HLA Peptide Research Articles

Peptide Sharing Between CMV and Mismatched HLA Class I Peptides Promotes Early T-Cell-Mediated Rejection After Kidney Transplantation.

Cytomegalovirus (CMV) infection is related to acute rejection and graft loss after kidney transplantation, though the underlying mechanism remains largely unknown. Some CMV strains produce a peptide that is identical to a peptide sequence found in the leader peptide of specific HLA-A and -C alleles. In this retrospective study of 351 kidney transplantations, we explored whether CMV-seropositive recipients without the VMAPRTLIL, VMAPRTLLL or VMAPRTLVL HLA class I leader peptide receiving a transplant from a donor with this peptide, faced an increased risk of T-cell-mediated rejection (TCMR) in the first 90 days after transplantation. An independent case-control cohort was used for validation (n = 122). The combination of recipient CMV seropositivity with the VMAPRTLIL peptide mismatch was associated with TCMR with a hazard ratio (HR) of 3.06 (p = 0.001) in a multivariable analysis. Similarly, the VMAPRTLLL peptide mismatch was associated with TCMR revealing a HR of 2.61 (p = 0.008). Transplantations featuring either a VMAPRTLIL or a VMAPRTLLL peptide mismatch had a significantly higher cumulative TCMR incidence (p < 0.0001), with the primary impact observed in the first 2 weeks post-transplantation. The findings could be validated in an independent cohort. Together, our data strongly suggest that CMV-positive recipients without an HLA peptide identical to a CMV peptide yet transplanted with a donor who does possess this peptide, have a significantly increased risk of early TCMR. Considering the prevention of such an leader peptide mismatch in these patients or adjusting immunosuppression protocols accordingly may hold promise in reducing the incidence of early TCMR.

Complex Interactions between the Human Major Histocompatibility Complex (MHC) and Microbiota: Their Roles in Disease Pathogenesis and Immune System Regulation.

The relationship between microbiota and the immune system is complex and characterized by the ways in which microbiota directs immune function interactions, both innate and acquired and also keeps activating the immune system throughout an individual's life. In this respect, the human Major Histocompatibility Complex (MHC, referred to as HLA in humans) plays a crucial role and is also established in self-defense against microbes by presenting microbial-derived peptides to the immune cells. However, this assumption has some unclear aspects that should be investigated. For example, how is the microbiota shaped by microbe species diversity, quantity and functions of the immune system, as well as the role and molecular mechanisms of the HLA complex during this process. There are autoimmune diseases related to both HLA and specific microbiota changes or alterations, many of which are mentioned in the present review. In addition, the HLA peptide presenting function should be put in a framework together with its linkage to diseases and also with HLA compatibility necessary for transplants to be successful. These are still quite an enigmatically statistical and phenomenological approach, but no firm pathogenic mechanisms have been described; thus, HLA's real functioning is still to be fully unveiled. After many years of HLA single-genes studies, firm pathogenesis mechanisms underlying disease linkage have been discovered. Finally, microbiota has been defined as conformed by bacteria, protozoa, archaea, fungi, and viruses; notwithstanding, endogenous viral sequences integrated into the human genome and other viral particles (obelisks) recently found in the digestive mucosa should be taken into account because they may influence both the microbiome and the immune system and their interactions. In this context, we propose to integrate these microbial-genetic particle components into the microbiome concept and designate it as "microgenobiota".

Systematic Assessment of Deep Learning-Based Predictors of Fragmentation Intensity Profiles.

In recent years, several deep learning-based methods have been proposed for predicting peptide fragment intensities. This study aims to provide a comprehensive assessment of six such methods, namely Prosit, DeepMass:Prism, pDeep3, AlphaPeptDeep, Prosit Transformer, and the method proposed by Guan et al. To this end, we evaluated the accuracy of the predicted intensity profiles for close to 1.7 million precursors (including both tryptic and HLA peptides) corresponding to more than 18 million experimental spectra procured from 40 independent submissions to the PRIDE repository that were acquired for different species using a variety of instruments and different dissociation types/energies. Specifically, for each method, distributions of similarity (measured by Pearson's correlation and normalized angle) between the predicted and the corresponding experimental b and y fragment intensities were generated. These distributions were used to ascertain the prediction accuracy and rank the prediction methods for particular types of experimental conditions. The effect of variables like precursor charge, length, and collision energy on the prediction accuracy was also investigated. In addition to prediction accuracy, the methods were evaluated in terms of prediction speed. The systematic assessment of these six methods may help in choosing the right method for MS/MS spectra prediction for particular needs.

Interrelation of HLA-I and class II major histocompatibility complex molecules with clinical and morphological signs of breast cancer: A retrospective cohort study

Background. For a long time, interest in the HLA peptide complex is unabated, the clinical significance of which in cancer is still the subject of intense debate. Through the presentation of HLA antigens, tumor cells become available for recognition and destruction by effector cells of the immune system. A detailed analysis of the expression status of HLA molecules by breast cancer cells is of both scientific and important practical value. It can provide additional information about the immune system to determine a further strategy for treating breast cancer.&#x0D; Aim. To evaluate the frequency of expression of HLA-I and class II molecules by breast cancer cells and to determine its relationship with the morphological and clinical characteristics of the tumor.&#x0D; Materials and methods. This study included 82 patients with breast cancer who received treatment at the Blokhin National Medical Research Center of Oncology. Immunophenotyping of the primary tumor was performed by the immunohistochemical method (immunofluorescent staining) on cryostat sections. The reaction was evaluated using a ZEISS luminescent microscope (AXIOSKOP, Germany). The frequency of expression of HLA-I and class II molecules was studied depending on the clinical and morphological characteristics of breast cancer.&#x0D; Results. It was found that the frequency of expression of HLA I and II class molecules by breast cancer cells differed. HLA class I antigens are preserved in almost half of the cases 54.5%, while HLA class II antigens are preserved in 22.0%. Associations of molecules of the major histocompatibility complex with clinical and morphological signs of breast cancer were revealed. The frequency of HLA-DR negative cases increases in the stage advanсed (p=0.029). The frequency of monomorphic expression of HLA class II with T1 tumor was 50% versus 0% at T4 tumor (p=0.032). Estrogen receptor-negative tumors in most cases did not express HLA-II class (85.2% vs 64%; p=0.034). No connection with other clinical and morphological features of the tumor has been established.&#x0D; Conclusion. In most cases of breast cancer, the expression of HLA class II molecules is lost, while the expression of HLA class I is preserved in half of the cases. Monomorphic expression of HLA class II is characteristic of the early stage of breast cancer development and predominantly of receptor-positive tumors.

Usefulness of Docking and Molecular Dynamics in Selecting Tumor Neoantigens to Design Personalized Cancer Vaccines: A Proof of Concept.

Personalized cancer vaccines based on neoantigens are a new and promising treatment for cancer; however, there are still multiple unresolved challenges to using this type of immunotherapy. Among these, the effective identification of immunogenic neoantigens stands out, since the in silico tools used generate a significant portion of false positives. Inclusion of molecular simulation techniques can refine the results these tools produce. In this work, we explored docking and molecular dynamics to study the association between the stability of peptide-HLA complexes and their immunogenicity, using as a proof of concept two HLA-A2-restricted neoantigens that were already evaluated in vitro. The results obtained were in accordance with the in vitro immunogenicity, since the immunogenic neoantigen ASTN1 remained bound at both ends to the HLA-A2 molecule. Additionally, molecular dynamic simulation suggests that position 1 of the peptide has a more relevant role in stabilizing the N-terminus than previously proposed. Likewise, the mutations may have a "delocalized" effect on the peptide-HLA interaction, which means that the mutated amino acid influences the intensity of the interactions of distant amino acids of the peptide with the HLA. These findings allow us to propose the inclusion of molecular simulation techniques to improve the identification of neoantigens for cancer vaccines.

Sensitive, High-Throughput HLA-I and HLA-II Immunopeptidomics Using Parallel Accumulation-Serial Fragmentation Mass Spectrometry

Comprehensive and in-depth identification of the human leukocyte antigen class I (HLA-I) and class II (HLA-II) tumor immunopeptidome can inform the development of cancer immunotherapies. Mass spectrometry (MS) is a powerful technology for direct identification of HLA peptides from patient-derived tumor samples or cell lines. However, achieving sufficient coverage to detect rare and clinically relevant antigens requires highly sensitive MS-based acquisition methods and large amounts of sample. While immunopeptidome depth can be increased by off-line fractionation prior to MS, its use is impractical when analyzing limited amounts of primary tissue biopsies. To address this challenge, we developed and applied a high-throughput, sensitive, and single-shot MS-based immunopeptidomics workflow that leverages trapped ion mobility time-of-flight MS on the Bruker timsTOF single-cell proteomics system (SCP). We demonstrate greater than twofold improved coverage of HLA immunopeptidomes relative to prior methods with up to 15,000 distinct HLA-I and HLA-II peptides from 4e7 cells. Our optimized single-shot MS acquisition method on the timsTOF SCP maintains high coverage, eliminates the need for off-line fractionation, and reduces input requirements to as few as 1e6 A375cells for >800 distinct HLA-I peptides. This depth is sufficient to identify HLA-I peptides derived from cancer-testis antigen and noncanonical proteins. We also apply our optimized single-shot SCP acquisition methods to tumor-derived samples, enabling sensitive, high-throughput, and reproducible immunopeptidome profiling with detection of clinically relevant peptides from less than 4e7 cells or 15mg wet weight tissue.

A Sampling of Highlights from the Literature.

What We're Reading| May 03 2023 A Sampling of Highlights from the Literature: Article Recommendations from Our Deputy and Senior Editors Author & Article Information Online ISSN: 2326-6074 Print ISSN: 2326-6066 ©2023 American Association for Cancer Research2023American Association for Cancer Research Cancer Immunol Res (2023) 11 (5): 557. https://doi.org/10.1158/2326-6066.CIR-11-5-WWR Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn Email Tools Icon Tools Get Permissions Cite Icon Cite Search Site Article Versions Icon Versions Version of Record May 3 2023 Citation A Sampling of Highlights from the Literature: Article Recommendations from Our Deputy and Senior Editors. Cancer Immunol Res 1 May 2023; 11 (5): 557. https://doi.org/10.1158/2326-6066.CIR-11-5-WWR Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest Search Advanced Search Polyclonal neoantigen-specific T-cell responses associate with anti–PD-1 benefit (from Alex Ritter, Jennifer Lippincott Schwartz and Gillian Griffiths via NIH Flickr) To better understand differences in the immune response in patients with metastatic melanoma who do and do not have a clinical response to anti–PD-1 therapy, Puig-Saus et al. generated neoantigen-specific T cells from 11 patients using personalized neoantigen peptide–HLA libraries. Responding and nonresponding patients had neoantigen-specific CD8+ T cells in peripheral blood and tumor that recognized a limited number of mutations, but the CD8+ T cells from those who responded to therapy were more polyclonal, with multiple neoantigen-specific T-cell receptor clonotypes for the mutations, and were detected longitudinally, highlighting important immune characteristics of a successful clinical response to anti–PD-1 therapy. Puig-Saus C, …, Ribas A. Nature 2023 March 8;615:697–704. Neutrophils have a key role in tumor control following immunotherapy (from SVG) Neutrophils can have both pro- and... You do not currently have access to this content.

Quantification of Neoantigen-Mediated Immunoediting in Cancer Evolution—Letter

Quantification of Neoantigen-Mediated Immunoediting in Cancer Evolution—Letter

The Intracellular Proteome as a Source for Novel Targets in CAR-T and T-Cell Engagers-Based Immunotherapy.

The impressive clinical success of cancer immunotherapy has motivated the continued search for new targets that may serve to guide potent effector functions in an attempt to efficiently kill malignant cells. The intracellular proteome is an interesting source for such new targets, such as neo-antigens and others, with growing interest in their application for cell-based immunotherapies. These intracellular-derived targets are peptides presented by MHC class I molecules on the cell surface of malignant cells. These disease-specific class I HLA-peptide complexes can be targeted by specific TCRs or by antibodies that mimic TCR-specificity, termed TCR-like (TCRL) antibodies. Adoptive cell transfer of TCR engineered T cells and T-cell-receptor-like based CAR-T cells, targeted against a peptide-MHC of interest, are currently tested as cancer therapeutic agents in pre-clinical and clinical trials, along with soluble TCR- and TCRL-based agents, such as immunotoxins and bi-specific T cell engagers. Targeting the intracellular proteome using TCRL- and TCR-based molecules shows promising results in cancer immunotherapy, as exemplified by the success of the anti-gp100/HLA-A2 TCR-based T cell engager, recently approved by the FDA for the treatment of unresectable or metastatic uveal melanoma. This review is focused on the selection and isolation processes of TCR- and TCRL-based targeting moieties, with a spotlight on pre-clinical and clinical studies, examining peptide-MHC targeting agents in cancer immunotherapy.

AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics

Machine learning and in particular deep learning (DL) are increasingly important in mass spectrometry (MS)-based proteomics. Recent DL models can predict the retention time, ion mobility and fragment intensities of a peptide just from the amino acid sequence with good accuracy. However, DL is a very rapidly developing field with new neural network architectures frequently appearing, which are challenging to incorporate for proteomics researchers. Here we introduce AlphaPeptDeep, a modular Python framework built on the PyTorch DL library that learns and predicts the properties of peptides (https://github.com/MannLabs/alphapeptdeep). It features a model shop that enables non-specialists to create models in just a few lines of code. AlphaPeptDeep represents post-translational modifications in a generic manner, even if only the chemical composition is known. Extensive use of transfer learning obviates the need for large data sets to refine models for particular experimental conditions. The AlphaPeptDeep models for predicting retention time, collisional cross sections and fragment intensities are at least on par with existing tools. Additional sequence-based properties can also be predicted by AlphaPeptDeep, as demonstrated with a HLA peptide prediction model to improve HLA peptide identification for data-independent acquisition (https://github.com/MannLabs/PeptDeep-HLA).

Molecular Basis for the Recognition of HIV Nef138-8 Epitope by a Pair of Human Public T Cell Receptors.

Cross-recognized public TCRs against HIV epitopes have been proposed to be important for the control of AIDS disease progression and HIV variants. The overlapping Nef138-8 and Nef138-10 peptides from the HIV Nef protein are HLA-A24-restricted immunodominant T cell epitopes, and an HIV mutant strain with a Y139F substitution in Nef protein can result in immune escape and is widespread in Japan. Here, we identified a pair of public TCRs specific to the HLA-A24-restricted Nef-138-8 epitope using PBMCs from White and Japanese patients, respectively, namely TD08 and H25-11. The gene use of the variable domain for TD08 and H25-11 is TRAV8-3, TRAJ10 for the α-chain and TRBV7-9, TRBD1*01, TRBJ2-5 for the β-chain. Both TCRs can recognize wild-type and Y2F-mutated Nef138-8 epitopes. We further determined three complex structures, including TD08/HLA-A24-Nef138-8, H25-11/HLA-A24-Nef138-8, and TD08/HLA-A24-Nef138-8 (2F). Then, we revealed the molecular basis of the public TCR binding to the peptide HLA, which mostly relies on the interaction between the TCR and HLA and can tolerate the mutation in the Nef138-8 peptide. These findings promote the molecular understanding of T cell immunity against HIV epitopes and provide an important basis for the engineering of TCRs to develop T cell-based immunotherapy against HIV infection.

Redirecting Polyclonal T Cells against Cancer with Soluble T-Cell Receptors.

Cancer cells accumulate genetic mutations in coding proteins that may be presented by HLA as neoantigenic peptides (peptide HLA, pHLA). T cells scan for neoantigenic pHLA by the T-cell receptor (TCR):CD3 complex. This complex has the dual function of binding pHLA, by the TCR, and triggering T-cell activation by CD3. Checkpoint therapy activates exhausted T cells to kill cancer cells and generally work best against tumors with high neoantigen burden and in patients with neoantigenic-reactive T cells. TCR T-cell engagers (TCE) are a novel class of immunotherapy that bypasses these two requirements by redirecting polyclonal T cells, regardless of their native specificity, to kill a cancer cell independent of neoantigen burden. This is accomplished through deconstructing the membrane-bound TCR:CD3 complex into a soluble bispecific protein comprised of a targeting domain (TCR) and activating domain (usually anti-CD3 single-chain variable fragment). The pool of targets for TCR TCE is larger than for antibody therapeutics and includes >90% of human intra- or extracellular proteins. Most tumor-associated antigens for solid tumors are intracellular and accessible only by a TCR therapeutic. Tebentafusp, a TCR TCE directed to a peptide derived from the gp100 melanoma protein presented by HLA*A02:01, demonstrated a survival benefit in metastatic uveal melanoma (mUM). This survival benefit highlights the promise of TCR TCEs because mUM is a solid tumor with a very low neoantigen burden and has poor response to checkpoints and chemotherapy. Other TCR TCE programs are now in clinical studies for a broader range of tumors.

Modification of the HLA-A*24:02 Peptide Binding Pocket Enhances Cognate Peptide-Binding Capacity and Antigen-Specific T Cell Activation.

The immunogenicity of a T cell Ag is correlated with the ability of its antigenic epitope to bind HLA and be stably presented to T cells. This presents a challenge for the development of effective cancer immunotherapies, as many self-derived tumor-associated epitopes elicit weak T cell responses, in part due to weak binding affinity to HLA. Traditional methods to increase peptide-HLA binding affinity involve modifying the peptide to reflect HLA allele binding preferences. Using a different approach, we sought to analyze whether the immunogenicity of wild-type peptides could be altered through modification of the HLA binding pocket. After analyzing HLA class I peptide binding pocket alignments, we identified an alanine 81 to leucine (A81L) modification within the F binding pocket of HLA-A*24:02 that was found to heighten the ability of artificial APCs to retain and present HLA-A*24:02-restricted peptides, resulting in increased T cell responses while retaining Ag specificity. This modification led to increased peptide exchange efficiencies for enhanced detection of low-avidity T cells and, when expressed on artificial APCs, resulted in greater expansion of Ag-specific T cells from melanoma-derived tumor-infiltrating lymphocytes. Our study provides an example of how modifications to the HLA binding pocket can enhance wild-type cognate peptide presentation to heighten T cell activation.

Mechanisms of CD8+ T-cell failure in chronic hepatitis E virus infection.

In immunosuppressed patients, persistent HEV infection is common and may lead to cirrhosis and liver failure. HEV clearance depends on an effective virus-specific CD8+ T-cell response; however, the knowledge gap around HEV-specific CD8+ T-cell epitopes has hindered analysis of the mechanisms of T-cell failure in persistent infection. We comprehensively studied HEV-specific CD8+ T-cell responses in 46 patients with self-limiting (n= 34) or chronic HEV infection (n= 12), by epitope-specific expansion, functional testing, exvivo peptide HLA class I tetramer multi-parametric staining, and viral sequence analysis. We identified 25 HEV-specific CD8+ T-cell epitopes restricted by 9 different HLA class I alleles. In self-limiting HEV infection, HEV-specific CD8+ T cells were vigorous, contracted after resolution of infection, and formed functional memory responses. In contrast, in chronic infection, the HEV-specific CD8+ T-cell response was diminished, declined over time, and displayed phenotypic features of exhaustion. However, improved proliferation of HEV-specific CD8+ T cells, increased interferon-γ production and evolution of a memory-like phenotype were observed upon reduction of immunosuppression and/or ribavirin treatment and were associated with viral clearance. In 1 patient, mutational viral escape in a targeted CD8+ T-cell epitope contributed to CD8+ T-cell failure. Chronic HEV infection is associated with HEV-specific CD8+ T-cell exhaustion, indicating that T-cell exhaustion driven by persisting antigen recognition also occurs in severely immunosuppressed hosts. Functional reinvigoration of virus-specific T cells is at least partially possible when antigen is cleared. In a minority of patients, viral escape also contributes to HEV-specific CD8+ T-cell failure and thus needs to be considered in personalized immunotherapeutic approaches. Hepatitis E virus (HEV) infection is usually cleared spontaneously (without treatment) in patients with fully functioning immune systems. In immunosuppressed patients, chronic HEV infection is common and can progress rapidly to cirrhosis and liver failure. Herein, we identified the presence of HEV-specific CD8+ T cells (a specific type of immune cell that can target HEV) in immunosuppressed patients, but we show that these cells do not function properly. This dysfunction appears to play a role in the development of chronic HEV infection in vulnerable patients.

Analysis of the ZNT8, GAD65, HLA-DQA1, HLA-DQB1, and C-peptides in Indonesian children with type 1 diabetes mellitus

Autoimmune reaction in Type 1 Diabetes Mellitus (T1DM) is caused by genetic and environmental factors. The genes HLA-DQA1 and HLA-DQB1 are strongly associated with T1DM. Other established markers of T1DM were Zinc Transporter 8 Antibody (ZnT8), Glutamic Acid Decarboxylase Antibody-65 (GAD65), and C-peptide. This study aims to analyze ZnT8, GAD65, HLA-DQA1, HLA-DQB1, and C-peptide in Indonesian children with T1DM. A cross-sectional study of T1DM children was conducted in Dr. Soetomo Hospital, Indonesia. ZnT8, GAD65, HLA-DQA1, HLA-DQB1, and C-peptide were examined with an ELISA kit. Mann-Whitney test was performed with a significant value of p&lt;0.05. A total of 62 participants consisting of 31 children for each group were enrolled. The prevalence of ZnT8, GAD65, and C-peptide in T1DM patients was 77.4%, 90.3%, and 87.1%. There are 74% of T1DM children had two positive antibodies and 55% had two positive HLA peptides. There was no difference in HLA-DQA1 and HLA-DQB1 peptides between T1DM and control groups (p=0.12; p=0.19). Meanwhile, the comparison between ZnT8, GAD65, and C-Peptide values between T1DM and control groups shows a significant difference (p&lt;0.05). HLA-DQA1 peptide value was higher in T1DM children and HLA-DQB1 peptide value was higher in non-T1DM children.

Spliced HLA peptides, a novel source for melanoma immunotherapy

Human leukocyte antigen class I (HLA-I) molecules sample the proteome following the degradation of intracellular proteins via the proteasome and other proteolytic mechanisms. These complexes of HLA-I and peptide (pHLA) are then recognized by T cells and the nature of the bound peptide ligand is the key driver of adaptive immunity. We have developed a sophisticated data-driven workflow for the identification of cis and trans- spliced peptide antigens. We have shown for 17 different monoallelic cell lines, that up to 40% of pHLA are generated through post-translational splicing mechanisms. We also found that spliced pep- tides display canonical HLA-binding sequence features(1). To understand the biological relevance of spliced peptides, we have interrogated the immunopeptidome of HLA-I molecules immunoaffinity purified from influenza-infected cells using LC-MS/MS and the novel bioinformatic pipeline. We have applied our approach to p-HLA derived from multiple melanoma cell line and identified~30% cis and trans HLA-I spliced peptides. Of note, more than more 100 spliced peptides were derived from melanoma-associated antigens (MAA) and ~40% of known MAA were only represented by spliced peptides. Immunogenicity studies of a subset of the MAA shown that multiple of the tested spliced peptides were highly immunogenic, compared to a smaller fraction of linear peptides. Our results highlight the complexity and diversity of HLA peptide antigen presentation and identify a mechanism whereby the available peptidome is diversified to enhance immunity. We found spliced pep- tides may yield more immunogenic epitopes than are available from the viral/cancer genome. Moreover, some antigens lack high-affinity HLA-ligands and the peptide splicing mechanism can generate higher affinity neoepitopes for interaction with host HLA allomorphs. Understanding the nature and abundance of spliced peptides has a high relevance for our understanding of potential novel targets of T cell immunity and will have significant implications for further immunotherapeutic approaches.

Poster session 2Peptide identification methodology introduces bias in the detected repertoire of MHC presented peptides

Immunopeptidomic profiling with mass spectrometry has the capacity to directly identify peptide neo-antigens and provide a better understanding of the relationship between oncogenic processes, antigen presentation and immunity. Key to this is the use of search engines for the interpretation of mass spectra acquired after HLA peptide purification and LC-MS. In this study we present a comparison of three commonly used search engines across several immunopeptidomic datasets. We found that choice of search engine influences not only sensitivity but remarkably the repertoire of peptide sequences identified. Using NetMHC we validate our results showing that additional peptides identified are highly likely to be bound to a HLA protein. Based on this we investigate how search engine bias affects the outcome of an immunopeptidomic analyses given a background of different HLA alleles. We look in detail at this effect profiling several tumour samples with diverse HLA types.

Immunological Interaction of HLA-DPB1 and Proteinase 3 in ANCA Vasculitis is Associated with Clinical Disease Activity.

PR3-ANCA vasculitis has a genetic association with HLA-DPB1. We explored immunologic and clinical features related to the interaction of HLA-DPB1*04:01 with a strongly binding PR3 peptide epitope (PR3225-239). Patients with ANCA vasculitis with active disease and disease in remission were followed longitudinally. Peripheral blood mononuclear cells from patients and healthy controls with HLA-DPB1*04:01 were tested for HLA-DPB1*04:01 expression and interaction with a PR3 peptide identified via in silico and in vitro assays. Tetramers (HLA/peptide multimers) identified autoreactive T cells in vitro. RESULTS: The HLA-DPB1*04:01 genotype was associated with risk of relapse in PR3-ANCA (HR for relapse 2.06; 95% CI, 1.01 to 4.20) but not in myeloperoxidase (MPO)-ANCA or the combined cohort. In silico predictions of HLA and PR3 peptide interactions demonstrated strong affinity between ATRLFPDFFTRVALY (PR3225-239) and HLA-DPB1*04:01 that was confirmed by in vitro competitive binding studies. The interaction was tested in ex vivo flow cytometry studies of labeled peptide and HLA-DPB1*04:01-expressing cells. We demonstrated PR3225-239 specific autoreactive T cells using synthetic HLA multimers (tetramers). Patients in long-term remission off therapy had autoantigenic peptide and HLA interaction comparable to that of healthy volunteers. The risk allele HLA-DPB1*04:01 has been associated with PR3-ANCA, but its immunopathologic role was unclear. These studies demonstrate that HLA-DPB1*04:01 and PR3225-239 initiate an immune response. Autoreactive T cells specifically recognized PR3225-239 presented by HLA-DPB1*04:01. Although larger studies should validate these findings, the pathobiology may explain the observed increased risk of relapse in our cohort. Moreover, lack of HLA and autoantigen interaction observed during long-term remission signals immunologic nonresponsiveness.

Charge-based interactions through peptide position 4 drive diversity of antigen presentation by human leukocyte antigen class I molecules.

Human leukocyte antigen class I (HLA-I) molecules bind and present peptides at the cell surface to facilitate the induction of appropriate CD8+ T cell-mediated immune responses to pathogen- and self-derived proteins. The HLA-I peptide-binding cleft contains dominant anchor sites in the B and F pockets that interact primarily with amino acids at peptide position 2 and the C-terminus, respectively. Nonpocket peptide–HLA interactions also contribute to peptide binding and stability, but these secondary interactions are thought to be unique to individual HLA allotypes or to specific peptide antigens. Here, we show that two positively charged residues located near the top of peptide-binding cleft facilitate interactions with negatively charged residues at position 4 of presented peptides, which occur at elevated frequencies across most HLA-I allotypes. Loss of these interactions was shown to impair HLA-I/peptide binding and complex stability, as demonstrated by both in vitro and in silico experiments. Furthermore, mutation of these Arginine-65 (R65) and/or Lysine-66 (K66) residues in HLA-A*02:01 and A*24:02 significantly reduced HLA-I cell surface expression while also reducing the diversity of the presented peptide repertoire by up to 5-fold. The impact of the R65 mutation demonstrates that nonpocket HLA-I/peptide interactions can constitute anchor motifs that exert an unexpectedly broad influence on HLA-I-mediated antigen presentation. These findings provide fundamental insights into peptide antigen binding that could broadly inform epitope discovery in the context of viral vaccine development and cancer immunotherapy.

Abstract 1375: The intra-tumoral spatial heterogeneity of T-cell antigens in glioblastoma: An integrated multi-omics approach

Abstract Glioblastoma is the most common primary malignant neoplasm of the central nervous system in adults. Current treatment options comprise maximal surgical resection followed by radiation and/or chemotherapy with temozolomide. However, these procedures are unable to eliminate all tumor cells, which in turn lead to disease recurrence accounting for the poor prognosis. Glioblastoma is a highly infiltrative tumor in which recurrence originates from the unresectable peritumoral infiltration zone. Thus, novel treatment options specifically targeting the tumor cells in the infiltration zone are needed to prevent relapse and enable long-lasting remission. In this work, we performed multi-omics spatial analysis of the necrotic center (NEC), the gadolinium contrast-enhanced region (T1), and the infiltration zone (INF) to assess immunological relevant aspects of tumor heterogeneity. By integrating mass spectrometry-based immunopeptidome analysis with next generation sequencing methods (whole exome and RNA sequencing, DNA methylation), we aimed to identify the intra-tumoral regional heterogeneity of T cell antigens with a special focus on the peritumoral infiltration zone. For multi-omics analysis, HLA peptides and genetic material from 15 glioblastoma patients were extracted and analyzed from the three zones NEC, T1, INF and for four patients additionally from adjacent benign (BEN) brain tissue. A total of 24,699 unique HLA class I and 17,394 HLA class II peptides were identified. Comparative profiling of peptides from our study and a benign tissue database (in-house (n=429) combined with HLA ligand atlas (https://hla-ligand-atlas.org)) revealed that 6% (970/15,579), 5% (829/16,442) and 5% (725/13,891) of HLA class I peptides were exclusively presented in the INF, T1 and NEC zone, respectively. 6% (394/7,150), 7% (589/8,736) and 13% (1,725/12,908) of HLA class II peptides showed exclusive representation in the INF, T1 and NEC zone, respectively. Importantly, due to the spatial analysis of the immunopeptidome, we revealed 970 HLA class I and 394 HLA class II peptides exclusively presented in the INF zone. Interestingly, one INF-associated HLA class I peptide, which showed frequent presentation in 36% of glioblastoma immunopeptidomes, is derived from the brain and acute leukemia cytoplasmic protein (BAALC), a highly expressed cell cycle inducer (via MEK kinase-1) in several cancers, including glioblastoma. Integrated RNA/DNA sequencing enabled a greater understanding of spatial tumor antigen presentation and lead to the identification of INF-specific neoepitopes derived from tumor-specific mutations. In summary, we identified the intra-tumoral regional heterogeneity of tumor antigens, which could be used in the future for specific immunotherapy approaches targeting the infiltration zone of glioblastoma. Citation Format: Marcel Wacker, Gioele Medici, Marissa Dubbelaar, Jens Bauer, Annika Nelde, Luca Regli, Michael Weller, Helmut R. Salih, Hans-Georg Rammensee, Marian C. Neidert, Juliane S. Walz. The intra-tumoral spatial heterogeneity of T-cell antigens in glioblastoma: An integrated multi-omics approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1375.