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PubMed2026

Immunopeptidomics-guided cancer vaccine design: Advances, challenges, and emerging opportunities.

Selecting clinically relevant tumor antigens remains a major challenge in the development of therapeutic cancer vaccines. Although computational approaches have considerably improved neoantigen prediction, many candidate epitopes identified in silico are not ultimately presented on the tumor cell surface. The emergence of immunopeptidomics has provided direct access to naturally processed HLA-associated peptides and has offered new opportunities for antigen discovery. Increasing evidence has shown that information derived from the immunopeptidome becomes considerably more informative when interpreted alongside genomic, transcriptomic, and proteomic data. This integrative view has broadened the spectrum of targetable antigens and has also revealed important limitations related to peptide abundance, HLA diversity, tumor heterogeneity, and the imperfect relationship between antigen presentation and immunogenicity. These issues have renewed interest in multi-antigen vaccine strategies designed to better reflect the complexity of tumor antigen landscapes. Advances in bioinformatics and artificial intelligence are facilitating the interpretation of increasingly complex datasets and are beginning to support more systematic approaches to antigen prioritization. In this review, we discuss how immunopeptidomics is contributing to next-generation cancer vaccine development, summarize the major translational challenges, and highlight emerging concepts that may improve the clinical applicability of immunopeptidomics-guided immunotherapy.

Cancer immunotherapy↗
PubMed2024

Innovations Toward Immunopeptidomics.

Over the past 30 years, immunopeptidomics has grown alongside improvements in mass spectrometry technology, genomics, transcriptomics, T cell receptor sequencing, and immunological assays to identify and characterize the targets of activated T cells. Together, multiple research groups with expertise in immunology, biochemistry, chemistry, and peptide mass spectrometry have come together to enable the isolation and sequence identification of endogenous major histocompatibility complex (MHC)-bound peptides. The idea to apply highly sensitive mass spectrometry techniques to study the landscape of peptide antigens presented by cell surface MHCs was innovative and continues to be successfully used and improved upon to deepen our understanding of how peptide antigens are processed and presented to T cells. Multiple research groups were involved in this bringing immunopeptidomics to the forefront of translational research, and we will highlight the contributions of one of the earliest developers, Professor Donald F. Hunt, and his research group at the University of Virginia. The Hunt laboratory applied cutting edge mass spectroscopy-based immunopeptidomics to study cancer, autoimmunity, transplant rejection, and infectious diseases. Across these diverse research areas, the Hunt laboratory and collaborators would characterize previously unknown MHC peptide-binding motifs and identify immunologically active antigens using ultra sensitive mass spectrometry techniques. Amazingly, many of the MHC-bound peptide antigens discovered in collaborations with the Hunt laboratory were sequenced by mass spectrometry before the completion of the human genome using manual de novo sequencing. In this perspective article, we will chronicle the work of the Hunt laboratory and their many collaborators that would be a major part of the foundation for mass spectrometry-based immunopeptidomics and its application to immunology research.

Animals↗
PubMed2026

Immunopeptidomics in gliomas: Decoding antigen presentation for precision immunotherapy.

Gliomas and particularly glioblastomas, represent the most aggressive and treatment-resistant brain tumours. Current standard treatments, including surgical resection, radiotherapy and chemotherapy, offer only limited long-term survival benefits. The highly immunosuppressive tumour microenvironment that characterizes gliomas enables immune evasion and limits the effectiveness of anti-tumour immune response, indicating the urgent need for identification of tumour antigens with clinical relevance to improve current immunotherapeutic strategies and enhance glioma immunogenicity. Immunopeptidomics, a mass spectrometry-based identification of peptides presented by HLA molecules, is a growing field of research for understanding the immunosurveillance of gliomas. By enabling the direct identification of naturally presented HLA-bound peptides from tumour tissue for T cell recognition, immunopeptidomics provide valuable insights into tumour antigen presentation and immune targeting. This review highlights the emerging role of immunopeptidomics in gliomas, covering the mechanisms of antigen processing and presentation by HLA class I and II molecules, the identification of glioma-associated antigens, the development of personalised peptide vaccines and the discovery of new targets for T cell-based immunotherapies. The potential of plasma-derived soluble HLA (sHLA) peptidomes as minimally invasive liquid-biopsy biomarkers is further discussed for disease monitoring and response to treatment. Overall, immunopeptidomics are foreseen as a powerful tool for the discovery of new tumour antigens leading to the development of more effective personalised glioma immunotherapies.

Humans↗
PubMed2026

Mass Spectrometry-Based Profiling of Personalized Immunopeptidomes in Thai Renal Cell Carcinoma.

This study profiles the personalized immunopeptidomes of 13 Thai patients with renal cell carcinoma (RCC), addressing a critical knowledge gap in Southeast Asian populations characterized by distinct HLA allele distributions. We combined whole-exome sequencing (WES)-based personalized proteome construction with liquid chromatography-tandem mass spectrometry (LC-MS/MS), using both database-driven searches and de novo peptide sequencing. HLA typing identified several class I allotypes that are underrepresented in publicly available immunopeptidome resources, including seven alleles not previously represented in the databases examined; HLA-A*11:01 was the most frequent allele in this cohort. Database-based analysis identified a single tumor-specific neoantigen derived from a mutant JADE2 peptide in the patient with the highest tumor mutational burden, which was validated by a mutant-specific ELISPOT response. In contrast, de novo sequencing revealed numerous noncanonical peptides, a subset of which were supported by proteogenomic validation using PepQuery and detected exclusively in cancer proteomes but not in normal tissue data sets, indicating their potential as tumor-associated antigen candidates. Together, these results establish an integrated and scalable framework for identifying HLA-presented tumor-derived peptides and provide a foundational immunopeptidome resource to support personalized cancer immunotherapy development in Southeast Asia.

Humans↗
PubMed2024

optiPRM: A Targeted Immunopeptidomics LC-MS Workflow With Ultra-High Sensitivity for the Detection of Mutation-Derived Tumor Neoepitopes From Limited Input Material.

Personalized cancer immunotherapies such as therapeutic vaccines and adoptive transfer of T cell receptor-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen class I molecules to cytotoxic T cells. Such neoepitopes can for example arise from somatic mutations and their identification is crucial for the rational design of new therapeutic interventions. Liquid chromatography mass spectrometry (LC-MS)-based immunopeptidomics is the only method to directly prove actual peptide presentation and we have developed a parameter optimization workflow to tune targeted assays for maximum detection sensitivity on a per peptide basis, termed optiPRM. Optimization of collision energy using optiPRM allows for the improved detection of low abundant peptides that are very hard to detect using standard parameters. Applying this to immunopeptidomics, we detected a neoepitope in a patient-derived xenograft from as little as 2.5 × 106 cells input. Application of the workflow on small patient tumor samples allowed for the detection of five mutation-derived neoepitopes in three patients. One neoepitope was confirmed to be recognized by patient T cells. In conclusion, optiPRM, a targeted MS workflow reaching ultra-high sensitivity by per peptide parameter optimization, makes the identification of actionable neoepitopes possible from sample sizes usually available in the clinic.

Humans↗
PubMed2026

Noncanonical Transcription and Splicing Shape the Colorectal Cancer Immunopeptidome in MSI and MSS Tumors.

Treatment with immune checkpoint inhibitors in colorectal cancer (CRC) has largely benefited patients with microsatellite instability-high (MSI-H) and not the larger proportion of patient with microsatellite-stable (MSS) tumors. This clinical dichotomy has fueled the view that high mutational burden is the dominant driver of tumor immunogenicity and that MSS CRC fails to respond because it is "antigen poor". To directly test this premise and define the origins of presented tumor antigens, we integrated HLA class I immunopeptidomics and matched RNA-seq from 26 primary CRC tumors spanning MSI-H and MSS subtypes. Using patient-specific canonical and cancer-specific proteogenomic databases, we identified 115,292 unique major histocompatibility complex (MHC)-associated peptides (MAPs) across 61 HLA alleles, with a mean of 9292 MAPs per tumor and no significant difference in MAP counts between MSI-H and MSS tumors. In toto, we identified 266 tumor antigens, all coded by unmutated genomic sequences, comprising 70 aberrantly expressed tumor-specific antigens (aeTSAs) and 196 tumor-associated antigens (TAAs). In our cohort, MSS tumors presented more TAAs and a comparable number of aeTSAs per tumor relative to MSI-H tumors. In TCGA-COAD stratified analyses (483 tumors), MSS tumors yielded more presentable aeTSAs and TAAs per patient than MSI-H tumors. Across both subtypes, aeTSAs arose predominantly from intronic translation, UTR usage, retroelement activation, and germline-like transcription, including recurrent aeTSAs from PIWIL1, L1TD1, and endogenous retroviral loci. Together, these data demonstrate that MSS CRC is not antigen poor and highlight noncanonical translation as a major, previously underappreciated contributor to the CRC immunopeptidome.

Humans↗
PubMed2026

Immunopeptidomics-driven MHC class II peptide-binding motif discovery for 2 common canine DR alleles.

Despite the central role of major histocompatibility complex (MHC) class II in adaptive immunity, peptide-binding motifs have yet to be characterized for any canine MHC class II allele. Here, we report the first immunopeptidomics-derived binding motifs for DLA-DRB1*015:01 (DLA-DR15) and DLA-DRB1*012:01 (DLA-DR12), 2 alleles overrepresented in breeds predisposed to immune-mediated diseases. Because dogs co-express DLA-DR and DLA-DQ, the MHC class II Ab clone YKIX334.2 was validated to be DLA-DR-specific, enabling allele-selective immunoaffinity purification of DLA-DR molecules from homozygous DLA-DR15 and DLA-DR12 donor spleens. Mass spectrometry and GibbsCluster motif deconvolution of 838 DLA-DR15-associated and 644 DLA-DR12-associated peptides eluted from their respective peptide-binding grooves revealed distinct allele-specific binding motifs, with characterization of anchor residue preferences, peptide-length distributions, cross-species comparisons with human and murine MHC class II motifs, and source protein composition of the eluted self-peptidome. To evaluate the translational utility of these motifs, recombinant DLA-DR15 and DLA-DR12 molecules were used to screen rabies virus glycoprotein and nucleoprotein peptide libraries via fluorescence-based peptide competition assays, identifying high-affinity candidate binders for both alleles. Spearman rank correlation between immunopeptidomics-derived position-specific scoring matrix scores and peptide competition assay rankings demonstrated modest associations, consistent with these approaches capturing complementary dimensions of peptide-MHC class II interaction. Ultimately, these findings establish what we believe is the first allele-specific peptide-binding motif framework for canine MHC class II, providing a foundation for DLA-allele-informed CD4+ T-cell epitope discovery studies and Ag-specific immune response characterization in the dog.

Animals↗
PubMed2024

Immunopeptidomics Mapping of Listeria monocytogenes T Cell Epitopes in Mice.

Listeria monocytogenes is a foodborne intracellular bacterial model pathogen. Protective immunity against Listeria depends on an effective CD8+ T cell response, but very few T cell epitopes are known in mice as a common animal infection model for listeriosis. To identify epitopes, we screened for Listeria immunopeptides presented in the spleen of infected mice by mass spectrometry-based immunopeptidomics. We mapped more than 6000 mouse self-peptides presented on MHC class I molecules, including 12 high confident Listeria peptides from 12 different bacterial proteins. Bacterial immunopeptides with confirmed fragmentation spectra were further tested for their potential to activate CD8+ T cells, revealing VTYNYINI from the putative cell wall surface anchor family protein LMON_0576 as a novel bona fide peptide epitope. The epitope showed high biological potency in a prime boost model and can be used as a research tool to probe CD8+ T cell responses in the mouse models of Listeria infection. Together, our results demonstrate the power of immunopeptidomics for bacterial antigen identification.

Animals↗
PubMed2026

Innovative CRISPR/Cas9-Based Strategy for Allele-Specific HLA Peptidome Analysis Using a Pan-HLA Antibody.

Human leukocyte antigen (HLA) immunopeptidomics is restricted by the limited availability of allele-specific antibodies and by potential artifacts introduced by HLA overexpression systems. To address these challenges, we developed a CRISPR/Cas9-based strategy that selectively deletes undesired classical class I alleles while preserving a single endogenous allele, thereby enabling allele-resolved peptidome profiling with a pan-HLA class I antibody. As a proof of concept, we edited JY cells to eliminate HLA-B∗07:02 and HLA-C∗07:02 while retaining HLA-A∗02:01 (ΔBC clones). Peptide-HLA complexes were immunoprecipitated from WT and ΔBC clones using either the pan-HLA class I antibody W6/32 or the A∗02:01-specific antibody PA2.1, followed by nanoLC-MS/MS and computational HLA assignment. Deletion of HLA-B and HLA-C alleles caused an expected ∼55% reduction in total class I surface expression. Despite this, W6/32 immunoprecipitation from ΔBC clones recovered a comparable peptide yield to PA2.1 in WT cells. Binding predictions showed that most peptides identified in ΔBC clones using W6/32 were assigned to HLA-A∗02:01, with near-complete loss of HLA-B∗07:02- and HLA-C∗07:02-derived peptides. Sequence logo analysis confirmed the canonical A∗02:01 motif across conditions. The ΔBC W6/32 immunopeptidome exhibited a high degree of overlap (∼88%) with the WT PA2.1 repertoire, supporting the specificity and fidelity of the approach. These findings establish CRISPR-based editing of HLA alleles as a viable strategy for allele-specific immunopeptidome analysis using pan-HLA antibodies, supporting its potential application beyond this proof-of-concept system, reducing reliance on allele-specific reagents and facilitating the study of underrepresented HLA alleles.

Humans↗
PubMed2026

Beyond Canonical Neoantigens: Emerging Technologies for Identification of Noncanonical Antigens and Implications for Personalized Cancer Vaccines.

Over the past decade, advances in sequencing technologies and computational pipelines enabled the development of personalized cancer vaccines (PCVs). Current PCV strategies primarily target cancer neoantigens generated by non-synonymous DNA mutations, which can result in altered amino acid sequences capable of eliciting tumor-specific immune responses. More recently, a distinct class of tumor-specific antigens (TSA), termed noncanonical or cryptic antigens, has emerged as an additional source of immunogenic targets. Unlike canonical neoantigens, noncanonical antigens typically cannot be identified by tumor/normal whole-exome sequencing, as they do not arise from classical DNA mutations. Instead, they are often associated with less well recognized and/or aberrant processes in the pathways from DNA to human leukocyte antigen (HLA)-presented peptides. Examples include transposable elements, circular RNA, translation of alternative open reading frames and/or long non-coding RNA, among others. Emerging evidence suggests that noncanonical antigens represent a substantial portion of the tumor-specific immunopeptidome and, similar to canonical neoantigens, are absent during thymic selection and can evade central tolerance and elicit T cell responses. Technological advances have increasingly facilitated the identification of noncanonical antigens. Long-read RNA sequencing reveals noncanonical transcripts by improving transcriptome assembly, while ribosome profiling provides genome-wide maps of actively translated regions, facilitating the discovery of peptides from aberrant translation events. Specialized molecular approaches enable enrichment and sequencing of circular RNAs, and immunopeptidomics using mass spectrometry allows for direct characterization of HLA-presented peptides. Together, these technological advances have led to an increasing interest in prioritizing and targeting noncanonical antigens in the next generation of PCVs. This review provides an overview of the diverse origins of TSAs beyond classical neoantigens and discusses emerging approaches that may enable the integration of these antigens in future clinical trials.

circular RNA↗
PubMed2025

High-quality peptide evidence for annotating non-canonical open reading frames as human proteins.

A major scientific drive is to characterize the protein-coding genome as it provides the primary basis for the study of human health. But the fundamental question remains: what has been missed in prior genomic analyses? Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states, with major implications for proteomics, genomics, and clinical science. However, the impact of ncORFs has been limited by the absence of a large-scale understanding of their contribution to the human proteome. Here, we report the collaborative efforts of stakeholders in proteomics, immunopeptidomics, Ribo-seq ORF discovery, and gene annotation, to produce a consensus landscape of protein-level evidence for ncORFs. We show that at least 25% of a set of 7,264 ncORFs give rise to translated gene products, yielding over 3,000 peptides in a pan-proteome analysis encompassing 3.8 billion mass spectra from 95,520 experiments. With these data, we developed an annotation framework for ncORFs and created public tools for researchers through GENCODE and PeptideAtlas. This work will provide a platform to advance ncORF-derived proteins in biomedical discovery and, beyond humans, diverse animals and plants where ncORFs are similarly observed.

GENCODE↗
PubMed2025

Differential Alloreactivity: Lessons Learned From a Singular HLA Locus.

Alloreactivity entails the recognition of cells and tissues from one individual as foreign by T cells and other immune effectors from another individual. Alloreactive immune responses play an important role in various clinical contexts, in particular in transplantation. Major drivers of these responses are the highly immunogenic, non-self HLA molecules. However, the immunogenicity of these allogeneic HLA molecules has been observed to vary according to certain immunobiological and immunogenetic parameters, leading to the concept of differential alloreactivity. Recent progress in unveiling the underpinnings of this phenomenon has been made for the frequently mismatched HLA-DP allotypes, whose singular genomic, structural and population genetics characteristics offer an ideal scenario for these investigations. Studies in the HLA-DP context have highlighted the immunopeptidome overlap between self and non-self HLA allotypes, as well as its editing by non-classical class II chaperones HLA-DM and HLA-DO, as a main determinant of their immunogenicity likely via indirect effects of thymic education. Recent evidence suggests that these observations could also be extended to alloresponses directed against HLA molecules encoded by other loci. How these functional characteristics of HLA molecules shape allorecognition by T-cell subsets, and how they translate into different clinical consequences in the context of transplantation will be the subject of the present review.

Humans↗
PubMed2024

NovoBoard: A Comprehensive Framework for Evaluating the False Discovery Rate and Accuracy of De Novo Peptide Sequencing.

De novo peptide sequencing is one of the most fundamental research areas in mass spectrometry-based proteomics. Many methods have often been evaluated using a couple of simple metrics that do not fully reflect their overall performance. Moreover, there has not been an established method to estimate the false discovery rate (FDR) of de novo peptide-spectrum matches. Here we propose NovoBoard, a comprehensive framework to evaluate the performance of de novo peptide-sequencing methods. The framework consists of diverse benchmark datasets (including tryptic, nontryptic, immunopeptidomics, and different species) and a standard set of accuracy metrics to evaluate the fragment ions, amino acids, and peptides of the de novo results. More importantly, a new approach is designed to evaluate de novo peptide-sequencing methods on target-decoy spectra and to estimate and validate their FDRs. Our FDR estimation provides valuable information to assess the reliability of new peptides identified by de novo sequencing tools, especially when no ground-truth information is available to evaluate their accuracy. The FDR estimation can also be used to evaluate the capability of de novo peptide sequencing tools to distinguish between de novo peptide-spectrum matches and random matches. Our results thoroughly reveal the strengths and weaknesses of different de novo peptide-sequencing methods and how their performances depend on specific applications and the types of data.

Peptides↗
PubMed2026

Hidden proteins encoded by non-canonical open reading frames: A review.

There is increasing evidence that translation is not limited to annotated protein-coding genes. Ribosome profiling sequencing, mass spectrometry-based proteomics, and immunopeptidomics have identified the productive translation of non-canonical open reading frames (ORFs). This suggests that the functional proteome includes not only conserved proteins but also proteins hidden in non-coding RNAs and de novo proteins. Some of these translated products are functional peptides, while others may be non-functional, potentially arising from evolutionary events. Several non-canonical ORF-encoded peptides have been found to regulate multiple physiological and pathological functions, particularly in cancer, immunity, and inflammation, indicating that they have potential as biomarkers and novel therapeutic targets. To better understand the diversity of functional peptides and translated non-canonical ORFs based on existing data, we summarize their classification according to transcriptional features and supporting evidence, including non-canonical ORFs located in ncRNAs and canonical mRNAs. This review provides a concise summary of the origin, discovery methods, and classification of non-canonical ORFs. It offers insights into the origins and functions of non-canonical ORF-encoded peptides from an evolutionary perspective, while also exploring the biological functions and regulatory mechanisms of these non-canonical ORF-encoded hidden proteins in tumorigenesis and progression.

Open Reading Frames↗
PubMed2026

Receptor-defined targeting of a genomically unique melanoma-enriched noncanonical antigen.

Effective T cell-based immunotherapies require functional receptors that can be engineered and redeployed to recognize tumor-restricted antigens. Noncanonical peptides arising from transcription outside annotated protein-coding regions expand the antigenic landscape of cancer; however, systematic strategies to biologically prioritize and functionally validate such targets remain underdeveloped. Here, we integrated de novo transcript analysis, exon-resolved quantification, RNA in situ hybridization, and immunopeptidomics to identify melanoma-associated noncanonical transcripts and advance candidates through receptor-level validation. Among three recurrent melanoma-associated transcripts, EVA003 emerged as a lead target based on its distinct repeat-enriched genomic architecture, consistent tumor-enriched exon-level expression across independent datasets, and a genomically unique immunogenic core sequence. We demonstrate endogenous presentation of EVA003-derived peptides on HLA-A*03:01 and detect specific reactivity in patient-derived tumor-infiltrating lymphocytes. Single-cell transcriptomic profiling identified a dominant peptide-reactive clonotype, enabling isolation of a naturally occurring T cell receptor. Transfer of this receptor into healthy donor T cells conferred antigen-dependent activation and cytotoxicity against both peptide-pulsed targets and melanoma cells expressing EVA003 endogenously. Together, these findings establish a biologically informed strategy for prioritizing noncanonical tumor antigens and demonstrate that genomically unique, tumor-enriched noncanonical peptides can be presented to molecularly defined receptors capable of mediating cancer cell killing. These findings support the integration of prioritized noncanonical antigens into engineered T cell therapeutic strategies.

Humans↗
PubMed2026

Micropeptides encoded by lncRNAs associated with cancer progression reveal novel immunogenic epitopes.

MOTIVATION: Long non-coding RNAs (lncRNAs) regulate gene expression, chromatin organization, and cellular signaling. Recent studies indicate that ∼20% of the ∼36 000 human lncRNA genes harbor small open reading frames (sORFs) capable of producing micropeptides (MPs), whose functions remain largely unknown. Whether these peptides contribute to the cancer immunopeptidome is largely unexplored. RESULTS: We systematically analyzed lncRNAs with strong experimental and computational evidence of MP-encoding potential (∼13% of the initial MP collection). Using The Cancer Genome Atlas (TCGA), we identified 2606 high-confidence lncRNA-derived MPs encoded by 647 genes across 16 cancer types. We then focused on 501 MPs from 124 lncRNA genes whose expression changes significantly across tumor stages and metastatic transitions, representing cancer transitional lncRNAs (Tr-lncRNAs). Dipeptide composition and conservation analyses showed that these MPs differ from a size-matched human coding proteome, supporting their potential as neoantigens. All possible 9-mer peptides were evaluated for predicted binding to prevalent European HLA class I alleles. Approximately 60% of Tr-lncRNA genes and 184 (37%) of derived peptides exhibited strong predicted HLA binding. Peptides from XIST, PCAT7, PVT1, HAND2-AS1 showed broad HLA coverage. Notably, TTN-AS1, encoded an MP (79 aa) generated 33 predicted distinct epitopes spanning all 27 HLA alleles. Our analysis identifies lncRNA-derived MPs as a previously underexplored source of potential cancer neoantigens, highlighting their promise as biomarkers and targets for immunotherapy. AVAILABILITY: Data, code and supplementary materials are available in https://doi.org/10.5281/zenodo.20167452 and GitHub: https://github.com/stavzok1/lncrna_peptide_analysis.

Humans↗
PubMed2024

Omics studies in Behçet's disease.

PURPOSE OF REVIEW: In this review, we aimed to highlight recent findings from "-omics" studies in Behçet's disease. RECENT FINDINGS: Recent genomic studies in Behçet's disease identified possible risk loci associated with Behçet's disease related uveitis, neurologic involvement and gastrointestinal involvement. Additionally, sex-specific genetic effects were determined in Behçet's disease. Transcriptomic analyses of immune cells in Behçet's disease revealed that key inflammatory pathways such as NF-κB and MAPK have roles in Behçet's disease pathogenesis. Proteomic studies have highlighted the role of immune cell derived extracellular vesicles and identified potential biomarkers for vascular involvement and examined HLA I-bound immunopeptidomes. Metabolomics studies are still limited, but recent research has pointed to alterations in fatty acid metabolism and lipid profiles in Behçet's disease patient. SUMMARY: Omics studies have gained importance in the field of Behçet's disease through the generation of large data sets and efforts to extend their application are intensifying. These studies can provide opportunities for understanding Behçet's disease pathogenesis when they lead to testable hypotheses. Current challenges include the choice of appropriately homogeneous patient and control groups, effective data management and sharing, high cost and a rapidly increasing gap between the wealth of observational data generated and the relative paucity of controlled experimental efforts that could lead to mechanistic understanding.

Behcet Syndrome↗
PubMed2025

Donor HLA Class I Evolutionary Divergence and Late Allograft Rejection After Liver Transplantation in Children: An Emulated Target Trial.

HLA evolutionary divergence (HED), a continuous metric quantifying the differences between each amino acid of two homologous HLA alleles, reflects the importance of the immunopeptidome presented to T lymphocytes. It has been associated with rejection after liver transplantation. This retrospective cohort study aimed to analyse the potential effect of donor or recipient HED on liver transplant rejection in a new series of patients transplanted during childhood and followed in adulthood. The study included 120 children who had been transplanted between 1991 and 2010 and were followed by routine biopsies and histological evaluations with a median of 14.1 years post-LT. Liver biopsies were performed routinely 1, 5, 10 and 20 years after transplantation and in the event of liver dysfunction. HED was calculated using the physicochemical Grantham distance for donor and recipient Class I (HLA-A, -B, -C) and Class II (HLA-DRB1, -DQB1) alleles. The influence of HED on rejection was analysed using inverse probability weighting (IPW) and target trial emulation using the g method. Based on the IPW score, donor HED class I was correlated with the occurrence of late (> 90 days) rejection (HR, 1.19, 95% CI: 1.01-1.40) independently of HLA mismatches, donor age and initial induction. The emulated target trial confirmed that donor HED Class I has a causal effect on liver graft rejection and this relationship was observed long-term.

Humans↗