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Previous studies have attempted to define human leukocyte antigen (HLA) class II supertypes, analogous to the case for class I, on the basis of shared peptide-binding motifs or structure. In the present study, we determined the binding capacity of a large panel of non-redundant peptides for a set of 27 common HLA DR, DQ, and DP molecules. The measured binding data were then used to define class II supertypes on the basis of shared binding repertoires. Seven different supertypes (main DR, DR4, DRB3, main DQ, DQ7, main DP, and DP2) were defined. The molecules associated with the respective supertypes fell largely along lines defined by MHC locus and reflect, in broad terms, commonalities in reported peptide-binding motifs. Repertoire overlaps between molecules within the same class II supertype were found to be similar in magnitude to what has been observed for HLA class I supertypes. Surprisingly, however, the degree to which repertoires between molecules in the different class II supertypes also overlapped was found to be five to tenfold higher than repertoire overlaps noted between molecules in different class I supertypes. These results highlight a high degree of repertoire overlap amongst all HLA class II molecules, perhaps reflecting binding in multiple registers, and more pronounced dependence on backbone interactions rather than peptide anchor residues. This fundamental difference between HLA class I and class II would not have been predicted on the basis of analysis of either binding motifs or the sequence/predicted structures of the HLA molecules.

Type 1 diabetes (T1D) is one of the most widely studied complex genetic disorders, and the genes in HLA are reported to account for approximately 40–50% of the familial aggregation of T1D. The major genetic determinants of this disease are polymorphisms of class II HLA genes encoding DQ and DR. The DR-DQ haplotypes conferring the highest risk are DRB1 *03:01- DQA1 *05:01- DQB1 *02:01 (abbreviated “DR3”) and DRB1 *04:01/02/04/05/08- DQA1 *03:01- DQB1 *03:02/04 (or DQB1 *02; abbreviated “DR4”). The risk is much higher for the heterozygote formed by these two haplotypes (OR = 16.59; 95% CI, 13.7–20.1) than for either of the homozygotes (DR3/DR3, OR = 6.32; 95% CI, 5.12–7.80; DR4/DR4, OR = 5.68; 95% CI, 3.91). In addition, some haplotypes confer strong protection from disease, such as DRB1 *15:01- DQA1 *01:02- DQB1 *06:02 (abbreviated “DR2”; OR = 0.03; 95% CI, 0.01–0.07). After adjusting for the genetic correlation with DR and DQ, significant associations can be seen for HLA class II DPB1 alleles, in particular, DPB1 *04:02, DPB1 *03:01, and DPB1 *02:02. Outside of the class II region, the strongest susceptibility is conferred by class I allele B*39:06 (OR =10.31; 95% CI, 4.21–25.1) and other HLA-B alleles. In addition, several loci in the class III region are reported to be associated with T1D, as are some loci telomeric to class I. Not surprisingly, current approaches for the prediction of T1D in screening studies take advantage of genotyping HLA-DR and HLA-DQ loci, which is then combined with family history and screening for autoantibodies directed against islet-cell antigens. Inclusion of additional moderate HLA risk haplotypes may help identify the majority of children with T1D before the onset of the disease.

Aims/hypothesisWe aimed to characterise and quantify the expression of HLA class II (HLA-II) in human pancreatic tissue sections and to analyse its induction in human islets.MethodsWe immunostained human pancreatic tissue sections from non-diabetic (n = 5), autoantibody positive (Aab+; n = 5), and type 1 diabetic (n = 5) donors, obtained from the Network of Pancreatic Organ Donors (nPOD), with HLA-II, CD68 and insulin. Each tissue section was acquired with a widefield slide scanner and then analysed with QuPath software. In total, we analysed 7415 islets that contained 338,480 cells. Widefield microscopy was further complemented by high resolution imaging of 301 randomly selected islets, acquired using a Zeiss laser scanning confocal (LSM880) to confirm our findings. Selected beta cells were acquired in enhanced resolution using LSM880 with an Airyscan detector. Further, we cultured healthy isolated human islets and reaggregated human islet microtissues with varying concentrations of proinflammatory cytokines (IFN-γ, TNF-α and IL-1β). After proinflammatory cytokine culture, islet function was measured by glucose-stimulated insulin secretion, and HLA-I and HLA-II expression was subsequently evaluated with immunostaining or RNA sequencing.ResultsInsulin-containing islets (ICIs) of donors with type 1 diabetes had a higher percentage of HLA-II positive area (24.31%) compared with type 1 diabetic insulin-deficient islets (IDIs, 0.67%), non-diabetic (3.80%), and Aab+ (2.31%) donors. In ICIs of type 1 diabetic donors, 45.89% of the total insulin signal co-localised with HLA-II, and 27.65% of the islet beta cells expressed both HLA-II and insulin, while in non-diabetic and Aab+ donors 0.96% and 0.59% of the islet beta cells, respectively, expressed both markers. In the beta cells of donors with type 1 diabetes, HLA-II was mostly present in the cell cytoplasm, co-localising with insulin. In the experiments with human isolated islets and reaggregated human islets, we observed changes in insulin secretion upon stimulation with proinflammatory cytokines, as well as higher expression of HLA-II and HLA-I when compared with controls cultured with media, and an upregulation of HLA-I and HLA-II RNA transcripts.Conclusions/interpretationAfter a long-standing controversy, we provide definitive evidence that HLA-II can be expressed by pancreatic beta cells from patients with type 1 diabetes. Furthermore, this upregulation can be induced in vitro in healthy isolated human islets or reaggregated human islets by treatment with proinflammatory cytokines. Our findings support a role for HLA-II in type 1 diabetes pathogenesis since HLA-II expressing beta cells can potentially become a direct target of autoreactive CD4+ lymphocytes.

Immunotherapy is currently recognized as the fourth modality in cancer therapy. CTL can detect cancer cells via complexes involving human leukocyte antigen (HLA) class I molecules and peptides derived from tumor antigens, resulting in antigen‐specific cancer rejection. The peptides may be predicted in silico using machine learning‐based algorithms. Neopeptides, derived from neoantigens encoded by somatic mutations in cancer cells, are putative immunotherapy targets, as they have high tumor specificity and immunogenicity. Here, we used our pipeline to select 278 neoepitopes with high predictive “SCORE” from the tumor tissues of 46 patients with hepatocellular carcinoma or metastasis of colorectal carcinoma. We validated peptide immunogenicity and specificity by in vivo vaccination with HLA‐A2, A24, B35, and B07 transgenic mice using ELISpot assay, in vitro and in vivo killing assays. We statistically evaluated the power of our prediction algorithm and demonstrated the capacity of our pipeline to predict neopeptides (area under the curve = 0.687, P < 0.0001). We also analyzed the potential of long peptides containing the predicted neoepitopes to induce CTLs. Our study indicated that the short peptides predicted using our algorithm may be intrinsically present in tumor cells as cleavage products of long peptides. Thus, we empirically demonstrated that the accuracy and specificity of our prediction tools may be potentially improved in vivo using the HLA transgenic mouse model. Our data will help to design feedback algorithms to improve in silico prediction, potentially allowing researchers to predict peptides for personalized immunotherapy. Using HLA‐transgenic mice, we assessed in vivo immunogenicity of neoantigen peptides by our prediction pipeline from patient tissues. Our results demonstrated that our prediction pipeline could propose immunogenic candidates; however, the power prediction is still insufficient for clinical application. Assessment of immunogenicity in an in vivo model is essential for clinical efficiency of peptide vaccines.

Preeclampsia (PE) is a serious gestational complication that affects the lives of the mother and the child. Women with PE showed higher levels of pro-inflammatory cytokines secreted by leukocytes compared with women with normal pregnancies. The differences are most noticeable in the percentage of CD16+ monocytes, although the mechanism underlying this increase remains unclear. The CD16 receptor is critical for antibody-dependent cellular cytotoxicity, and by binding to antibodies on the surface of target cells, it activates their death. In this study, we examined the effect of soluble placental factors on the expression of CD16 monocytes and the potential role the soluble form of human leukocyte antigen (HLA) has on CD16 monocyte expression. At the first stage of our study, we collected samples of placental villi fragments from 58 pregnant women (38 women with PE and 20 with a healthy pregnancy). Then we studied the effect of placental villus-conditioned culture medium on CD16 expression by monocytes derived from the same women. It was shown that the content of CD16+ monocytes increased significantly in women with PE within 3 h and to a lesser extent in women with a healthy pregnancy ( = 0.009). Also, the addition of the recombinant histocompatibility HLA-B to the placental villus-conditioned culture medium blocks the induction of CD16 expression on monocytes. At the second stage of our study, we typed HLA class I and class II alleles in the umbilical cord blood samples and the venous blood samples taken from 38 women with PE and 40 women with a normal pregnancy. It was found that certain HLA class II alleles predominate in women with preeclampsia. The DRB1*01:01:01G allele showed the greatest difference ( < 0.001). Analyzing five alleles simultaneously makes it possible to predict the PE with AUC = 0.76. Evaluation of unique children's alleles also showed that class II alleles have greater differences among them than class I alleles. The DQB1*06:03:01G allele had the greatest differences with = 0.03 (the number was higher in the control group). Performing an analysis of four alleles of children simultaneously allowed us to predict PE with an AUC of 0.64. This work suggests that the activation of CD16+ monocyte expression occurs due to the interaction of soluble placental antigens with monocytes. The most likely way to activate CD16 expression on monocytes is by HLA class II (both maternal and fetal) interaction with CD4 receptors on the surface of monocytes, whereas HLA class I is capable of blocking this process. Evaluation of maternal HLA alleles may be a significant marker for predicting PE.

Human leukocyte antigen (HLA) class I and II are known to have association with severe cutaneous adverse reactions (SCARs) when exposing to certain drug treatment. Due to genetic differences at population level, drug hypersensitivity reactions are varied, and thus common pharmacogenetics markers for one country might be different from another country, for instance, is associated with carbamazepine (CBZ)-induced SCARs in European and Japanese while is associated with CBZ-induced Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN) among Taiwanese and Southeast Asian. Such differences pose a major challenge to prevent drug hypersensitivity when pharmacogenetics cannot be ubiquitously and efficiently translated into clinic. Therefore, a population-wide study of the distribution of HLA-pharmacogenetics markers is needed. This work presents a study of Thai alleles on both class I and II genes from 470 unrelated Thai individuals by means of polymerase chain reaction sequence-specific oligonucleotide (PCR-SSO) in which oligonucleotide probes along the stretches of genes were genotyped. These 470 individuals were selected according to their regional locations, which were from North, Northeast, South, Central, and a capital city, Bangkok. Top ranked alleles in Thai population include (26.06%), (14.04%), (17.13%), (15.32%), (24.89%), and (21.28%). The results revealed that the distribution of HLA-pharmacogenetics alleles from the South had more HLA-B75 family that a typical pharmacogenetics test for SJS/TEN screening would not cover. Besides the view across the nation, when compared alleles from Thai population with alleles from both European and Asian countries, the distribution landscape of -associated drug hypersensitivity across many countries could be observed. Consequently, this pharmacogenetics database offers a comprehensive view of pharmacogenetics marker distribution in Thailand that could be used as a reference for other Southeast Asian countries to validate the feasibility of their future pharmacogenetics deployment.

Introduction: Although, several studies have assessed the association of HLA Class I and II genes with inclusion body myositis (IBM), results were inconsistent and between-studies heterogeneity needs to be investigated. Objectives: The aim of this review was to summarize existing data on the contribution of HLA-DRB1 and HLA-B alleles to IBM susceptibility and to investigate the between-studies heterogeneity by subgroup analyses and meta-regressions. Design: This study was performed according to the PRISMA guidelines for systematic reviews and meta-analyses. Methods: An electronic literature search for eligible studies among all papers published prior to January 29, 2025, was conducted through PubMed, EMBASE, Web of science, and Scopus databases. Meta-analyses together with subgroup analyses and meta-regressions were performed for the two following HLA genes: HLA-DRB1 and HLA-B. Results: Combined analyses revealed a significant increase in IBM risk conferred by the HLA-DRB1*03 allele (9.21 (7.05–12.01)), the DRB*03:01 allele (8.44 (6.85–10.41)), the DRB1*01 allele (2.31 (1.82–2.93)), the DRB1*01:01 allele (2.63 (1.95–3.55)), the DRB1*15:02 allele (3.49 (2.12–5.75)), the B*08 allele (4.05 (2.58–6.38)), and the DQB1*02 allele (6.62 (4.5–9.74)), all p-values < 0.001. In addition, the DRB1*15:01 allele was found to be protective against IBM in all populations (0.48 (0.32–0.72)). Conversely, the DRB*11 allele was not associated with IBM risk, OR (95% CI) = 0.91 (0.54–1.51), p = 0.703. Conclusion: This meta-analysis demonstrated that HLA-DRB1, DQB1, and B loci could play a major role in IBM pathogenesis. Registration: This review has been registered on PROSPERO on June 25, 2024: CRD42024557948, Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024557948

Objectives Inducible T cell costimulator (ICOS) is a CD28-family costimulatory receptor with bidirectional therapeutic effects on antitumor immunity, and HLA-mediated tumor recognition is essential for effective T cell responses. However, their clinicopathological significance in lung adenocarcinoma (LUAD) is not fully understood. We investigated subset-specific pattern of ICOS expression and examined whether ICOS + tumor-infiltrating lymphocyte (TIL) density and tumor HLA expression provide immune context and prognostic information in LUAD. Materials and Methods We examined 228 resected LUADs by immunohistochemistry. ICOS + TIL density and HLA class I and HLA-DR status were compared with the densities of CD8 + , CD3 + CD8 − , and FOXP3 + TILs and with postsurgical outcomes. Subset-specific ICOS expression was evaluated using multiplex pseudocolored immunohistochemistry in 10 representative cases selected from the ICOS + TIL-high group and validated using a publicly available single-cell RNA-seq dataset. Results ICOS + TIL density correlated with each T cell subset. Multiplex analysis showed the highest ICOS positivity among Tregs, followed by CD4 + non-Tregs and CD8 + TILs. Because CD4 + non-Tregs were numerically predominant, ICOS + CD4 + non-Tregs constituted the largest ICOS + fraction. Single-cell RNA-seq analysis corroborated these findings. ICOS + TIL density was significantly higher in HLA-DR-strong tumors, and tumor HLA class I and HLA-DR were associated with longer recurrence-free survival. ICOS had no overall prognostic impact; however, among HLA-DR-strong tumors, ICOS-high patients tended toward longer cancer-specific survival. Conclusion In LUAD, ICOS + TIL density largely reflects ICOS + CD4 + non-Treg infiltration and is enriched in HLA-DR-strong tumors. Tumor HLA expression was associated with favorable prognosis, and ICOS may have context-dependent clinical significance that warrants further investigation.

Background A recent paper by Jin et al. reveals an unexpected role of the Aryl Hydrocarbon Receptor (AHR), so far considered an environmental sensor. The authors demonstrate that AHR transactivates CIITA, thereby up-regulating antigen-presenting HLA-II molecules in cutaneous melanoma. Main body In this commentary, we review the evidence supporting this original observation and discuss its potential biological implications. Conclusions These findings suggest that the environmental exposome and HLA-II-mediated antigen presentation should be considered interconnected aspects of self-non-self-discrimination, with potentially important implications for tumor (immune) surveillance.

The use of minimal peptide sets offers an appealing alternative for design of vaccines and T cell diagnostics compared to conventional whole protein approaches. T cell immunogenicity towards peptides is contingent on binding to human leukocyte antigen (HLA) molecules of the given individual. HLA is highly polymorphic, and each variant typically presents a different repertoire of peptides. This polymorphism combined with pathogen diversity challenges the rational selection of peptide sets with broad immunogenic potential and population coverage. Here we propose PopCover-2.0, a simple yet highly effective method, for resolving this challenge. The method takes as input a set of (predicted) CD8 and/or CD4 T cell epitopes with associated HLA restriction and pathogen strain annotation together with information on HLA allele frequencies, and identifies peptide sets with optimal pathogen and HLA (class I and II) coverage. PopCover-2.0 was benchmarked on historic data in the context of HIV and SARS-CoV-2. Further, the immunogenicity of the selected SARS-CoV-2 peptides was confirmed by experimentally validating the peptide pools for T cell responses in a panel of SARS-CoV-2 infected individuals. In summary, PopCover-2.0 is an effective method for rational selection of peptide subsets with broad HLA and pathogen coverage. The tool is available at https://services.healthtech.dtu.dk/service.php?PopCover-2.0 .