The use of virtual crossmatch for HLA antigen compatibility assessment before transplantation has become common practice in transplantation medicine. The accuracy of virtual crossmatch relies on accurate and complete donor HLA antigen typing and up-to-date patient HLA antigen antibody characterization. Here, we report a case in which anti-HLA-DP antibodies were detected in the patient, and the donor HLA-DPB1*29:01 was not included in the bead panel of Luminex-based single antigen bead assay (LSA). The deceased donor HLA antigen typing results were downloaded from the United Network for Organ Sharing. Serum samples were tested for HLA antibodies using LSA. Epitope analysis was performed manually based on alignment of HLA-DP using the Sequence Alignment Tool from the IPD-IMGT/HLA database (https://www.ebi.ac.uk/ipd/imgt/hla/). The LSA showed that anti-HLA-DP3, DP6, DP9, DP11, DP14, DP15, DP17, and DP20 were positive. HLA antigen typing with real-time polymerase chain reaction showed that the donor carried HLA-DPB1*29:01. Epitope analysis showed that the anti-HLA-DPB1*29:01 donor-specific antibody was present in this patient. The LSA can miss antibodies against HLA antigens not represented by the beads, leading to false-negative results for donor-specific antibodies. Failure to consider the possibility of unrepresented HLA proteins may potentially lead to incorrect clinical decision. Epitope analysis may help predict reactivity to HLA antigens not present on LSA beads.
Mismatched allogeneic haematopoietic stem cell transplants (HSCT) are complicated by the presence of pre-existing HLA-specific antibodies targeting the mismatched HLA antigens (DSAs). Data indicates that the presence of DSAs pre-transplant, termed HLA incompatible HSCT, is associated with inferior outcomes and graft failure. Whilst studies acknowledge that DSAs should be avoided there is limited information regarding the impact of specific DSAs and their levels on HSCT outcomes. There is also a recognised lack of knowledge and methods which allow the immunological risk of HLA incompatible HSCT to be defined, with a large volume of data being extrapolated from solid organ transplant data. We have established a stem cell specific flow cytometry crossmatch (SC-FCXM) for the in vitro assessment of the binding capacity of HLA-specific antibodies to CD34+ stem cells. A library of HLA typed expanded human CD34+ progenitor cells from cord blood (CB-CD34+) was generated and used to assess HLA-specific antibody binding of 86 serum samples from the National External Quality Assurance Scheme (NEQAS) Histocompatibility and Immunogenetics crossmatching 2B external proficiency testing scheme issued between 2023 and 2025. Sera were analysed using LABScreen Single Antigen (LSSAg) Class I and II and donor specific HLA antibodies (DSAs) were identified for each CB-CD34+ and serum combination. A range of DSAs targeting single HLA antigens, plus multiple HLA-specific Class I, Class II or a combination of Class I and II antibodies based on mean fluorescence intensity (MFI) was examined. The impact of increasing DSA MFI on SC-FCXM reactivity was determined by correlation and regression studies comparing cumulative peak LSSAg MFI versus median fluorescence intensity of anti-human IgG APC as determined by the SC-FCXM (APC Median SC-FCXM). As LSSAg MFI of DSAs targeting HLA-A (p = 0.0001), -B (p = 0.0001) and -DRB1 (p = 0.0155) increased, there was significant correlation with APC Median SC-FCXM, but no correlation (p > 0.05) between LSSAg MFI and APC Median SC-FCXM for HLA-C, -DQB1, -DQA1 or -DPB1. A significant correlation (p ≤ 0.05) was observed for multiple HLA Class I (p = 0.0005), Class II (p = 0.0001), plus combinations of Class I and II DSAs (p = 0.0013) between combined LSSAg MFI and APC Median SC-FCXM. The extrapolation of this preliminary data has provided an indication of which DSAs and their levels (as determined by LSSAg MFI) cause FCXM reactivity against CD34+ stem cells, which could prove to be relevant in HLA incompatible HSCT. However, the assay currently remains a proof-of-concept and further work is required to establish clinical correlation of the results to patient outcomes.
HLA-E presented cancer peptides can be promising cancer therapy targets, as HLA-E is minimally polymorphic and widely expressed across human populations and cancer types. However, systematic discovery of cancer associated HLA-E peptides has been constrained by sparse training data and the technical difficulty of HLA-E immunopeptidomics. Here we develop an integrated HLA-E antigen discovery platform combining a deep learning prediction model, pooled mammalian cell screening, peptide-HLA-E stability validation, and mass spectrometry. We introduce MHC Attention, a neural network that learns allele-level attention over candidate MHC alleles in multi-allele immunopeptidomics datasets, enabling direct training on patient-derived MHC peptide data. Screening an approximately 6,000-peptide HLA-E library identified stable HLA-E-presented peptides and generated HLA-E-specific training data that improved prediction performance of MHC Attention. Combining our screening assays and improved prediction algorithm, we discovered novel HLA-E-presented cancer peptides, including candidates derived from ETV4, WT1, RNF43 and BMP8A, with orthogonal support from stability assays or immunopeptidomics. These results establish a scalable framework for HLA-E peptide target discovery and provide candidate targets for broadly applicable peptide-HLA-directed cancer immunotherapies. MHC Attention 2.0 can be accessed online via https://vcreate.io/mhcattention .
Immune checkpoint inhibitors (ICIs) can induce severe immune-related adverse events (irAEs), including type 1 diabetes (ICI-T1D) and interstitial lung disease (ICI-ILD); however, predictive genetic markers have not yet been fully elucidated. Accordingly, this study aimed to identify genetic polymorphisms associated with susceptibility to nivolumab-induced ICI-T1D and ICI-ILD. To address this, whole-genome sequencing using next-generation sequencing was performed on genomic DNA obtained from patients recruited from multiple centers nationwide who developed ICI-T1D (n = 14), ICI-ILD (n = 58), or no irAEs (ICI-Control, n = 72) after initiation of nivolumab therapy, followed by a genome-wide association study (GWAS). The primary GWAS identified an association signal within the HLA region on chromosome 6 in the comparison between the ICI-T1D and ICI-Control groups, whereas no significant associations were detected in analyses involving the ICI-ILD group. This signal was accompanied by an increased rate of missing genotypes, most prominently around the HLA-DRB5 locus, suggesting underlying structural and haplotypic complexity within the HLA-DR region that cannot be fully resolved by reference genome-based short-read analysis alone, leading to a post hoc analysis focusing on disease-susceptibility alleles of HLA-DRB3/4/5 and their haplotypic structures in relation to HLA-DRB1, which is in strong linkage disequilibrium with these loci, with comparisons to a healthy reference population (General Controls; n = 1,320). 24 distinct HLA-DRB1 alleles and 11 distinct HLA-DRB3/4/5 alleles (including null types), and 30 distinct haplotypes were identified. Compared with General Controls, in the ICI-T1D group, HLA-DRB1*04:05:01, DRB1*08:02:01, and DRB4*01:03:01 were associated with susceptibility; in addition, the haplotypes DRB1*04:05:01-DRB4*01:03:01, DRB1*08:02:01-DRB3/4/5 null, and DRB1*09:01:02-DRB4*01:03:01 were also associated with susceptibility. For the ICI-ILD group, HLA-DRB1*08:03:02 was associated with susceptibility, and the haplotypes DRB1*04:10:03-DRB4*01:03:01 and DRB1*08:03:02-DRB3/4/5 null were also associated with susceptibility. Overall, these findings indicate that HLA class II polymorphisms, including DRB3/4/5, contribute to genetic susceptibility to ICI-related irAEs and support the extension of HLA typing beyond DRB1 to better elucidate the immunogenetic basis of these adverse events.
Cytokeratin-positive interstitial reticulum cell (CIRC) tumor, a subtype of fibroblastic reticular cell tumor (FRCT), is an extremely rare primary neoplasm of lymph nodes and soft tissue, with limited understanding of its clinicopathological and molecular features. This case is the first identification of human leukocyte antigen loss of heterozygosity (HLA LOH) in CIRC tumor, which provides novel insights into immune evasion mechanisms and potential therapeutic implications. A 67-year-old female presented with a local recurrence seven years after initial resection of a CIRC tumor on her right shoulder. Physical examination revealed a firm, poorly mobile subcutaneous mass (12cm×8cm). Imaging confirmed a right parascapular mass with bone destruction. Histologically, the recurrent tumor consisted of spindle and epithelioid cells arranged in storiform and sheet-like patterns, with extensive necrosis and a mitotic count of 3 per 10 high-power fields. Immunohistochemically, tumor cells diffusely expressed cytokeratins, vimentin, CD68, CD163, and EMA, with focal expression of SMA, S-100, calponin, and CD3, but were negative for CD21, CD35, CD1a, ALK, and HHV8. The Ki-67 index was 25%. Whole-exome sequencing identified 30 single-nucleotide variants and 7 indels (variant allele frequencies 2.17%-12.6%), copy number gains on chromosomes 7, 11, and 14, and microsatellite stability. Notably, two HLA LOH events affecting HLA-B39:01:01:01 and HLA-C07:02:01:01 were detected. No disease progression was observed during follow-up. This is the first report of HLA LOH in FRCT/CIRC tumor. The key take-away lesson is that HLA LOH represents a potential immune evasion mechanism, which may render single-agent immune checkpoint inhibitors ineffective and thus guide alternative immunotherapeutic strategies. Chromosomal instability appears to be a prominent genomic feature of FRCT. These findings expand the molecular landscape of this rare tumor and underscore the value of comprehensive genomic profiling in guiding individualized treatment.
Pediatric asthma (PA) is a prevalent chronic respiratory disease. Emerging evidence suggests that dysregulated macrophage heterogeneity and immune-metabolic crosstalk contribute to disease pathogenesis, yet specific molecular nodes linking innate immune dysfunction to PA remain unidentified. This study aimed to identify and characterize immune checkpoint-related candidate key genes in PA. Bulk RNA-sequencing data from airway epithelium of PA patients (training set GSE152004) were analyzed for differential expression, followed by intersection with immune checkpoint-related genes. Four machine learning algorithms (SVM-RFE, Boruta, LASSO, and XGBoost) were applied to screen candidate key genes, which were further validated in an independent dataset (GSE65204). A nomogram was constructed to evaluate diagnostic value. Functional enrichment, immune infiltration, and regulatory network analyses were performed. In vitro IL-13 stimulation of bronchial epithelial cells and patient peripheral blood mononuclear cell samples were used for experimental validation. Single-cell RNA-seq data (GSE254127) were analyzed for cell typing, macrophage subclustering, pseudotime trajectory, and cell-cell communication. HLA-DPA1 and HLA-DPB1 were identified as candidate key genes by consensus of all four algorithms. Both were significantly downregulated in PA and showed high diagnostic value (nomogram). Downregulation of HLA-DPA1/DPB1 correlated with attenuated antigen presentation and enhanced metabolic dysfunction. IL-13-treated bronchial epithelial cells and patient samples confirmed reduced mRNA and protein expression. Exploratory single-cell analysis revealed that HLA-DPA1/DPB1 were enriched in macrophages, specifically a Macro2 subset characterized by metabolic and stress-related functions-highlighting macrophage heterogeneity in innate immune regulation. Pseudotime trajectory suggested a shift from immune-activated toward metabolically stressed states. Cell-cell communication analysis identified epithelial cells as primary signal senders, with macrophages and dendritic cells as central receivers, and the MIF signaling axis as a key intercellular bridge. This multi-level integrated transcriptomic analysis identified HLA-DPA1 and HLA-DPB1 as candidate key genes in childhood asthma, and reveals their potential role in immune-metabolic dysregulation centered on macrophage functional heterogeneity. Our data are consistent with a potential role for these genes in immune-metabolic dysregulation centered on macrophage functional heterogeneity, although direct functional validation is required to establish causality. These findings provide new insights into innate immune circuits in childhood asthma and lay a foundation for potential molecular targets for future precision therapeutic strategies.
MEFV mutations are prevalent in Mediterranean populations, yet their potential role in modulating ankylosing spondylitis (AS) remains unclear. We investigated whether MEFV variants act as susceptibility factors or modify disease phenotype via interaction with HLA-B27. In this cross-sectional study, 129 AS patients meeting the modified New York criteria, 51 rheumatoid arthritis controls, and 58 healthy controls were genotyped for 11 MEFV mutations using pyrosequencing. Radiographic severity was assessed using the Bath Ankylosing Spondylitis Radiographic Index (BASRI), scored by a blinded radiologist. Multivariate linear regression identified independent predictors of structural involvement, incorporating a multiplicative interaction term (HLA-B27×MEFV). Bonferroni correction was applied to post-hoc analyses. MEFV carrier frequencies were similar across groups (29.5% in AS, 29.4% in RA, 22.4% in controls; p = 0.582), indicating no primary role in susceptibility. In multivariate analysis without interaction, disease duration (β = 0.379, p < 0.001) and male sex (β = 0.214, p = 0.017) independently predicted BASRI scores, whereas HLA-B27 and MEFV alone were not significant. Including the interaction term revealed a significant HLA-B27×MEFV effect (β = 0.243, p = 0.012), improving model fit (ΔR2 = 0.034). Double-positive patients had higher BASRI scores than double-negatives (7.80 ± 4.15 vs. 4.80 ± 3.50; p = 0.008).      . MEFV variants do not increase AS susceptibility but are associated with greater structural involvement in HLA-B27-positive patients. This interaction identifies a high-risk genetic subgroup in endemic populations, highlighting implications for early identification and targeted monitoring.
HLA-DRB4*01:229 differs from HLA-DRB4*01:03:01:17 by one nucleotide substitution in codon 156 of exon 3.
HLA-DPA1*01:248 and -DPA1*02:01:41, two novel HLA-DPA1 alleles detected by next generation sequencing.
Ten novel HLA class I alleles were detected during the routine HLA typing process.
HLA-C*02:02:81 differs from HLA-C*02:02:02:01 by one nucleotide substitution in codon 294 in exon 5.
暂无摘要（点击查看详情）
暂无摘要（点击查看详情）
暂无摘要（点击查看详情）
暂无摘要（点击查看详情）
Platelet transfusion refractoriness (PTR) represents a major challenge in the transfusion support of patients with severe thrombocytopenia, particularly those with hematologic malignancies, intensive chemotherapy, or hematopoietic stem cell transplantation. Although nonimmune mechanisms account for the majority of cases, immune-mediated PTR caused by alloantibodies against platelet antigens, most commonly human leukocyte antigen (HLA) class I molecules, remains clinically important. This review summarizes current knowledge on the definition, mechanisms, diagnostic evaluation, and management of immune PTR. The immunologic basis of platelet destruction in immune PTR involves several mechanisms mediated by anti-HLA antibodies, including Fc receptor-dependent phagocytosis, complement activation, and antibody-induced platelet activation. Diagnostic evaluation integrates clinical assessment with laboratory detection of HLA antibodies, molecular HLA typing, and platelet crossmatching. Clinical management primarily relies on the provision of compatible platelet products, including HLA-matched platelets, antibody-specific antigen-negative platelet units, or crossmatched platelet concentrates. In selected cases, additional testing for antibodies against human platelet antigens (HPAs) may be required. Preventive strategies such as leukoreduction have substantially reduced the incidence of alloimmunization, although immune PTR continues to occur in a subset of transfusion-dependent patients. Emerging strategies aimed at improving transfusion outcomes include approaches to reduce platelet immunogenicity, development of HLA-deficient platelets, and pharmacologic interventions targeting antibody-mediated platelet clearance. A better understanding of the mechanisms underlying immune PTR may help refine diagnostic algorithms and expand therapeutic options for patients requiring long-term platelet transfusion support.
Human leukocyte antigen (HLA) polymorphisms are central to anti-infective pharmacogenetics and to inter-individual variability in infection outcomes and vaccine responses, but clinical relevance depends on whether an association changes treatment or prevention decisions. This narrative review is organized around two complementary pillars: first, severe, typically T cell-mediated adverse drug reactions to anti-infective agents, where HLA can support prevention when genetic effect, phenotype precision, and therapeutic alternatives converge; and second, selected, replicated HLA-region associations with infection outcomes or vaccine immunogenicity, where biological effects may be robust yet individual-level clinical translation is often limited. Within the adverse drug reaction pillar, the clearest preventive paradigm remains HLA-B*57:01-guided abacavir prescribing, with additional high-signal examples including dapsone hypersensitivity and flucloxacillin-induced liver injury that illustrate how large effect sizes do not always justify routine screening. Within the infection and vaccine pillar, HIV, HCV, and hepatitis B vaccine response provide the strongest evidence that HLA shapes clinically relevant host-response heterogeneity. Across both domains, the key pharmacological distinction is between mechanistically persuasive associations and those that are sufficiently robust, transportable, and decision-relevant to change practice.
Alzheimer's disease (AD) is a multifactorial neurodegenerative condition in which accumulating genetic and molecular evidence implicates dysregulation of peripheral immune processes in disease pathogenesis. Nevertheless, the contribution of distinct peripheral immune cell subsets and associated gene regulatory landscapes to AD risk remains incompletely defined. To address this gap, we integrated single-cell expression quantitative trait loci (sc‑eQTL) data from the OneK1K cohort with AD GWAS summary statistics. We systematically interrogated immune cell-specific genes for their contributions to AD risk by integrating genetic causal inference with Bayesian colocalization analyses, and identified 24 eGenes that passed both the MR significance threshold (P < 0.05) and the criterion for strong shared genetic signals (PP.H4 > 0.8). Notable candidates included GATS, HLA-DOB, HLA-DQA1, PM20D1, and others, with each gene demonstrating a cell-type-specific association restricted to its corresponding immune cell type, such as monocytes, CD8 + T cells, or B cells. Independent peripheral blood single-cell transcriptomic data further supported disease-associated shifts in cell-type-specific expression patterns in AD. Phenome-wide association studies (PheWAS) indicated limited associations with off-target traits, indicating a favorable safety profile for therapeutic intervention, with the exceptions of B4GALNT3, PM20D1, and CNN2. Integration of immune gene targets with pharmacological databases yielded three candidate compound, including NSC321521 (targeting HLA-DQA1), phenoxybenzamine (targeting GSTP1), and rimexolone (targeting BIN1). Among these compounds, Predicted blood-brain barrier permeability was observed only for phenoxybenzamine and rimexolone, with docking studies indicating stable interactions, such as those between NSC321521 and HLA-DQA1, phenoxybenzamine and GSTP1, and rimexolone and BIN1. This integrative approach highlights key immune‑cell‑specific genes involved in AD and proposes repurposable drugs with central nervous system potential, paving the way for more targeted immunomodulatory strategies in AD.
Deciphering how human T cells recognise peptide-HLA (pHLA) complexes underpins next-generation vaccines and personalised immunotherapies, yet extreme sequence diversity and paired-chains interdependence still hamper reliable in silico prediction of T-cell receptor (TCR) specificity. To overcome these hurdles, we built TCRBinder, a paired-chain-aware deep model with a multi-branch encoder that routes each molecular component through dedicated transformer-based modules to capture contextual signals in both HLA pseudo-sequences and antigenic peptides while simultaneously processing the TCR [Formula: see text] and [Formula: see text] chains. This design captures the synergistic interaction between paired chains to emulate peptide-HLA-TCR (PHT) interactions and expose residue-level contact motifs. Across PHT and peptide-TCR (pTCR) benchmarks, the model delivered state-of-the-art performance (AUC-ROC = 0.911, AUPR = 0.791 for the PHT task) and remained superior on multiple independent datasets. We tracked the dynamics of clonal expansion and, in a large SARS-CoV-2 repertoire containing completely unseen peptides, improved the AUC-ROC by up to 16.3% over the leading alternatives. Moreover, TCRBinder provided mechanistic insights by pinpointing contact hotspots and quantifying residue contributions to binding probability. These capabilities position TCRBinder as a versatile tool for rational antigen discovery, immunotherapy stratification, and neoantigen vaccine design.
Tumor-associated antigens (TAAs) are non-mutated antigenic peptides expressed in cancer tissue at abnormally high levels but in normal tissue either at negligible levels, during only particular developmental stages, or in a tissue-restricted manner. The shared nature of TAAs across patients makes them attractive targets for off-the-shelf immunotherapies. However, no studies have comprehensively surveyed the TAA potential of all possible wild-type peptides originating from cancer-associated genes. In this study of 16 cancer tissue types and 39 normal tissue types, we analyzed the expression profiles of protein-coding genes to identify those with aberrantly high RNA levels across multiple solid tumor types and low RNA levels across all normal tissue types examined. We then developed a score to quantify tumor specificity of gene expression. Compared to previously reported TAA genes, those we identified exhibited substantially greater tumor specificity. Seven of these genes demonstrated consistently elevated expression in at least five tumor types and minimal expression across all non-immune-privileged normal tissues. To assess Human Leukocyte Antigen (HLA) class I presentation potential of the multi-cancer-associated genes, we computationally predicted the binding affinities between the most common class I HLA alleles and all possible wild-type TAA epitopes of 8-11 amino acids arising from those genes. We then applied rigorous filtering criteria to prioritize the most promising multi-cancer TAA peptide candidates and evaluated their HLA binding and cell-surface presentation using T2 and immunopeptidome analysis. Our results highlight new potential targets for multi-cancer immunotherapies.