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Transplantation of hematopoietic cells from a healthy individual (allogeneic hematopoietic cell transplantation (allo-HCT)) demonstrates that adoptive immunotherapy can cure blood cancers: still, post-transplantation relapses remain frequent. To explain their drivers, we analyzed the genomic and gene expression profiles of acute myeloid leukemia (AML) blasts purified from patients at serial time-points during their disease history. We identified a transcriptional signature specific for post-transplantation relapses and highly enriched in immune-related processes, including T cell costimulation and antigen presentation. In two independent patient cohorts we confirmed the deregulation of multiple costimulatory ligands on AML blasts at post-transplantation relapse (PD-L1, B7-H3, CD80, PVRL2), mirrored by concomitant changes in circulating donor T cells. Likewise, we documented the frequent loss of surface expression of HLA-DR, -DQ and -DP on leukemia cells, due to downregulation of the HLA class II regulator CIITA. We show that loss of HLA class II expression and upregulation of inhibitory checkpoint molecules represent alternative modalities to abolish AML recognition from donor-derived T cells, and can be counteracted by interferon-γ or checkpoint blockade, respectively. Our results demonstrate that the deregulation of pathways involved in T cell-mediated allorecognition is a distinctive feature and driver of AML relapses after allo-HCT, which can be rapidly translated into personalized therapies.Post-transplantation relapse in acute myeloid leukemia patients without genomic loss of HLA is driven by transcriptional alterations in antigen presentation and T cell costimulation genes.

Th2 immunity plays important roles in both protective and allergic responses. Nevertheless, the nature of antigen-presenting cells responsible for Th2 cell differentiation remains ill-defined compared with the nature of the cells responsible for Th1 and Th17 cell differentiation. Basophils have attracted attention as a producer of Th2-inducing cytokine IL-4, whereas their MHC class II (MHC-II) expression and function as antigen-presenting cells are matters of considerable controversy. Here we revisited the MHC-II expression on basophils and explored its functional relevance in Th2 cell differentiation. Basophils generated in vitro from bone marrow cells in culture with IL-3 plus GM-CSF displayed MHC-II on the cell surface, whereas those generated in culture with IL-3 alone did not. Of note, these MHC-II–expressing basophils showed little or no transcription of the corresponding MHC-II gene. The GM-CSF addition to culture expanded dendritic cells (DCs) other than basophils. Coculture of basophils and DCs revealed that basophils acquired peptide–MHC-II complexes from DCs via cell contact-dependent trogocytosis. The acquired complexes, together with CD86, enabled basophils to stimulate peptide-specific T cells, leading to their proliferation and IL-4 production, indicating that basophils can function as antigen-presenting cells for Th2 cell differentiation. Transfer of MHC-II from DCs to basophils was also detected in draining lymph nodes of mice with atopic dermatitis-like skin inflammation. Thus, the present study defined the mechanism by which basophils display MHC-II on the cell surface and appears to reconcile some discrepancies observed in previous studies.

Human leukocyte antigen (HLA) is a key genetic factor conferring risk of systemic lupus erythematosus (SLE), but precise independent localization of HLA effects is extremely challenging. As a result, the contribution of specific HLA alleles and amino-acid residues to the overall risk of SLE and to risk of specific autoantibodies are far from completely understood. Here, we dissected (a) overall SLE association signals across HLA, (b) HLA-peptide interaction, and (c) residue-autoantibody association. Classical alleles, SNPs, and amino-acid residues of eight HLA genes were imputed across 4,915 SLE cases and 13,513 controls from Eastern Asia. We performed association followed by conditional analysis across HLA, assessing both overall SLE risk and risk of autoantibody production. DR15 alleles HLA-DRB1*15:01 (P = 1.4x10-27, odds ratio (OR) = 1.57) and HLA-DQB1*06:02 (P = 7.4x10-23, OR = 1.55) formed the most significant haplotype (OR = 2.33). Conditioned protein-residue signals were stronger than allele signals and mapped predominantly to HLA-DRB1 residue 13 (P = 2.2x10-75) and its proxy position 11 (P = 1.1x10-67), followed by HLA-DRB1-37 (P = 4.5x10-24). After conditioning on HLA-DRB1, novel associations at HLA-A-70 (P = 1.4x10-8), HLA-DPB1-35 (P = 9.0x10-16), HLA-DQB1-37 (P = 2.7x10-14), and HLA-B-9 (P = 6.5x10-15) emerged. Together, these seven residues increased the proportion of explained heritability due to HLA to 2.6%. Risk residues for both overall disease and hallmark autoantibodies (i.e., nRNP: DRB1-11, P = 2.0x10-14; DRB1-13, P = 2.9x10-13; DRB1-30, P = 3.9x10-14) localized to the peptide-binding groove of HLA-DRB1. Enrichment for specific amino-acid characteristics in the peptide-binding groove correlated with overall SLE risk and with autoantibody presence. Risk residues were in primarily negatively charged side-chains, in contrast with rheumatoid arthritis. We identified novel SLE signals in HLA Class I loci (HLA-A, HLA-B), and localized primary Class II signals to five residues in HLA-DRB1, HLA-DPB1, and HLA-DQB1. These findings provide insights about the mechanisms by which the risk residues interact with each other to produce autoantibodies and are involved in SLE pathophysiology.

The secretion of Interleukin-4 (IL4) is the characteristic of T-helper 2 responses. IL4 is a cytokine produced by CD4+ T cells in response to helminthes and other extracellular parasites. It has a critical role in guiding antibody class switching, hematopoiesis and inflammation, and the development of appropriate effector T-cell responses. In this study, it is the first time an attempt has been made to understand whether it is possible to predict IL4 inducing peptides. The data set used in this study comprises 904 experimentally validated IL4 inducing and 742 noninducing MHC class II binders. Our analysis revealed that certain types of residues are preferred at certain positions in IL4 inducing peptides. It was also observed that IL4 inducing and noninducing epitopes differ in compositional and motif pattern. Based on our analysis we developed classification models where the hybrid method of amino acid pairs and motif information performed the best with maximum accuracy of 75.76% and MCC of 0.51. These results indicate that it is possible to predict IL4 inducing peptides with reasonable precession. These models would be useful in designing the peptides that may induce desired Th2 response.

Key Points MHC class II molecules bind antigenic peptides that are generated in endosomal–lysosomal antigen-processing compartments. These peptides are derived from proteins that access these compartments using various endocytic pathways and also as a result of autophagy. Proteolysis in antigen-processing compartments is regulated in antigen-presenting cells (APCs) to favour the formation of antigenic peptides that can bind to MHC class II and to avoid the complete hydrolysis of proteins to very short peptides or to amino acids. Nonspecific endocytosis processes are terminated following dendritic cell (DC) activation, but mature DCs can still internalize antigen by receptor-mediated endocytosis or phagocytosis. Using these pathways, mature DCs can generate peptide–MHC class II complexes and activate naive CD4 + T cells. The formation of antigen-processing compartments is regulated during APC activation. B cell activation results in MHC class II recruitment to endosomes and lysosomes to form these compartments, whereas in DCs, lysosomal proteases relocalize to antigen-processing compartments and enhance antigen proteolysis. APC activation leads to efficient generation of peptide–MHC class II complexes and markedly increases the expression of these complexes on the APC plasma membrane. Increased surface expression of peptide–MHC class II complexes on activated APCs is a result of enhanced MHC class II transcription and/or translation, movement of intracellular peptide–MHC class II complexes to the APC plasma membrane and reduced lysosomal MHC class II degradation. Expression of the E3 ubiquitin ligase MARCH1 by immature APCs promotes rapid turnover of peptide–MHC class II complexes. DC activation terminates MARCH1 expression and ubiquitylation of peptide–MHC class II complexes, thus increasing the half-life of peptide–MHC class II complexes. To play their part in the generation of effective adaptive immune responses, different types of antigen-presenting cell (APC) take up and process antigen in different ways. The length of time that peptide–MHC class II complexes are present on APC surfaces can also vary depending on the cell type. This Review describes the different modes and mechanisms that regulate MHC class II processing and presentation. Antigenic peptide-loaded MHC class II molecules (peptide–MHC class II) are constitutively expressed on the surface of professional antigen-presenting cells (APCs), including dendritic cells, B cells, macrophages and thymic epithelial cells, and are presented to antigen-specific CD4 + T cells. The mechanisms of antigen uptake, the nature of the antigen processing compartments and the lifetime of cell surface peptide–MHC class II complexes can vary depending on the type of APC. It is likely that these differences are important for the function of each distinct APC subset in the generation of effective adaptive immune responses. In this Review, we describe our current knowledge of the mechanisms of uptake and processing of antigens, the intracellular formation of peptide–MHC class II complexes, the intracellular trafficking of peptide–MHC class II complexes to the APC plasma membrane and their ultimate degradation.

To define the cell populations that drive joint inflammation in rheumatoid arthritis (RA), we applied single-cell RNA sequencing (scRNA-seq), mass cytometry, bulk RNA sequencing (RNA-seq) and flow cytometry to T cells, B cells, monocytes, and fibroblasts from 51 samples of synovial tissue from patients with RA or osteoarthritis (OA). Utilizing an integrated strategy based on canonical correlation analysis of 5,265 scRNA-seq profiles, we identified 18 unique cell populations. Combining mass cytometry and transcriptomics revealed cell states expanded in RA synovia: THY1(CD90) + HLA-DRA hi sublining fibroblasts, IL1B + pro-inflammatory monocytes, ITGAX + TBX21 + autoimmune-associated B cells and PDCD1 + peripheral helper T (T PH ) cells and follicular helper T (T FH ) cells. We defined distinct subsets of CD8 + T cells characterized by GZMK + , GZMB + , and GNLY + phenotypes. We mapped inflammatory mediators to their source cell populations; for example, we attributed IL6 expression to THY1 + HLA-DRA hi fibroblasts and IL1B production to pro-inflammatory monocytes. These populations are potentially key mediators of RA pathogenesis. Defining cell types and their activation status in rheumatoid arthritis (RA) is critical to understanding this disease. Raychaudhuri and colleagues leverage several single-cell -omics approaches to define the cellular processes and pathways in the human RA joint.

To control and prevent the current COVID-19 pandemic, the development of novel vaccines is an emergent issue. In addition, we need to develop tools that can measure/monitor T-cell and B-cell responses to know how our immune system is responding to this deleterious virus. However, little information is currently available about the immune target epitopes of novel coronavirus (SARS-CoV-2) to induce host immune responses. Through a comprehensive bioinformatic screening of potential epitopes derived from the SARS-CoV-2 sequences for HLAs commonly present in the Japanese population, we identified 2013 and 1399 possible peptide epitopes that are likely to have the high affinity (<0.5%- and 2%-rank, respectively) to HLA class I and II molecules, respectively, that may induce CD8+ and CD4+ T-cell responses. These epitopes distributed across the structural (spike, envelope, membrane, and nucleocapsid proteins) and the nonstructural proteins (proteins corresponding to six open reading frames); however, we found several regions where high-affinity epitopes were significantly enriched. By comparing the sequences of these predicted T cell epitopes to the other coronaviruses, we identified 781 HLA-class I and 418 HLA-class II epitopes that have high homologies to SARS-CoV. To further select commonly-available epitopes that would be applicable to larger populations, we calculated population coverages based on the allele frequencies of HLA molecules, and found 2 HLA-class I epitopes covering 83.8% of the Japanese population. The findings in the current study provide us valuable information to design widely-available vaccine epitopes against SARS-CoV-2 and also provide the useful information for monitoring T-cell responses.

Viral diseases pose major threats to humans and other animals, including the billions of chickens that are an important food source as well as a public health concern due to zoonotic pathogens. Unlike humans and other typical mammals, the major histocompatibility complex (MHC) of chickens can confer decisive resistance or susceptibility to many viral diseases. An iconic example is Marek’s disease, caused by an oncogenic herpesvirus with over 100 genes. Classical MHC class I and class II molecules present antigenic peptides to T lymphocytes, and it has been hard to understand how such MHC molecules could be involved in susceptibility to Marek’s disease, given the potential number of peptides from over 100 genes. We used a new in vitro infection system and immunopeptidomics to determine peptide motifs for the 2 class II molecules expressed by the MHC haplotype B2, which is known to confer resistance to Marek’s disease. Surprisingly, we found that the vast majority of viral peptide epitopes presented by chicken class II molecules arise from only 4 viral genes, nearly all having the peptide motif for BL2*02, the dominantly expressed class II molecule in chickens. We expressed BL2*02 linked to several Marek’s disease virus (MDV) peptides and determined one X-ray crystal structure, showing how a single small amino acid in the binding site causes a crinkle in the peptide, leading to a core binding peptide of 10 amino acids, compared to the 9 amino acids in all other reported class II molecules. The limited number of potential T cell epitopes from such a complex virus can explain the differential MHC-determined resistance to MDV, but raises questions of mechanism and opportunities for vaccine targets in this important food species, as well as providing a basis for understanding class II molecules in other species including humans.

•The vaccine is composed of immunodominant regions of SARS-CoV-2 non-structural proteins.•Also, the functional region of the spike protein is incorporated in the vaccine construct.•The final vaccine construct contains multiple CD8+ and CD4+ overlapping epitopes•Also, it contains multiple IFN-γ inducing, linear and conformational B cell epitopes.•It forms significant interactions and stable complex with TLR-4/MD.•The DNA vaccine is designed by reverse translation of the final vaccine construct. SARS-CoV-2 causes a severe respiratory disease called COVID-19. Currently, global health is facing its devastating outbreak. However, there is no vaccine available against this virus up to now. In this study, a novel multi-epitope vaccine against SARS-CoV-2 was designed to provoke both innate and adaptive immune responses. The immunodominant regions of six non-structural proteins (nsp7, nsp8, nsp9, nsp10, nsp12 and nsp14) of SARS-CoV-2 were selected by multiple immunoinformatic tools to provoke T cell immune response. Also, immunodominant fragment of the functional region of SARS-CoV-2 spike (400–510 residues) protein was selected for inducing neutralizing antibodies production. The selected regions’ sequences were connected to each other by furin-sensitive linker (RVRR). Moreover, the functional region of β-defensin as a well-known agonist for the TLR-4/MD complex was added at the N-terminus of the vaccine using (EAAAK)3 linker. Also, a CD4 + T-helper epitope, PADRE, was used at the C-terminal of the vaccine by GPGPG and A(EAAAK)2A linkers to form the final vaccine construct. The physicochemical properties, allergenicity, antigenicity, functionality and population coverage of the final vaccine construct were analyzed. The final vaccine construct was an immunogenic, non-allergen and unfunctional protein which contained multiple CD8 + and CD4 + overlapping epitopes, IFN-γ inducing epitopes, linear and conformational B cell epitopes. It could form stable and significant interactions with TLR-4/MD according to molecular docking and dynamics simulations. Global population coverage of the vaccine for HLA-I and II were estimated 96.2% and 97.1%, respectively. At last, the final vaccine construct was reverse translated to design the DNA vaccine. Although the designed vaccine exhibited high efficacy in silico, further experimental validation is necessary.

The authors show that a large fraction of tumour mutations is immunogenic and predominantly recognized by CD4 + T cells; they use these data to design synthetic messenger-RNA-based vaccines specific against tumour mutations, and show that these can reject tumours in mice. A pointer to personalized cancer immunotherapy Sebastian Kreiter et al . demonstrate in three independent murine tumour models that many non-synonymous cancer mutations are immunogenic and, surprisingly, most of these are recognized by CD4 + T cells. Mutation based synthetic mRNA based vaccines are shown to result in rejection of tumors in mice. The authors demonstrate an abundance of mutations predicted to bind to MHC class II in human cancers, suggesting that the tailored immunotherapy approach introduced here may serve as a model for the effective targeting of individual patient's tumours with vaccines produced 'just in time'. Tumour-specific mutations are ideal targets for cancer immunotherapy as they lack expression in healthy tissues and can potentially be recognized as neo-antigens by the mature T-cell repertoire. Their systematic targeting by vaccine approaches, however, has been hampered by the fact that every patient’s tumour possesses a unique set of mutations (‘the mutanome’) that must first be identified. Recently, we proposed a personalized immunotherapy approach to target the full spectrum of a patient’s individual tumour-specific mutations 1 . Here we show in three independent murine tumour models that a considerable fraction of non-synonymous cancer mutations is immunogenic and that, unexpectedly, the majority of the immunogenic mutanome is recognized by CD4 + T cells. Vaccination with such CD4 + immunogenic mutations confers strong antitumour activity. Encouraged by these findings, we established a process by which mutations identified by exome sequencing could be selected as vaccine targets solely through bioinformatic prioritization on the basis of their expression levels and major histocompatibility complex (MHC) class II-binding capacity for rapid production as synthetic poly-neo-epitope messenger RNA vaccines. We show that vaccination with such polytope mRNA vaccines induces potent tumour control and complete rejection of established aggressively growing tumours in mice. Moreover, we demonstrate that CD4 + T cell neo-epitope vaccination reshapes the tumour microenvironment and induces cytotoxic T lymphocyte responses against an independent immunodominant antigen in mice, indicating orchestration of antigen spread. Finally, we demonstrate an abundance of mutations predicted to bind to MHC class II in human cancers as well by employing the same predictive algorithm on corresponding human cancer types. Thus, the tailored immunotherapy approach introduced here may be regarded as a universally applicable blueprint for comprehensive exploitation of the substantial neo-epitope target repertoire of cancers, enabling the effective targeting of every patient’s tumour with vaccines produced ‘just in time’.