal structure, which is the molecular basis for C- to N-terminal peptide binding to HLA-DP. Our results point to unique features of HLA-DP molecules that substantially broaden the HLA class II bound peptide repertoire to combat pathogens and eliminate cancer cells.

In hematopoietic cell transplantation (HCT), permissive HLA-DPB1 mismatches between patients and their unrelated donors are associated with improved outcomes compared with nonpermissive mismatches, but the underlying mechanism is incompletely understood. Here, we used mass spectrometry, T-cell receptor-β (TCRβ) deep sequencing, and cellular in vitro models of alloreactivity to interrogate the HLA-DP immunopeptidome and its role in alloreactive T-cell responses. We find that permissive HLA-DPB1 mismatches display significantly higher peptide repertoire overlaps compared with their nonpermissive counterparts, resulting in lower frequency and diversity of alloreactive TCRβ clonotypes in healthy individuals and transplanted patients. Permissiveness can be reversed by the absence of the peptide editor HLA-DM or the presence of its antagonist, HLA-DO, through significant broadening of the peptide repertoire. Our data establish the degree of immunopeptidome divergence between donor and recipient as the mechanistic basis for the clinically relevant permissive HLA-DPB1 mismatches in HCT and show that permissiveness is dependent on HLA-DM-mediated peptide editing. Its key role for harnessing T-cell alloreactivity to HLA-DP highlights HLA-DM as a potential novel target for cellular and immunotherapy of leukemia., (© 2021 by The American Society of Hematology.)

HLA-DP alleles can be classified into functional T cell epitope (TCE) groups. TCE-1 and TCE-2 are clearly defined, but TCE-3 still represents an heterogeneous group. Because polymorphisms in HLA-DP influence the presented peptidome, we investigated whether the composition of peptides binding in HLA-DP may be used to refine the HLA-DP group classification. Peptidomes of human HLA-DP-typed B cell lines were analyzed with mass spectrometry after immunoaffinity chromatography and peptide elution. Gibbs clustering was performed to identify motifs of binding peptides. HLA-DP peptide-binding motifs showed a clear association with the HLA-DP allele-specific sequences of the binding groove. Hierarchical clustering of HLA-DP immunopeptidomes was performed to investigate the similarities and differences in peptidomes of different HLA-DP molecules, and this clustering resulted in the categorization of HLA-DP alleles into 3-DP peptidome clusters (DPC). The peptidomes of HLA-DPB1*09:01, -10:01, and -17:01 (TCE-1 alleles) and HLA-DPB1*04:01, -04:02, and -02:01 (TCE-3 alleles) were separated in two maximal distinct clusters, DPC-1 and DPC-3, respectively, reflecting their previous TCE classification. HLA-DP alleles categorized in DPC-2 shared certain similar peptide-binding motifs with DPC-1 or DPC-3 alleles, but significant differences were observed for other positions. Within DPC-2, divergence between the alleles was observed based on the preference for different peptide residues at position 9. In summary, immunopeptidome analysis was used to unravel functional hierarchies among HLA-DP alleles, providing new molecular insights into HLA-DP classification., (Copyright © 2020 by The American Association of Immunologists, Inc.)

In the context of HLA-DP-mismatched allogeneic stem cell transplantation, mismatched HLA-DP alleles can provoke profound allo-HLA-DP-specific immune responses from the donor T-cell repertoire leading to graft-versus-leukemia effect and/or graft-versus-host disease in the patient. The magnitude of allo-HLA-DP-specific immune responses has been shown to depend on the specific HLA-DP disparity between donor and patient and the immunogenicity of the mismatched HLA-DP allele(s). HLA-DP peptidome clustering (DPC) was developed to classify the HLA-DP molecules based on similarities and differences in their peptide-binding motifs. To investigate a possible categorization of HLA-DP molecules based on overlap of presented peptides, we identified and compared the peptidomes of the thirteen most frequently expressed HLA-DP molecules. Our categorization based on shared peptides was in line with the DPC classification. We found that the HLA-DP molecules within the previously defined groups DPC-1 or DPC-3 shared the largest numbers of presented peptides. However, the HLA-DP molecules in DPC-2 segregated into two subgroups based on the overlap in presented peptides. Besides overlap in presented peptides within the DPC groups, a substantial number of peptides was also found to be shared between HLA-DP molecules from different DPC groups, especially for groups DPC-1 and -2. The functional relevance of these findings was illustrated by demonstration of cross-reactivity of allo-HLA-DP-reactive T-cell clones not only against HLA-DP molecules within one DPC group, but also across different DPC groups. The promiscuity of peptides presented in various HLA-DP molecules and the cross-reactivity against different HLA-DP molecules demonstrate that these molecules cannot be strictly categorized in immunogenicity groups. [ABSTRACT FROM AUTHOR]

Accurate prediction of antigen presentation by human leukocyte antigen (HLA) class II molecules is crucial for rational development of immunotherapies and vaccines targeting CD4+ T cell activation. So far, most prediction methods for HLA class II antigen presentation have focused on HLA-DR because of limited availability of immunopeptidomics data for HLA-DQ and HLA-DP while not taking into account alternative peptide binding modes. We present an update to the NetMHCIIpan prediction method, which closes the performance gap between all three HLA class II loci. We accomplish this by first integrating large immunopeptidomics datasets describing the HLA class II specificity space across all loci using a refined machine learning framework that accommodates inverted peptide binders. Next, we apply targeted immunopeptidomics assays to generate data that covers additional HLA-DP specificities. The final method, NetMHCIIpan-4.3, achieves high accuracy and molecular coverage across all HLA class II allotypes. [ABSTRACT FROM AUTHOR]