HLA最新文献

The interaction between T-cell receptors (TCRs) and antigenic peptides presented by HLA molecules is fundamental to adaptive immunity. However, the extreme polymorphism of HLA genes poses major challenges for transplantation, antigen discovery, immunotherapy and studies of allele-specific function. Although CRISPR/Cas9 has transformed gene editing, existing sgRNA design tools are not optimised for knockout of HLA Class I genes due to their high rates of polymorphism. To address this, we developed HLA-Knockout (https://hlaknockout.rutgers.edu), a novel web-based tool that enables precise, allele-specific targeting of HLA Class I genes. HLA-Knockout retrieves user-defined HLA sequences from the IPD-IMGT/HLA database and applies stringent design criteria, including mismatch filtering and PAM disruption analysis, to ensure high specificity and minimal off-target effects on non-target HLA Class I alleles. Using HLA-Knockout, we achieved efficient single- and double-allele HLA Class I knockouts in human cells without disrupting non-target HLA Class I alleles. Functional assays confirmed allele-specific loss of antigen-specific TCR activation, validating the platform's utility. HLA-Knockout provides a unique resource for dissecting HLA-restricted immune interactions and has broad applications in transplantation biology, autoimmunity and cancer immunotherapy.

The HLA-F is a non-classical HLA class I gene that belongs to the class Ib major histocompatibility complex (MHC) molecules. It is distinguished in the literature from its classical MHC class Ia counterparts by a minor frequency of polymorphisms. The exact function of HLA-F remains unknown, but recent publications emphasise the essential immunological role of this gene in infectious diseases, cancer research, organ transplantation and autoimmune diseases. The rapidly evolving sequencing techniques within the last years allow the accession of larger genomic regions at reasonable costs. In this regard we developed a long-range PCR assay, covering the entire HLA-F gene, including the flanking untranslated regions (UTRs). According to the positions of the 5′ and 3′ amplification primers, the PCR amplicon has a total length of 3.8 kb. After verification of our in-house developed LR-PCR with pre-typed cell-line derived DNA-samples from International HLA Reference Standards (IHWG), we analysed a randomly selected cohort of 763 DNA samples from the Stefan Morsch Stiftung stem cell donor registry on a MiSeq next generation sequencing (NGS) platform. This HLA-F genotyping project revealed so far unpublished data regarding the allele frequency distribution pattern as well as several new allelic variations, not listed yet in the IPD-IMGT/HLA Database. Prior to submission, all novel alleles were confirmed with Oxford Nanopore sequencing. Linkage disequilibrium between HLA-F and its neighbouring loci HLA-A and HLA-E was also assessed.

Microvascular inflammation (MVI) in kidney allografts in the absence of detectable donor-specific anti-HLA antibodies (DSA) is increasingly recognised as a cause of premature graft failure following kidney transplantation. Potential mechanisms include NK cell alloreactivity mediated by recognition of mismatched HLA class I molecules (missing-self) via killer-immunoglobulin-like receptors. Here, we report the case of an early kidney allograft rejection with severe MVI on biopsy in a patient that was fully HLA-matched except for a HLA-DPB1*04 mismatch in the donor. There were no detectable DSA at any time. MVI was successfully reversed and clinically stabilised with a 9-month course of daratumumab (anti-CD38 mAb). This case suggests alternative mechanisms of alloreactivity, such as NK cell-mediated effects, and highlights the existence of MVI in the absence of detectable B cell alloreactivity. Moreover, this case exemplifies the potential of anti-CD38 treatment in these patients.

Initially, chimeric antigen receptor (CAR) T-cell therapy was developed to eliminate malignant B cells in haematological B-cell malignancies by targeting CD19 and B-cell maturation antigen. This approach achieved notable success, resulting in (malignant) B-cell depletion and inducing clinical remission in cancer patients. The scope of CAR T-cell therapy has since expanded to various other applications. Recently, CD19-directed CAR T cells have shown promising results in treating B-cell-mediated autoimmune diseases, with patients experiencing long-lasting symptom cessation. Despite these advancements, the unselective targeting of both pathogenic and protective B cells calls for precise immunotherapies capable of selectively removing pathogenic B cells. Therefore, antigen-specific CARs were designed to specifically interact with and deplete subpopulations of target cells expressing the target antigens. Subsequently, modified CARs were introduced by incorporating autoantigens into the sequence, which allowed antigen-specific B cells to bind to CAR T cells. Additionally, antigen-specific CAR T cells have been exploited to treat viral infections. Moreover, CAR technology was expanded to regulatory T cells (Tregs), where CARs can be adopted to induce a tolerogenic environment in target tissues, offering new possibilities in autoimmune diseases, as well as prevention of graft-versus-host disease in haematopoietic stem cell transplantation and transplant rejection in the setting of solid organ transplantation. Although CAR T cells and CAR Tregs are promising and broadly explored, safety issues must be addressed and possible solutions thoroughly investigated. This review outlines the broad potential of CAR-based therapies in autoimmunity, virology and transplantation while addressing the need for solutions to current safety issues.

In HLA-incompatible transplantation, monitoring donor-specific antibodies (DSA) after transplantation informs clinical decision-making and the management of antibody-mediated rejection. Persistent post-transplant DSAs are associated with poorer graft survival compared to cases where DSAs resolve. Previously, four distinct early post-transplant DSA dynamic patterns were identified using a unique dataset with frequent DSA measurements and shown to be associated with AMR and graft outcomes. However, frequent testing is costly, and predicting outcomes using fewer DSA measurements could improve monitoring efficiency. A machine learning classifier based on dynamic time warping was used to identify early post-transplant DSA patterns from a reduced set of measurements. Individual days and day combinations within the first 50 post-transplant days were systematically evaluated. The combinations with the highest classification accuracy compared to using all available time points were selected as optimal. This study determined the minimum number of DSA screenings required to accurately classify early DSA dynamics. Measuring DSAs on Days 1, 10, and either 26 or 34 identified the four dynamic patterns with 93.7% accuracy. Including both Days 26 and 34 increased the accuracy to 96.9%. Testing beyond Day 34 did not yield further improvement in classification. Several monitoring regimens commonly used in clinical practice were evaluated, and the proposed approach outperformed all of them. This study identifies an efficient DSA monitoring strategy that can predict antibody behaviour early post-transplant, enabling timely intervention. It also addresses inconsistencies in current monitoring practices, offering evidence for standardised, data-driven protocols for more precise and efficient post-transplant care.