IPD-IMGT/HLA Database

Orthanq: transparent and uncertainty-aware haplotype quantification with application in HLA-typing

BACKGROUND

Identification of human leukocyte antigen (HLA) types from DNA-sequenced human samples is important in organ transplantation and cancer immunotherapy and remains a challenging task considering sequence homology and extreme polymorphism of HLA genes.

RESULTS

We present Orthanq, a novel statistical model and corresponding application for transparent and uncertainty-aware quantification of haplotypes. We utilize our approach to perform HLA typing while, for the first time, reporting uncertainty of predictions and transparently observing mutations beyond reported HLA types. Using 99 gold standard samples from 1000 Genomes, Illumina Platinum Genomes and Genome In a Bottle projects, we show that Orthanq can provide overall superior accuracy and shorter runtimes than state-of-the-art HLA typers.

CONCLUSIONS

Orthanq is the first approach that allows to directly utilize existing pangenome alignments and type all HLA loci. Moreover, it can be generalized for usages beyond HLA typing, e.g. for virus lineage quantification. Orthanq is available under https://orthanq.github.io .

Transformers meets neoantigen detection: a systematic literature review

Cancer immunology offers a new alternative to traditional cancer treatments, such as radiotherapy and chemotherapy. One notable alternative is the development of personalized vaccines based on cancer neoantigens. Moreover, Transformers are considered a revolutionary development in artificial intelligence with a significant impact on natural language processing (NLP) tasks and have been utilized in proteomics studies in recent years. In this context, we conducted a systematic literature review to investigate how Transformers are applied in each stage of the neoantigen detection process. Additionally, we mapped current pipelines and examined the results of clinical trials involving cancer vaccines.

Frequency-dependent selection of neoantigens fosters tumor immune escape and predicts immunotherapy response

Cancer is an evolutionary process shaped by selective pressure from the microenvironments. However, recent studies reveal that certain tumors undergo neutral evolution where there is no detectable fitness difference amongst the cells following malignant transformation. Here, through computational modeling, we demonstrate that negative frequency-dependent selection (or NFDS), where the immune response against cancer cells depends on the clonality of neoantigens, can lead to an immunogenic landscape that is highly similar to neutral evolution. Crucially, NFDS promotes high antigenic heterogeneity and early immune evasion in hypermutable tumors, leading to poor responses to immune checkpoint blockade (ICB) therapy. Our model also reveals that NFDS is characterized by a negative association between average clonality and total burden of neoantigens. Indeed, this unique feature of NFDS is common in the whole-exome sequencing (WES) datasets (357 tumor samples from 275 patients) from four melanoma cohorts with ICB therapy and a non-small cell lung cancer (NSCLC) WES dataset (327 tumor samples from 100 patients). Altogether, our study provides quantitative evidence supporting the theory of NFDS in cancer, explaining the high prevalence of neutral-looking tumors. These findings also highlight the critical role of frequency-dependent selection in devising more efficient and predictive immunotherapies.

Long-read RNA-seq demarcates cis- and trans-directed alternative RNA splicing

Genetic regulation of alternative splicing constitutes an important link between genetic variation and disease. Nonetheless, RNA splicing is regulated by both cis-acting elements and trans-acting splicing factors. Determining splicing events that are directed primarily by the cis- or trans-acting mechanisms will greatly inform our understanding of the genetic basis of disease. Here, we show that long-read RNA-seq, combined with our new method isoLASER, enables a clear segregation of cis- and trans-directed splicing events for individual samples. The genetic linkage of splicing is largely individual-specific, in stark contrast to the tissue-specific pattern of splicing profiles. Analysis of long-read RNA-seq data from human and mouse revealed thousands of cis-directed splicing events susceptible to genetic regulation. We highlight such events in the HLA genes whose analysis was challenging with short-read data. We also highlight novel cis-directed splicing events in Alzheimer's disease-relevant genes such as MAPT and BIN1. Together, the clear demarcation of cis- and trans-directed splicing paves ways for future studies of the genetic basis of disease.

A journey to your self: The vague definition of immune self and its practical implications

The identification of immunogenic peptides has become essential in an increasing number of fields in immunology, ranging from tumor immunotherapy to vaccine development. The nature of the adaptive immune response is shaped by the similarity between foreign and self-protein sequences, a concept extensively applied in numerous studies. Can we precisely define the degree of similarity to self? Furthermore, do we accurately define immune self? In the current work, we aim to unravel the conceptual and mechanistic vagueness hindering the assessment of self-similarity. Accordingly, we demonstrate the remarkably low consistency among commonly employed measures and highlight potential avenues for future research.

A multi-ethnic reference panel to impute HLA classical and non-classical class I alleles in admixed samples: Testing imputation accuracy in an admixed sample from Brazil

The MHC class I region contains crucial genes for the innate and adaptive immune response, playing a key role in susceptibility to many autoimmune and infectious diseases. Genome-wide association studies have identified numerous disease-associated SNPs within this region. However, these associations do not fully capture the immune-biological relevance of specific HLA alleles. HLA imputation techniques may leverage available SNP arrays by predicting allele genotypes based on the linkage disequilibrium between SNPs and specific HLA alleles. Successful imputation requires diverse and large reference panels, especially for admixed populations. This study employed a bioinformatics approach to call SNPs and HLA alleles in multi-ethnic samples from the 1000 genomes (1KG) dataset and admixed individuals from Brazil (SABE), utilising 30X whole-genome sequencing data. Using HIBAG, we created three reference panels: 1KG (n = 2504), SABE (n = 1171), and the full model (n = 3675) encompassing all samples. In extensive cross-validation of these reference panels, the multi-ethnic 1KG reference exhibited overall superior performance than the reference with only Brazilian samples. However, the best results were achieved with the full model. Additionally, we expanded the scope of imputation by developing reference panels for non-classical, MICA, MICB and HLA-H genes, previously unavailable for multi-ethnic populations. Validation in an independent Brazilian dataset showcased the superiority of our reference panels over the Michigan Imputation Server, particularly in predicting HLA-B alleles among Brazilians. Our investigations underscored the need to enhance or adapt reference panels to encompass the target population's genetic diversity, emphasising the significance of multiethnic references for accurate imputation across different populations.

Comparison of human leukocyte antigen in patients with paroxysmal nocturnal hemoglobinuria of different clone sizes

Glycosylphosphatidylinositol-anchored protein-deficient hematopoietic stem and progenitor cell development caused by PIGA mutations cannot fully explain the pathogenesis of paroxysmal nocturnal hemoglobinuria (PNH). Herein, patients newly diagnosed with PNH at our hospital between April 2019 and April 2021 were recruited. The human leukocyte antigen (HLA) class I and II loci were analyzed, and patients were stratified by PNH clone sizes: small (< 50%) and large (≥ 50%). In 40 patients (29 males; 72.5%), the median PNH clone size was 72%. Thirteen (32.5%) and twenty-seven (67.5%) patients harbored small and large PNH clones, respectively. DRB1*15:01 and DQB1*06:02 had higher frequencies in patients with PNH than in healthy controls (adjusted P-value = 4.10 × 10-4 and 4.10 × 10-4, respectively). Whole HLA class I and II allele contributions differed (P = 0.046 and 0.065, not significant difference) when comparing patients with small and large PNH clones. B*13:01 and C*04:01 allelic frequencies were significantly higher in patients with small clones (P = 0.032 and P = 0.032, respectively). Patients with small clones had higher class II HLA evolutionary divergence (HED) (P = 0.041) and global class I and II HED (P = 0.019). In the entire cohort, 17 HLA aberrations were found in 11 (27.5%) patients. No significant differences in HLA aberrations were found between patients with small or large clones. In conclusion, patients with small clones tended to have a higher frequency of immune attack-associated alleles. A higher HED in patients with small clones may reflect a propensity for T cell-mediated autoimmunity. HLA aberrations were similar between patients with small and large clones.

Evaluation of HLA typing content of next-generation sequencing datasets from family trios and individuals of arab ethnicity

Introduction: HLA typing is a critical tool in both clinical and research applications at the individual and population levels. Benchmarking studies have indicated HLA-HD as the preferred tool for accurate and comprehensive HLA allele calling. The advent of next-generation sequencing (NGS) has revolutionized genetic analysis by providing high-throughput sequencing data. This study aims to evaluate, using the HLA-HD tool, the HLA typing content of whole exome, whole genome, and HLA-targeted panel sequence data from the consanguineous population of Arab ethnicity, which has been underrepresented in prior benchmarking studies. Methods: We utilized sequence data from family trios and individuals, sequenced on one or more of the whole exome, whole genome, and HLA-targeted panel sequencing technologies. The performance and resolution across various HLA genes were evaluated. We incorporated a comparative quality control analysis, assessing the results obtained from HLA-HD by comparing them with those from the HLA-Twin tool to authenticate the accuracy of the findings. Results: Our analysis found that alleles across 29 HLA loci can be successfully and consistently typed from NGS datasets. Clinical-grade whole exome sequencing datasets achieved the highest consistency rate at three-field resolution, followed by targeted HLA panel, research-grade whole exome, and whole genome datasets. Discussion: The study catalogues HLA typing consistency across NGS datasets for a large array of HLA genes and highlights assessments regarding the feasibility of utilizing available NGS datasets in HLA allele studies. These findings underscore the reliability of HLA-HD for HLA typing in underrepresented populations and demonstrate the utility of various NGS technologies in achieving accurate HLA allele calling.

Reassessing human MHC-I genetic diversity in T cell studies

The Major Histocompatibility Complex class I (MHC-I) system plays a vital role in immune responses by presenting antigens to T cells. Allele specific technologies, including recombinant MHC-I technologies, have been extensively used in T cell analyses for COVID-19 patients and are currently used in the development of immunotherapies for cancer. However, the immense diversity of MHC-I alleles presents challenges. The genetic diversity serves as the foundation of personalized medicine, yet it also poses a potential risk of exacerbating healthcare disparities based on MHC-I alleles. To assess potential biases, we analysed (pre)clinical publications focusing on COVID-19 studies and T cell receptor (TCR)-based clinical trials. Our findings reveal an underrepresentation of MHC-I alleles associated with Asian, Australian, and African descent. Ensuring diverse representation is vital for advancing personalized medicine and global healthcare equity, transcending genetic diversity. Addressing this disparity is essential to unlock the full potential of T cells for enhancing diagnosis and treatment across all individuals.

Novel insights into TCR-T cell therapy in solid neoplasms: optimizing adoptive immunotherapy

Adoptive immunotherapy in the T cell landscape exhibits efficacy in cancer treatment. Over the past few decades, genetically modified T cells, particularly chimeric antigen receptor T cells, have enabled remarkable strides in the treatment of hematological malignancies. Besides, extensive exploration of multiple antigens for the treatment of solid tumors has led to clinical interest in the potential of T cells expressing the engineered T cell receptor (TCR). TCR-T cells possess the capacity to recognize intracellular antigen families and maintain the intrinsic properties of TCRs in terms of affinity to target epitopes and signal transduction. Recent research has provided critical insight into their capability and therapeutic targets for multiple refractory solid tumors, but also exposes some challenges for durable efficacy. In this review, we describe the screening and identification of available tumor antigens, and the acquisition and optimization of TCRs for TCR-T cell therapy. Furthermore, we summarize the complete flow from  laboratory to clinical applications of TCR-T cells. Last, we emerge future prospects for improving therapeutic efficacy in cancer world with combination therapies or TCR-T derived products. In conclusion, this review depicts our current understanding of TCR-T cell therapy in solid neoplasms, and provides new perspectives for expanding its clinical applications and improving therapeutic efficacy.

Resolving unknown nucleotides in the IPD-IMGT/HLA database by extended and full-length sequencing of HLA class I and II alleles

In the past, identification of HLA alleles was limited to sequencing the region of the gene coding for the peptide binding groove, resulting in a lack of sequence information in the HLA database, challenging HLA allele assignment software programs. We investigated full-length sequences of 19 HLA class I and 7 HLA class II alleles, and we extended another 47 HLA class I alleles with sequences of 5' and 3' UTR regions that were all not yet available in the IPD-IMGT/HLA database. We resolved 8638 unknown nucleotides in the coding sequence of HLA class I and 2139 of HLA class II. Furthermore, with full-length sequencing of the 26 alleles, more than 90 kb of sequence information was added to the non-coding sequences, whereas extension of the 47 alleles resulted in the addition of 5.5 kb unknown nucleotides to the 5' UTR and > 31.7 kb to the 3' UTR region. With this information, some interesting features were observed, like possible recombination events and lineage evolutionary origins. The continuing increase in the availability of full-length sequences in the HLA database will enable the identification of the evolutionary origin and will help the community to improve the alignment and assignment accuracy of HLA alleles.

Identification of apolipoprotein B-reactive CDR3 motifs allows tracking of atherosclerosis-related memory CD4+T cells in multiple donors

Introduction

Atherosclerosis is a major pathological condition that underlies many cardiovascular diseases (CVDs). Its etiology involves breach of tolerance to self, leading to clonal expansion of autoreactive apolipoprotein B (APOB)-reactive CD4+T cells that correlates with clinical CVD. The T-cell receptor (TCR) sequences that mediate activation of APOB-specific CD4+T cells are unknown.

Methods

In a previous study, we had profiled the hypervariable complementarity determining region 3 (CDR3) of CD4+T cells that respond to six immunodominant APOB epitopes in most donors. Here, we comprehensively analyze this dataset of 149,065 APOB-reactive and 199,211 non-reactive control CDR3s from six human leukocyte antigen-typed donors.

Results

We identified 672 highly expanded (frequency threshold > 1.39E-03) clones that were significantly enriched in the APOB-reactive group as compared to the controls (log10 odds ratio ≥1, Fisher's test p < 0.01). Analysis of 114,755 naïve, 91,001 central memory (TCM) and 29,839 effector memory (TEM) CDR3 sequences from the same donors revealed that APOB+ clones can be traced to the complex repertoire of unenriched blood T cells. The fraction of APOB+ clones that overlapped with memory CDR3s ranged from 2.2% to 46% (average 16.4%). This was significantly higher than their overlap with the naïve pool, which ranged from 0.7% to 2% (average 1.36%). CDR3 motif analysis with the machine learning-based in-silico tool, GLIPHs (grouping of lymphocyte interactions by paratope hotspots), identified 532 APOB+ motifs. Analysis of naïve and memory CDR3 sequences with GLIPH revealed that ~40% (209 of 532) of these APOB+ motifs were enriched in the memory pool. Network analysis with Cytoscape revealed extensive sharing of the memory-affiliated APOB+ motifs across multiple donors. We identified six motifs that were present in TCM and TEM CDR3 sequences from >80% of the donors and were highly enriched in the APOB-reactive TCR repertoire.

Discussion

The identified APOB-reactive expanded CD4+T cell clones and conserved motifs can be used to annotate and track human atherosclerosis-related autoreactive CD4+T cells and measure their clonal expansion.

Race, ethnicity, ancestry, and aspects that impact HLA data and matching for transplant

Race, ethnicity, and ancestry are terms that are often misinterpreted and/or used interchangeably. There is lack of consensus in the scientific literature on the definition of these terms and insufficient guidelines on the proper classification, collection, and application of this data in the scientific community. However, defining groups for human populations is crucial for multiple healthcare applications and clinical research. Some examples impacted by population classification include HLA matching for stem-cell or solid organ transplant, identifying disease associations and/or adverse drug reactions, defining social determinants of health, understanding diverse representation in research studies, and identifying potential biases. This article describes aspects of race, ethnicity and ancestry information that impact the stem-cell or solid organ transplantation field with particular focus on HLA data collected from donors and recipients by donor registries or transplant centers.

Advancements in HLA Typing Techniques and Their Impact on Transplantation Medicine

HLA typing serves as a standard practice in hematopoietic stem cell transplantation to ensure compatibility between donors and recipients, preventing the occurrence of allograft rejection and graft-versus-host disease. Conventional laboratory methods that have been widely employed in the past few years, including sequence-specific primer PCR and sequencing-based typing (SBT), currently face the risk of becoming obsolete. This risk stems not only from the extensive diversity within HLA genes but also from the rapid advancement of next-generation sequencing and third-generation sequencing technologies. Third-generation sequencing systems like single-molecule real-time (SMRT) sequencing and Oxford Nanopore (ONT) sequencing have the capability to analyze long-read sequences that span entire intronic-exonic regions of HLA genes, effectively addressing challenges related to HLA ambiguity and the phasing of multiple short-read fragments. The growing dominance of these advanced sequencers in HLA typing is expected to solidify further through ongoing refinements, cost reduction, and error rate minimization. This review focuses on hematopoietic stem cell transplantation (HSCT) and explores prospective advancements and application of HLA DNA typing techniques. It explores how the adoption of third-generation sequencing technologies can revolutionize the field by offering improved accuracy, reduced ambiguity, and enhanced assessment of compatibility in HSCT. Embracing these cutting-edge technologies is essential to advancing the success rates and outcomes of hematopoietic stem cell transplantation. This review underscores the importance of staying at the forefront of HLA typing techniques to ensure the best possible outcomes for patients undergoing HSCT.

MR1 antigen presentation to MAIT cells and other MR1-restricted T cells

MHC antigen presentation plays a fundamental role in adaptive and semi-invariant T cell immunity. Distinct MHC molecules bind antigens that differ in chemical structure, origin and location and present them to specialized T cells. MHC class I-related protein 1 (MR1) presents a range of small molecule antigens to MR1-restricted T (MR1T) lymphocytes. The best studied MR1 ligands are derived from microbial metabolism and are recognized by a major class of MR1T cells known as mucosal-associated invariant T (MAIT) cells. Here, we describe the MR1 antigen presentation pathway: the known types of antigens presented by MR1, the location where MR1-antigen complexes form, the route followed by the complexes to the cell surface, the mechanisms involved in termination of MR1 antigen presentation and the accessory cellular proteins that comprise the MR1 antigen presentation machinery. The current road map of the MR1 antigen presentation pathway reveals potential strategies for therapeutic manipulation of MR1T cell function and provides a foundation for further studies that will lead to a deeper understanding of MR1-mediated immunity.

Reducing Immunogenicity by Design: Approaches to Minimize Immunogenicity of Monoclonal Antibodies

Monoclonal antibodies (mAbs) have transformed therapeutic strategies for various diseases. Their high specificity to target antigens makes them ideal therapeutic agents for certain diseases. However, a challenge to their application in clinical practice is their potential risk to induce unwanted immune response, termed immunogenicity. This challenge drives the continued efforts to deimmunize these protein therapeutics while maintaining their pharmacokinetic properties and therapeutic efficacy. Because mAbs hold a central position in therapeutic strategies against an array of diseases, the importance of conducting comprehensive immunogenicity risk assessment during the drug development process cannot be overstated. Such assessment necessitates the employment of in silico, in vitro, and in vivo strategies to evaluate the immunogenicity risk of mAbs. Understanding the intricacies of the mechanisms that drive mAb immunogenicity is crucial to improving their therapeutic efficacy and safety and developing the most effective strategies to determine and mitigate their immunogenic risk. This review highlights recent advances in immunogenicity prediction strategies, with a focus on protein engineering strategies used throughout development to reduce immunogenicity.

An immunogenetic basis for lung cancer risk

Cancer risk is influenced by inherited mutations, DNA replication errors, and environmental factors. However, the influence of genetic variation in immunosurveillance on cancer risk is not well understood. Leveraging population-level data from the UK Biobank and FinnGen, we show that heterozygosity at the human leukocyte antigen (HLA)-II loci is associated with reduced lung cancer risk in smokers. Fine-mapping implicated amino acid heterozygosity in the HLA-II peptide binding groove in reduced lung cancer risk, and single-cell analyses showed that smoking drives enrichment of proinflammatory lung macrophages and HLA-II+ epithelial cells. In lung cancer, widespread loss of HLA-II heterozygosity (LOH) favored loss of alleles with larger neopeptide repertoires. Thus, our findings nominate genetic variation in immunosurveillance as a critical risk factor for lung cancer.

Forum on immune digital twins: a meeting report

Medical digital twins are computational models of human biology relevant to a given medical condition, which are tailored to an individual patient, thereby predicting the course of disease and individualized treatments, an important goal of personalized medicine. The immune system, which has a central role in many diseases, is highly heterogeneous between individuals, and thus poses a major challenge for this technology. In February 2023, an international group of experts convened for two days to discuss these challenges related to immune digital twins. The group consisted of clinicians, immunologists, biologists, and mathematical modelers, representative of the interdisciplinary nature of medical digital twin development. A video recording of the entire event is available. This paper presents a synopsis of the discussions, brief descriptions of ongoing digital twin projects at different stages of progress. It also proposes a 5-year action plan for further developing this technology. The main recommendations are to identify and pursue a small number of promising use cases, to develop stimulation-specific assays of immune function in a clinical setting, and to develop a database of existing computational immune models, as well as advanced modeling technology and infrastructure.

Canine major histocompatibility complex class I (MHC-I) diversity landscape

The genes of the Major Histocompatibility Complex class I (MHC-I) are among the most diverse in the mammalian genome, playing a crucial role in immunology. Understanding the diversity landscape of MHC-I is therefore of paramount importance. The dog is a key translational model in various biomedical fields. However, our understanding of the canine MHC-I diversity landscape lags significantly behind that of humans. To address this deficiency, we used our newly developed software, KPR de novo assembler and genotyper, to genotype 1,325 samples from 1,025 dogs with paired-end RNA-seq data from 43 BioProjects, after extensive quality control. Among 926 dogs that pass the QC, 591 dogs (64%) have at least one allele genotyped, and a total of 97 known alleles and 52 putative new alleles were identified. Further analysis reveals that DLA-I gene expression levels vary among the tissues, with lowest for testis and brain tissues and highest for blood, corpus luteum, and spleen. We identified dominant alleles in each of the 17 canine breeds, as well as among the entire canine population. Furthermore, our analysis also identifies breed-specific alleles and mutually co-occurred/exclusive alleles. Our study indicates that canine DLA-88 is as diversified as human HLA-A/B/C genes within the entire population, but less diversified within a breed than with HLA-A/B/C within an ethnic group. Lastly, we examined the hypervariable regions (HVR) within or across human/canine MHC-I alleles and found that 80% of the HVRs overlap between the two species. We further noted that 80% of the HVRs are within 4A contact with the peptides, and that the dog-human difference overlaps with only 20% HVRs. Our research offers valuable insights for immunological studies involving dogs.

T-cell virtuosity in ''knowing thyself"

Major Histocompatibility Complex (MHC) I and II and the αβ T-cell antigen receptor (TCRαβ) govern fundamental traits of adaptive immunity. They form a membrane-borne ligand-receptor system weighing host proteome integrity to detect contamination by nonself proteins. MHC-I and -II exhibit the "MHC-fold", which is able to bind a large assortment of short peptides as proxies for self and nonself proteins. The ensuing varying surfaces are mandatory ligands for Ig-like TCRαβ highly mutable binding sites. Conserved molecular signatures guide TCRαβ ligand binding sites to focus on the MHC-fold (MHC-restriction) while leaving many opportunities for its most hypervariable determinants to contact the peptide. This riveting molecular strategy affords many options for binding energy compatible with specific recognition and signalling aimed to eradicated microbial pathogens and cancer cells. While the molecular foundations of αβ T-cell adaptive immunity are largely understood, uncertainty persists on how peptide-MHC binding induces the TCRαβ signals that instruct cell-fate decisions. Solving this mystery is another milestone for understanding αβ T-cells' self/nonself discrimination. Recent developments revealing the innermost links between TCRαβ structural dynamics and signalling modality should help dissipate this long-sought-after enigma.

Large-scale integrative analysis of juvenile idiopathic arthritis for new insight into its pathogenesis

BACKGROUND

Juvenile idiopathic arthritis (JIA) is one of the most prevalent rheumatic disorders in children and is classified as an autoimmune disease (AID). While a robust genetic contribution to JIA etiology has been established, the exact pathogenesis remains unclear.

METHODS

To prioritize biologically interpretable susceptibility genes and proteins for JIA, we conducted transcriptome-wide and proteome-wide association studies (TWAS/PWAS). Then, to understand the genetic architecture of JIA, we systematically analyzed single-nucleotide polymorphism (SNP)-based heritability, a signature of natural selection, and polygenicity. Next, we conducted HLA typing using multi-ethnicity RNA sequencing data. Additionally, we examined the T cell receptor (TCR) repertoire at a single-cell level to explore the potential links between immunity and JIA risk.

RESULTS

We have identified 19 TWAS genes and two PWAS proteins associated with JIA risks. Furthermore, we observe that the heritability and cell type enrichment analysis of JIA are enriched in T lymphocytes and HLA regions and that JIA shows higher polygenicity compared to other AIDs. In multi-ancestry HLA typing, B*45:01 is more prevalent in African JIA patients than in European JIA patients, whereas DQA1*01:01, DQA1*03:01, and DRB1*04:01 exhibit a higher frequency in European JIA patients. Using single-cell immune repertoire analysis, we identify clonally expanded T cell subpopulations in JIA patients, including CXCL13+BHLHE40+ TH cells which are significantly associated with JIA risks.

CONCLUSION

Our findings shed new light on the pathogenesis of JIA and provide a strong foundation for future mechanistic studies aimed at uncovering the molecular drivers of JIA.

Investigating the genetic makeup of the major histocompatibility complex (MHC) in the United Arab Emirates population through next-generation sequencing

The Human leukocyte antigen (HLA) molecules are central to immune response and have associations with the phenotypes of various diseases and induced drug toxicity. Further, the role of HLA molecules in presenting antigens significantly affects the transplantation outcome. The objective of this study was to examine the extent of the diversity of HLA alleles in the population of the United Arab Emirates (UAE) using Next-Generation Sequencing methodologies and encompassing a larger cohort of individuals. A cohort of 570 unrelated healthy citizens of the UAE volunteered to provide samples for Whole Genome Sequencing and Whole Exome Sequencing. The definition of the HLA alleles was achieved through the application of the bioinformatics tools, HLA-LA and xHLA. Subsequently, the findings from this study were compared with other local and international datasets. A broad range of HLA alleles in the UAE population, of which some were previously unreported, was identified. A comparison with other populations confirmed the current population's unique intertwined genetic heritage while highlighting similarities with populations from the Middle East region. Some disease-associated HLA alleles were detected at a frequency of > 5%, such as HLA-B*51:01, HLA-DRB1*03:01, HLA-DRB1*15:01, and HLA-DQB1*02:01. The increase in allele homozygosity, especially for HLA class I genes, was identified in samples with a higher level of genome-wide homozygosity. This highlights a possible effect of consanguinity on the HLA homozygosity. The HLA allele distribution in the UAE population showcases a unique profile, underscoring the need for tailored databases for traditional activities such as unrelated transplant matching and for newer initiatives in precision medicine based on specific populations. This research is part of a concerted effort to improve the knowledge base, particularly in the fields of transplant medicine and investigating disease associations as well as in understanding human migration patterns within the Arabian Peninsula and surrounding regions.

Immune-driven clonal cell selection at the intersection among cancer, infections, autoimmunity and senescence

Immune surveillance mechanisms play a crucial role in maintaining lifelong immune homeostasis in response to pathologic stimuli and aberrant cell states. However, their persistence, especially in the context of chronic antigenic exposure, can create a fertile ground for immune evasion. These escaping cell phenotypes, harboring a variety of genomic and transcriptomic aberrances, chiefly in human leukocyte antigen (HLA) and antigen presentation machinery genes, may survive and proliferate, featuring a scenario of clonal cell expansion with immune failure characteristics. While well characterized in solid and, to some extent, hematological malignancies, little is known about their occurrence and significance in other disease contexts. Historical literature highlights the role for escaping HLA-mediated recognition as a strategy adopted by virus to evade from the immune system, hinting at the potential for immune aberrant cell expansion in the context of chronic infections. Additionally, unmasked in idiopathic aplastic anemia as a mechanism able to rescue failing hematopoiesis, HLA clonal escape may operate in autoimmune disorders, particularly in tissues targeted by aberrant immune responses. Furthermore, senescent cell status emerging as immunogenic phenotypes stimulating T cell responses, may act as a bottleneck for the selection of such immune escaping clones, blurring the boundaries between neoplastic transformation, aging and inflammation. Here we provide a fresh overview and perspective on this immune-driven clonal cell expansion, linking pathophysiological features of neoplastic, autoimmune, infectious and senescence processes exposed to immune surveillance.

A rigorous benchmarking of alignment-based HLA typing algorithms for RNA-seq data

Accurate identification of human leukocyte antigen (HLA) alleles is essential for various clinical and research applications, such as transplant matching and drug sensitivities. Recent advances in RNA-seq technology have made it possible to impute HLA types from sequencing data, spurring the development of a large number of computational HLA typing tools. However, the relative performance of these tools is unknown, limiting the ability for clinical and biomedical research to make informed choices regarding which tools to use. Here we report the study design of a comprehensive benchmarking of the performance of 12 HLA callers across 682 RNA-seq samples from 8 datasets with molecularly defined gold standard at 5 loci, HLA-A, -B, -C, -DRB1, and -DQB1. For each HLA typing tool, we will comprehensively assess their accuracy, compare default with optimized parameters, and examine for discrepancies in accuracy at the allele and loci levels. We will also evaluate the computational expense of each HLA caller measured in terms of CPU time and RAM. We also plan to evaluate the influence of read length over the HLA region on accuracy for each tool. Most notably, we will examine the performance of HLA callers across European and African groups, to determine discrepancies in accuracy associated with ancestry. We hypothesize that RNA-Seq HLA callers are capable of returning high-quality results, but the tools that offer a good balance between accuracy and computational expensiveness for all ancestry groups are yet to be developed. We believe that our study will provide clinicians and researchers with clear guidance to inform their selection of an appropriate HLA caller.

A novel HLA-B*58:141 allele identified by next-generation sequencing in a potential hematopoietic cell recipient

We report a novel HLA-B*58 allele, now named B*58:141, identified by next-generation sequencing.

In Silico Tools for Predicting Novel Epitopes

Identifying antigens within a pathogen is a critical task to develop effective vaccines and diagnostic methods, as well as understanding the evolution and adaptation to host immune responses. Historically, antigenicity was studied with experiments that evaluate the immune response against selected fragments of pathogens. Using this approach, the scientific community has gathered abundant information regarding which pathogenic fragments are immunogenic. The systematic collection of this data has enabled unraveling many of the fundamental rules underlying the properties defining epitopes and immunogenicity, and has resulted in the creation of a large panel of immunologically relevant predictive (in silico) tools. The development and application of such tools have proven to accelerate the identification of novel epitopes within biomedical applications reducing experimental costs. This chapter introduces some basic concepts about MHC presentation, T cell and B cell epitopes, the experimental efforts to determine those, and focuses on state-of-the-art methods for epitope prediction, highlighting their strengths and limitations, and catering instructions for their rational use.

NanoHLA: A Method for Human Leukocyte Antigen Class I Genes Typing Without Error Correction Based on Nanopore Sequencing Data

Human leukocyte antigen (HLA) typing is of great importance in clinical applications such as organ transplantation, blood transfusion, disease diagnosis and treatment, and forensic analysis. In recent years, nanopore sequencing technology has emerged as a rapid and cost-effective option for HLA typing. However, due to the principles and data characteristics of nanopore sequencing, there was a scarcity of robust and generalizable bioinformatics tools for its downstream analysis, posing a significant challenge in deciphering the thousands of HLA alleles present in the human population. To address this challenge, we developed NanoHLA as a tool for high-resolution typing of HLA class I genes without error correction based on nanopore sequencing. The method integrated the concepts of HLA type coverage analysis and the data conversion techniques employed in Nano2NGS, which was characterized by applying nanopore sequencing data to NGS-liked data analysis pipelines. In validation with public nanopore sequencing datasets, NanoHLA showed an overall concordance rate of 84.34% for HLA-A, HLA-B, and HLA-C, and demonstrated superior performance in comparison to existing tools such as HLA-LA. NanoHLA provides tools and solutions for use in HLA typing related fields, and look forward to further expanding the application of nanopore sequencing technology in both research and clinical settings. The code is available at https://github.com/langjidong/NanoHLA .

Repeated local ellipsoid protrusion supplements HLA surface characterization

Allorecognition of donor HLA is a major risk factor for long-term kidney graft survival. Although several molecular matching algorithms have been proposed that compare physiochemical and structural features of the donors' and recipients' HLA proteins in order to predict their compatibility, the exact underlying mechanisms are still not fully understood. We hypothesized that the ElliPro approach of single ellipsoid fitting and protrusion ranking lacks sensitivity for the characteristic shape of HLA molecules and developed a prediction pipeline named Snowball that is fitting smaller ellipsoids iteratively to substructures. Aggregated protrusion ranks of locally fitted ellipsoids were calculated for 712 publicly available HLA structures and 78 predicted structures using AlphaFold 2. Amino-acid sequence and protrusion ranks were used to train deep neural network predictors to infer protrusion ranks for all known HLA sequences. Snowball protrusion ranks appear to be more sensitive than ElliPro scores in fine parts of the HLA such as the helix structures forming the HLA binding groove in particular when the ellipsoids are fitted to substructures considering atoms within a 15 Å radius. A cloud-based web service was implemented based on amino-acid matching considering both protein- and position-specific surface area and protrusion ranks extending the previously presented Snowflake prediction pipeline.

Allele Frequency Net Database

The allele frequency net database (AFND, http://www.allelefrequencies.net ) is an online web-based repository that contains information on the frequencies of immune-related genes and their corresponding alleles in worldwide human populations. At present, the website contains data from 1784 population samples in more than 14 million individuals from 129 countries on the frequency of genes from different polymorphic regions including data for the human leukocyte antigen (HLA) system. In addition, over the last four years, AFND has also incorporated genotype raw data from 85,000 individuals comprising 215 population samples from 39 countries. Moreover, more population data sets containing next generation sequencing data spanning >3 million individuals have been added. This resource has been widely used in a variety of contexts such as histocompatibility, immunology, epidemiology, pharmacogenetics, epitope prediction algorithms for population coverage in vaccine development, population genetics, among many others. In this chapter, we present an update of the most used searching mechanisms as described in a previous volume and some of the latest developments included in AFND.

Fifty novel HLA-DPB1 alleles identified in a UK cohort of unrelated hematopoietic cell donors and recipients

HLA-DPB1 is the classical HLA class II genes with the least recorded variation on the IPD-IMGT/HLA Database, suggesting the full extent of its diversity is perhaps yet to be characterized. Here, a full-gene typing strategy was employed to genotype a UK cohort of 1470 HCT recipients (n = 744) and donors (n = 726). In total, 2940 full-length HLA-DPB1 sequences were generated, comprising 193 distinct alleles. Of these, 107 sequences contained novel variation, totaling 49 unique intronic HLA-DPB1 alleles, and one coding variant (HLA-DPB1*1188:01). Full-gene sequencing resulted in zygosity changes for 129 individuals by identifying two distinct intronic variants of the same coding allele. We verified the existence of nine unconfirmed alleles and extended the sequence of two existing alleles on the IPD-IMGT/HLA Database.

Accurate identification of HLA-B*15:02 allele by two-dimensional polymerase chain reaction

BACKGROUND

HLA-B*15:02 is highly associated with carbamazepine-induced SJS/TEN; however, there is no rapid and accurate detecting method. Here, we present a method to distinguish HLA-B*15:02 from 16 highly homologous HLA-B*15 alleles.

METHODS

The high-throughput two-dimensional polymerase chain reaction (2D-PCR) technology was employed to identify HLA-B*15:02 in two-tube reaction. And, 2D-PCR accuracy was verified by PCR-sequence based typing (PCR-SBT).

RESULTS

HLA-B*15:02 heterozygotes were identified by 14 melting valleys in the first tube reaction and none in the second, or by 13 melting valleys in the first tube reaction and one in the second. HLA-B*15:02 homozygote was identified by 13 melting valleys in the first tube reaction and none in the second. Three (0.16%) HLA-B*15:02 homozygotes and 84 (4.59%) HLA-B*15:02 heterozygotes were detected in 1830 samples of clinical general population without detecting 16 highly homologous alleles to HLA-B*15:02. The kappa test showed 100% coincidence between the 2D-PCR and PCR-SBT.

CONCLUSIONS

2D-PCR in two-tube reaction method for identifying HLA-B*15:02 was successfully established. Identification of HLA-B*15:02 is necessary prior to taking CBZ based on HLA-B*15:02 allele frequency.

Full-Length Characterization of Novel HLA-DRB1 Alleles for Reference Database Submission

The prerequisite for successful HLA genotyping is the integrity of the large allele reference database IPD-IMGT/HLA. Consequently, it is in the laboratories' best interest that the data quality of submitted novel sequences is high. However, due to its long and variable length, the gene HLA-DRB1 presents the biggest challenge and as of today only 16% of the HLA-DRB1 alleles in the database are characterized in full length. To improve this situation, we developed a protocol for long-range PCR amplification of targeted HLA-DRB1 alleles. By subsequently combining both long-read and short-read sequencing technologies, our protocol ensures phased and error-corrected sequences of reference grade quality. This dual redundant reference sequencing (DR2S) approach is of particular importance for correctly resolving the challenging repeat regions of DRB1 intron 1. Until today, we used this protocol to characterize and submit 384 full-length HLA-DRB1 sequences to IPD-IMGT/HLA.

MHC-Fine: Fine-tuned AlphaFold for Precise MHC-Peptide Complex Prediction

The precise prediction of Major Histocompatibility Complex (MHC)-peptide complex structures is pivotal for understanding cellular immune responses and advancing vaccine design. In this study, we enhanced AlphaFold's capabilities by fine-tuning it with a specialized dataset comprised by exclusively high-resolution MHC-peptide crystal structures. This tailored approach aimed to address the generalist nature of AlphaFold's original training, which, while broad-ranging, lacked the granularity necessary for the high-precision demands of MHC-peptide interaction prediction. A comparative analysis was conducted against the homology-modeling-based method Pandora [13], as well as the AlphaFold multimer model [8]. Our results demonstrate that our fine-tuned model outperforms both in terms of RMSD (median value is 0.65 Å) but also provides enhanced predicted lDDT scores, offering a more reliable assessment of the predicted structures. These advances have substantial implications for computational immunology, potentially accelerating the development of novel therapeutics and vaccines by providing a more precise computational lens through which to view MHC-peptide interactions.

Honduras HIV cohort: HLA class I and CCR5-Δ32 profiles and their associations with HIV disease outcome

IMPORTANCE

We identify both canonical and novel human leukocyte antigen (HLA)-HIV associations, providing a first step toward improved understanding of HIV immune control among the understudied Honduras Mestizo population. Our results are relevant to understanding the protective or detrimental effects of HLA subtypes in Latin America because their unique HLA diversity poses challenges for designing vaccines against HIV and interpreting results from such vaccine trials. Likewise, the description of the HLA profile in an understudied population that shows a unique HLA immunogenetic background is not only relevant for HIV immunology but also relevant in population genetics, molecular anthropology, susceptibility to other infections, autoimmune diseases, and allograft transplantation.

Targeting MHC-I molecules for cancer: function, mechanism, and therapeutic prospects

The molecules of Major histocompatibility class I (MHC-I) load peptides and present them on the cell surface, which provided the immune system with the signal to detect and eliminate the infected or cancerous cells. In the context of cancer, owing to the crucial immune-regulatory roles played by MHC-I molecules, the abnormal modulation of MHC-I expression and function could be hijacked by tumor cells to escape the immune surveillance and attack, thereby promoting tumoral progression and impairing the efficacy of cancer immunotherapy. Here we reviewed and discussed the recent studies and discoveries related to the MHC-I molecules and their multidirectional functions in the development of cancer, mainly focusing on the interactions between MHC-I and the multiple participators in the tumor microenvironment and highlighting the significance of targeting MHC-I for optimizing the efficacy of cancer immunotherapy and a deeper understanding of the dynamic nature and functioning mechanism of MHC-I in cancer.

HLA-B*27 and Ankylosing Spondylitis: 50 Years of Insights and Discoveries

PURPOSE OF REVIEW

To commemorate the 50th anniversary of the groundbreaking discovery of a remarkably strong association between HLA-B*27 and ankylosing spondylitis (AS).

RECENT FINDINGS

In addition to HLA-B*27, more than 116 other recognized genetic risk variants have been identified, while epigenetic factors largely remain unexplored in this context. Among patients with AS who carry the HLA-B*27 gene, clonally expanded CD8 + T cells can be found in their bloodstream and within inflamed tissues. Moreover, the α and β chain motifs of these T-cell receptors demonstrate a distinct affinity for certain self- and microbial-derived peptides, leading to an autoimmune response that ultimately results in the onset of the disease. These distinctive peptide-binding and presentation characteristics are a hallmark of the disease-associated HLA-B*27:05 subtype but are absent in HLA-B*27:09, a subtype not associated with the disease, differing by only a single amino acid. This discovery represents a significant advancement in unraveling the 50-year-old puzzle of how HLA-B*27 contributes to the development of AS. These findings will significantly accelerate the process of identifying peptides, both self- and microbial-derived, that instigate autoimmunity. This, in return, will pave the way for the development of more accurate and effective targeted treatments. Moreover, the discovery of improved biomarkers, in conjunction with the emerging technology of electric field molecular fingerprinting, has the potential to greatly bolster early diagnosis capabilities. A very recently published groundbreak paper underscores the remarkable effectiveness of targeting and eliminating disease-causing T cells in a HLA-B*27 patients with AS. This pivotal advancement not only signifies a paradigm shift but also bolsters the potential for preventing the disease in individuals carrying high-risk genetic variants.

Neoantigen-targeted TCR-engineered T cell immunotherapy: current advances and challenges

Adoptive cell therapy using T cell receptor-engineered T cells (TCR-T) is a promising approach for cancer therapy with an expectation of no significant side effects. In the human body, mature T cells are armed with an incredible diversity of T cell receptors (TCRs) that theoretically react to the variety of random mutations generated by tumor cells. The outcomes, however, of current clinical trials using TCR-T cell therapies are not very successful especially involving solid tumors. The therapy still faces numerous challenges in the efficient screening of tumor-specific antigens and their cognate TCRs. In this review, we first introduce TCR structure-based antigen recognition and signaling, then describe recent advances in neoantigens and their specific TCR screening technologies, and finally summarize ongoing clinical trials of TCR-T therapies against neoantigens. More importantly, we also present the current challenges of TCR-T cell-based immunotherapies, e.g., the safety of viral vectors, the mismatch of T cell receptor, the impediment of suppressive tumor microenvironment. Finally, we highlight new insights and directions for personalized TCR-T therapy.

Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution

The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues. To mitigate technical confounding, we developed scHLApers, a pipeline to accurately quantify single-cell HLA expression using personalized reference genomes. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B and T cells. For example, a T cell HLA-DQA1 eQTL ( rs3104371 ) is strongest in cytotoxic cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.

Exploring the genetic diversity of the Japanese population: Insights from a large-scale whole genome sequencing analysis

The Japanese archipelago is a terminal location for human migration, and the contemporary Japanese people represent a unique population whose genomic diversity has been shaped by multiple migrations from Eurasia. We analyzed the genomic characteristics that define the genetic makeup of the modern Japanese population from a population genetics perspective from the genomic data of 9,287 samples obtained by high-coverage whole-genome sequencing (WGS) by the National Center Biobank Network. The dataset comprised populations from the Ryukyu Islands and other parts of the Japanese archipelago (Hondo). The Hondo population underwent two episodes of population decline during the Jomon period, corresponding to the Late Neolithic, and the Edo period, corresponding to the Early Modern era, while the Ryukyu population experienced a population decline during the shell midden period of the Late Neolithic in this region. Haplotype analysis suggested increased allele frequencies for genes related to alcohol and fatty acid metabolism, which were reported as loci that had experienced positive natural selection. Two genes related to alcohol metabolism were found to be 12,500 years out of phase with the time when they began to increase in the allele frequency; this finding indicates that the genomic diversity of Japanese people has been shaped by events closely related to agriculture and food production.

DeepHLAPred: a deep learning-based method for non-classical HLA binder prediction

Human leukocyte antigen (HLA) is closely involved in regulating the human immune system. Despite great advance in detecting classical HLA Class I binders, there are few methods or toolkits for recognizing non-classical HLA Class I binders. To fill in this gap, we have developed a deep learning-based tool called DeepHLAPred. The DeepHLAPred used electron-ion interaction pseudo potential, integer numerical mapping and accumulated amino acid frequency as initial representation of non-classical HLA binder sequence. The deep learning module was used to further refine high-level representations. The deep learning module comprised two parallel convolutional neural networks, each followed by maximum pooling layer, dropout layer, and bi-directional long short-term memory network. The experimental results showed that the DeepHLAPred reached the state-of-the-art performanceson the cross-validation test and the independent test. The extensive test demonstrated the rationality of the DeepHLAPred. We further analyzed sequence pattern of non-classical HLA class I binders by information entropy. The information entropy of non-classical HLA binder sequence implied sequence pattern to a certain extent. In addition, we have developed a user-friendly webserver for convenient use, which is available at http://www.biolscience.cn/DeepHLApred/ . The tool and the analysis is helpful to detect non-classical HLA Class I binder. The source code and data is available at https://github.com/tangxingyu0/DeepHLApred .

High population frequencies of MICA copy number variations originate from independent recombination events

MICA is a stress-induced ligand of the NKG2D receptor that stimulates NK and T cell responses and was identified as a key determinant of anti-tumor immunity. The MICA gene is located inside the MHC complex and is in strong linkage disequilibrium with HLA-B. While an HLA-B*48-linked MICA deletion-haplotype was previously described in Asian populations, little is known about other MICA copy number variations. Here, we report the genotyping of more than two million individuals revealing high frequencies of MICA duplications (1%) and MICA deletions (0.4%). Their prevalence differs between ethnic groups and can rise to 2.8% (Croatia) and 9.2% (Mexico), respectively. Targeted sequencing of more than 70 samples indicates that these copy number variations originate from independent nonallelic homologous recombination events between segmental duplications upstream of MICA and MICB. Overall, our data warrant further investigation of disease associations and consideration of MICA copy number data in oncological study protocols.

HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases

The human leukocyte antigen (HLA) region on chromosome 6 is strongly associated with many immune-mediated and infection-related diseases. Due to its highly polymorphic nature and complex linkage disequilibrium patterns, traditional genetic association studies of single nucleotide polymorphisms do not perform well in this region. Instead, the field has adopted the assessment of the association of HLA alleles (i.e., entire HLA gene haplotypes) with disease. Often based on genotyping arrays, these association studies impute HLA alleles, decreasing accuracy and thus statistical power for rare alleles and in non-European ancestries. Here, we use whole-exome sequencing (WES) from 454,824 UK Biobank (UKB) participants to directly call HLA alleles using the HLA-HD algorithm. We show this method is more accurate than imputing HLA alleles and harness the improved statistical power to identify 360 associations for 11 auto-immune phenotypes (at least 129 likely novel), leading to better insights into the specific coding polymorphisms that underlie these diseases. We show that HLA alleles with synonymous variants, often overlooked in HLA studies, can significantly influence these phenotypes. Lastly, we show that HLA sequencing may improve polygenic risk scores accuracy across ancestries. These findings allow better characterization of the role of the HLA region in human disease.

Proteogenomics Reveal the Overexpression of HLA-I in Cancer

An accurate quantification of HLA class I gene expression is important in understanding the interplay with the tumor microenvironment of antitumor cytotoxic T cell activities. Because HLA-I sequences are highly variable, standard RNAseq and mass spectrometry-based quantification workflows using common genome and protein sequence references do not provide HLA-I allele specific quantifications. Here, we used personalized HLA-I nucleotide and protein reference sequences based on the subjects' HLA-I genotypes and surveyed tumor and adjacent normal samples from patients across nine cancer types. Mass spectrometry using data dependent acquisition data was validated to be sufficient to estimate HLA-A protein expression at the allele level. We found that HLA-I proteins were present in significantly higher levels in tumors compared to adjacent normal tissues from 41 to 63% of head and neck squamous cell carcinoma, uterine corpus endometrial carcinoma, and clear cell renal cell carcinoma patients, and this was driven by increased levels of HLA-I gene transcripts. Most immune cell types are universally enriched in HLA-I high tumors, while endothelial and neuronal cells showed divergent relationships with HLA-I. Pathway analysis revealed that tumor senescence and autophagy activity influence the level of HLA-I proteins in glioblastoma. Genes correlated to HLA-I protein expression are mostly the ones directly involved in HLA-I function in immune response and cell death, while glycosylation genes are exclusively co-expressed with HLA-I at the protein level.

HLA-F transcriptional and protein differential expression according to its genetic polymorphisms

Many specificities single out HLA-F: its structure, expression regulation at cell membrane and function. HLA-F mRNA is detected in the most cell types and the protein is localized in the ER and Golgi apparatus. When expressed at cell surface, HLA-F may be associated to β2-microglobulin and peptide or expressed as an open-conformer molecule. HLA-F reaches the membrane upon activation of different primary cell types and cell-lines. HLA-F has its highest affinity for the KIR3DS1-activating NK receptor, but also binds inhibitory immune receptors. Some studies reported that HLA-F expression is associated with its genotype. Higher HLA-F mRNA expression associated with F*01:01:02, and 3 noncoding SNPs, rs1362126, rs2523405, and rs2523393, located in HLA-F-AS1 or upstream the HLA-F sequence were associated with HLA-F mRNA expression. Given the implication of HLA-F in many clinical setting, and the undisclosed process of its expression regulation, we aim to confirm the effect of the aforementioned SNPs with HLA-F transcriptional and protein expression. We analyzed the distribution, frequency and linkage disequilibrium of these SNPs at worldwide scale in the 1000 Genomes Project samples. Influence on the genotype of each SNP on HLA-F expression was explored using RNAseq data from the 1000 Genomes Project, and using Q-PCR and intracellular cytometry in PBMC from healthy individuals. Our results show that the SNPs under studied displayed remarkably different allelic proportion according to geography and confirm that rs1362126, rs2523405, and rs2523393 displayed the most concordant results, with the highest effect size and a double-dose effect.

Abrogation and Homeostatic Restoration of IgE Responses by a Universal IgE Allergy CTL Vaccine-The Three Signal Self/Non-Self/Self (S/NS/S) Model

Natural IgE cytotoxic peptides (nECPs), which are derived from the constant domain of the heavy chain of human IgE producing B cells via endoplasmic reticulum (ER) stress, are decorated onto MHC class 1a molecules (MHCIa) as unique biomarkers for CTL (cytotoxic T lymphocyte)-mediated immune surveillance. Human IgE exhibits only one isotype and lacks polymorphisms; IgE is pivotal in mediating diverse, allergen-specific allergies. Therefore, by disrupting self-IgE tolerance via costimulation, the cytotoxic T lymphocytes (CTLs) induced by nECPs can serve as universal allergy vaccines (UAVs) in humans to dampen IgE production mediated by diverse allergen-specific IgE- secreting B cells and plasma cells expressing surface nECP-MHCIa as targets. The study herein has enabled the identification of nECPs produced through the correspondence principle 1, 2 . Furthermore, nECP-tetramer-specific CTLs were found to be converted into CD4 Tregs that restored IgE competence via the homeostatic principle, mediated by SREBP-1c suppressed DCs. Thus, nECPs showed causal efficacy and safety as UAVs for treating type I hypersensitivity IgE-mediated allergies. The applied vaccination concept presented provides the foundation to unify, integrate through a singular class of tetramer-specific TCR clonotypes. The three signal model is proposed on the mechanisms underlying central tolerance, breaking tolerance and regaining peripheral tolerance via homeostasis concerning nECP as an efficacious and safe UAV to treat type I IgE-mediated hypersensitivity.

One Sentence Summary

Human IgE self-peptides are identified as universal allergy vaccines that inhibit IgE synthesis while allowing homeostatic IgE recovery.Graphic abstract textThree cell S/NS/S model of Universal Allergy Vaccines (UAV): Natural IgE peptides (nECPs) presented by enabler DCs break central IgE tolerance (Self), leading to CTLs that inhibit IgE production (Non-self). Generative DCs converted by the metabolic milieu transform the pre-existing nECP-specific CTLs into nECP-specific Tregs leading to homeostatic recovery of IgE competence (S).

Novel alleles in the era of next-generation sequencing-based HLA typing calls for standardization and policy

Next-Generation Sequencing (NGS) has transformed clinical histocompatibility laboratories through its capacity to provide accurate, high-throughput, high-resolution typing of Human Leukocyte Antigen (HLA) genes, which is critical for transplant safety and success. As this technology becomes widely used for clinical genotyping, histocompatibility laboratories now have an increased capability to identify novel HLA alleles that previously would not be detected using traditional genotyping methods. Standard guidelines for the clinical verification and reporting of novelties in the era of NGS are greatly needed. Here, we describe the experience of a clinical histocompatibility laboratory's use of NGS for HLA genotyping and its management of novel alleles detected in an ethnically-diverse population of British Columbia, Canada. Over a period of 18 months, 3,450 clinical samples collected for the purpose of solid organ or hematopoietic stem cell transplantation were sequenced using NGS. Overall, 29 unique novel alleles were identified at a rate of ∼1.6 per month. The majority of novelties (52%) were detected in the alpha chains of class II (HLA-DQA1 and -DPA1). Novelties were found in all 11 HLA classical genes except for HLA-DRB3, -DRB4, and -DQB1. All novelties were single nucleotide polymorphisms, where more than half led to an amino acid change, and one resulted in a premature stop codon. Missense mutations were evaluated for changes in their amino acid properties to assess the potential effect on the novel HLA protein. All novelties identified were confirmed independently at another accredited HLA laboratory using a different NGS assay and platform to ensure validity in the reporting of novelties. The novel alleles were submitted to the Immuno Polymorphism Database-Immunogenetics/HLA (IPD-IMGT/HLA) for official allele name designation and inclusion in future database releases. A nationwide survey involving all Canadian HLA laboratories confirmed the common occurrence of novel allele detection but identified a wide variability in the assessment and reporting of novelties. In summary, a considerable proportion of novel alleles were identified in routine clinical testing. We propose a framework for the standardization of policies on the clinical management of novel alleles and inclusion in proficiency testing programs in the era of NGS-based HLA genotyping.

HLA3DB: comprehensive annotation of peptide/HLA complexes enables blind structure prediction of T cell epitopes

The class I proteins of the major histocompatibility complex (MHC-I) display epitopic peptides derived from endogenous proteins on the cell surface for immune surveillance. Accurate modeling of peptides bound to the human MHC, HLA, has been mired by conformational diversity of the central peptide residues, which are critical for recognition by T cell receptors. Here, analysis of X-ray crystal structures within our curated database (HLA3DB) shows that pHLA complexes encompassing multiple HLA allotypes present a discrete set of peptide backbone conformations. Leveraging these backbones, we employ a regression model trained on terms of a physically relevant energy function to develop a comparative modeling approach for nonamer pHLA structures named RepPred. Our method outperforms the top pHLA modeling approach by up to 19% in structural accuracy, and consistently predicts blind targets not included in our training set. Insights from our work may be applied towards predicting antigen immunogenicity, and receptor cross-reactivity.

Targeting the melanoma-associated antigen CSPG4 with HLA-C*07:01-restricted T-cell receptors

Intorduction

Chondroitin sulfate proteoglycan 4 (CSPG4), also known as high molecular weight-melanoma associated antigen, is expressed in melanoma but also other tumor entities and constitutes an attractive target for immunotherapeutic approaches. While recent preclinical reports focused on anti-CSPG4 chimeric antigen receptors (CAR), we here explore T-cell receptor (TCR)-based approaches targeting CSPG4.

Methods

The TCRs of two CSPG4-reactive T-cell clones (11C/73 and 2C/165) restricted by the highly prevalent HLA-C*07:01 allele were isolated and the respective αβTCR pairs were retrovirally expressed in CRISPR/Cas9-edited TCR-knockout T cells for functional testing. We also combined alpha and beta TCR chains derived from 11C/73 and 2C/165 in a cross-over fashion to assess for hemichain dominance. CSPG4+ melanoma, glioblastoma and lung cancer cell lines were identified and, if negative, retrovirally transduced with HLA-C*07:01.

Results

Functional tests confirmed specific recognition of CSPG4+HLA-C*07:01+ target cells by the αβTCR retrieved from the parental T-cell clones and in part also by the cross-over TCR construct 2Cα-11Cβ. Despite high surface expression, the 11Cα-2Cβ combination, however, was not functional.

Discussion

Collectively, 11C/73- and 2C/165-expressing T cells specifically and efficiently recognized CSPG4+HLA-C*07:01+ cancer cells which warrants further preclinical and clinical evaluation of these TCRs.

MHC-II dynamics are maintained in HLA-DR allotypes to ensure catalyzed peptide exchange

Presentation of antigenic peptides by major histocompatibility complex class II (MHC-II) proteins determines T helper cell reactivity. The MHC-II genetic locus displays a large degree of allelic polymorphism influencing the peptide repertoire presented by the resulting MHC-II protein allotypes. During antigen processing, the human leukocyte antigen (HLA) molecule HLA-DM (DM) encounters these distinct allotypes and catalyzes exchange of the placeholder peptide CLIP by exploiting dynamic features of MHC-II. Here, we investigate 12 highly abundant CLIP-bound HLA-DRB1 allotypes and correlate dynamics to catalysis by DM. Despite large differences in thermodynamic stability, peptide exchange rates fall into a target range that maintains DM responsiveness. A DM-susceptible conformation is conserved in MHC-II molecules, and allosteric coupling between polymorphic sites affects dynamic states that influence DM catalysis. As exemplified for rheumatoid arthritis, we postulate that intrinsic dynamic features of peptide-MHC-II complexes contribute to the association of individual MHC-II allotypes with autoimmune disease.

HLA-A*02:06 allele may be susceptible to myelodysplastic syndrome in Zhejiang Han population, China

The association between HLA loci and haematological malignancy has been reported in certain populations. However, there are limited data for HLA loci at a high-resolution level with haematological malignancy in China. In this study, a total of 1115 patients with haematological malignancies (including 490 AML, 410 acute lymphoblastic leukaemia (ALL), 122 myelodysplastic syndrome [MDS] and 93 non-Hodgkin's lymphoma [NHL]) and 1836 healthy individuals as a control group in the Han population of Zhejiang Province, China, were genotyped for HLA-A, HLA-C, HLA-B, HLA-DRB1 and HLA-DQB1 loci at high resolution. The possible association between HLA alleles and haplotypes and haematologic malignancy was analysed. The allele frequencies (AFs) of HLA-A*02:05, HLA-A*02:06, HLA-A*32:01, HLA-B*35:03, HLA-B*54:01, HLA-B*55:07, HLA-DRB1*04:05, HLA-DRB1*15:01, HLA-DQB1*04:01 and HLA-DQB1*06:02 in the MDS patients were much higher than those in the control group (P < 0.05), while the AFs of HLA-C*07:02, HLA-DRB1*03:01, HLA-DRB1*14:54, HLA-DQB1*02:01 and HLA-DQB1*05:03 were obviously lower than those in the control group (p < .05). Interestingly, the differences in these HLA alleles in patients with MDS were not significant after applying Bonferroni correction (Pc > .05), except for HLA-A*02:06 (Pc < .01). There were 13, 6 and 10 HLA alleles with uncorrected significant differences (p < .05) among patients with AML, ALL and NHL, respectively, compared with those in the control group, but the differences in these HLA alleles were not significant after correction (Pc > .05). Compared to those of the control group, there were some haplotypes over 1.00% frequency in patients with AML, MDS and NHL patients with uncorrected significant differences (p < .05). However, none of them showed a significant difference after correction as well (Pc > .05). The study reveals that HLA-A*02:06 may lead to susceptibility to MDS, but none of the HLA alleles were associated with AML, ALL or NHL after correction. These data will help to further understand the role of HLA loci in the pathogenesis of haematological malignancy in China.