Promiscuity of Peptides Presented in HLA-DP Molecules from Different Immunogenicity Groups Is Associated With T-Cell Cross-Reactivity

Accurate prediction of HLA class II antigen presentation across all loci using tailored data acquisition and refined machine learning

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.

Development of TCR-T cell therapy targeting mismatched HLA-DPB1 for relapsed leukemia after allogeneic transplantation

Relapsed leukemia after allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains a significant challenge, with the re-emergence of the primary disease being the most frequent cause of death. Human leukocyte antigen (HLA)-DPB1 mismatch occurs in approximately 70% of unrelated allo-HSCT cases, and targeting mismatched HLA-DPB1 is considered reasonable for treating relapsed leukemia following allo-HSCT if performed under proper conditions. In this study, we established several clones restricted to HLA-DPB1*02:01, -DPB1*04:02, and -DPB1*09:01 from three patients who underwent HLA-DPB1 mismatched allo-HSCT using donor-derived alloreactive T cells primed to mismatched HLA-DPB1 in the recipient's body after transplantation. A detailed analysis of the DPB1*09:01-restricted clone 2A9 showed reactivity against various leukemia cell lines and primary myeloid leukemia blasts, even with low HLA-DP expression. T cell receptor (TCR)-T cells derived from clone 2A9 retained the ability to trigger HLA-DPB1*09:01-restricted recognition and lysis of various leukemia cell lines in vitro. Our study demonstrated that the induction of mismatched HLA-DPB1 specific T cell clones from physiologically primed post-allo-HSCT alloreactive CD4⁺ T cells and the redirection of T cells with cloned TCR cDNA by gene transfer are feasible as techniques for future adoptive immunotherapy.

Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes

CD4⁺ T cells orchestrate the adaptive immune response against pathogens and cancer by recognizing epitopes presented on class II major histocompatibility complex (MHC-II) molecules. The high polymorphism of MHC-II genes represents an important hurdle toward accurate prediction and identification of CD4⁺ T cell epitopes. Here we collected and curated a dataset of 627,013 unique MHC-II ligands identified by mass spectrometry. This enabled us to precisely determine the binding motifs of 88 MHC-II alleles across humans, mice, cattle, and chickens. Analysis of these binding specificities combined with X-ray crystallography refined our understanding of the molecular determinants of MHC-II motifs and revealed a widespread reverse-binding mode in HLA-DP ligands. We then developed a machine-learning framework to accurately predict binding specificities and ligands of any MHC-II allele. This tool improves and expands predictions of CD4⁺ T cell epitopes and enables us to discover viral and bacterial epitopes following the aforementioned reverse-binding mode.

A combination of HLA-DP α and β chain polymorphisms paired with a SNP in the DPB1 3' UTR region, denoting expression levels, are associated with atopic dermatitis

Introduction: Components of the immune response have previously been associated with the pathophysiology of atopic dermatitis (AD), specifically the Human Leukocyte Antigen (HLA) Class II region via genome-wide association studies, however the exact elements have not been identified. Methods: This study examines the genetic variation of HLA Class II genes using next generation sequencing (NGS) and evaluates the resultant amino acids, with particular attention on binding site residues, for associations with AD. The Genetics of AD cohort was used to evaluate HLA Class II allelic variation on 464 subjects with AD and 384 controls. Results: Statistically significant associations with HLA-DP α and β alleles and specific amino acids were found, some conferring susceptibility to AD and others with a protective effect. Evaluation of polymorphic residues in DP binding pockets revealed the critical role of P1 and P6 (P1: α31M + (β84G or β84V) [protection]; α31Q + β84D [susceptibility] and P6: α11A + β11G [protection]) and were replicated with a national cohort of children consisting of 424 AD subjects. Independently, AD susceptibility-associated residues were associated with the G polymorphism of SNP rs9277534 in the 3' UTR of the HLA-DPB1 gene, denoting higher expression of these HLA-DP alleles, while protection-associated residues were associated with the A polymorphism, denoting lower expression. Discussion: These findings lay the foundation for evaluating non-self-antigens suspected to be associated with AD as they potentially interact with particular HLA Class II subcomponents, forming a complex involved in the pathophysiology of AD. It is possible that a combination of structural HLA-DP components and levels of expression of these components contribute to AD pathophysiology.

Human T cells recognize HLA-DP-bound peptides in two orientations

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.

Distribution of HLA-A, -B, -C, -DRB1, -DQB1, -DPB1 allele frequencies in patients with COVID-19 bilateral pneumonia in Russians, living in the Chelyabinsk region (Russia)

In this population-based case-control study conducted in the Chelyabinsk region of Russia, we examined the distribution of HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1, in a group of 100 patients with confirmed COVID-19 bilateral pneumonia. Typing was performed by NGS and statistical calculations were carried out with the Arlequin program. HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1 alleles were compared between patients with COVID-19 and 99 healthy controls. We identified that COVID-19 susceptibility is associated with alleles and genotypes rs9277534A (disequilibrium with HLA-DPB1*02:01, -02:02, -04:01, -04:02, -17:01 alleles) with low expression of protein products HLA-DPB1 (pc < 0.028) and homozygosity at HLA-C*04 (p = 0.024, pc = 0.312). Allele HLA-A*01:01 was decreased in a group of patients with severe forms of bilateral pneumonia, and therefore it may be considered as a protective factor for the development of severe symptoms of COVID-19 (p = 0.009, pc = 0.225). Our studies provide further evidence for the functional association between HLA genes and COVID-19.