Immunopeptidomic Analysis Reveals That Deamidated HLA-bound Peptides Arise Predominantly from Deglycosylated Precursors

Multiple Classes of Antigen Contribute to the Antigenic Landscape of Mesothelioma

Mesothelioma is an incurable, asbestos-exposure-related cancer that typically affects the lining or pleura of the lungs. Symptoms typically develop many decades after initial asbestos exposure, leaving an enduring legacy of disease. The current disease burden is peaking worldwide and thus there is a massive unmet clinical need for curative therapies. Recently, immune checkpoint blockade-based therapy has been adopted as a first-line of treatment for mesothelioma. Vaccine-induced augmentation of immune responses unleashed during checkpoint blockade may provide further clinical benefit in mesothelioma. In this study, we explore the human leukocyte antigen class I landscape (or immunopeptidome) of mesothelioma in patient-derived cell lines and clinical material (pleural effusion samples). We identify a range of peptide antigens derived from targets including cancer testis antigens, endogenous retroviruses as well as novel post-translational modification of peptides. This information will facilitate the characterization of the immune response to these antigens to determine which class of antigen is most immunogenic and has the potential to be tested in future vaccine studies.

Antigen presentation of post-translationally modified peptides in major histocompatibility complexes

T cells of the adaptive immune system recognize pathogens and malignantly transformed cells through a process called antigen presentation. During this process, peptides are displayed on major histocompatibility complex (MHC) class I and II molecules. Self-reactive T cells are typically removed or suppressed during T-cell development and through peripheral tolerance mechanisms, ensuring that only T cells recognizing peptides that are either absent or present in low abundance under normal conditions remain. This selective process allows T cells to respond to peptides derived from foreign proteins while ignoring those from self-proteins. However, T cells can also respond to peptides derived from proteins that have undergone post-translational modifications (PTMs). Over 200 different PTMs have been described, and while they are essential for protein function, localization and stability, their dysregulation is often associated with disease conditions. PTMs can affect the proteolytic processing of proteins and prevent MHC binding, thereby changing the repertoire of peptides presented on MHC molecules. However, it is also increasingly evident that many peptides presented on MHC molecules carry PTMs, which can alter their immunogenicity. As a result, the presentation of post-translationally modified peptides by MHC molecules plays a significant role in various diseases, as well as autoimmune disorders and allergies. This review will provide an overview of the impact of PTMs on antigen presentation and their implications for immune recognition and disease.

Protein sequence editing defines distinct and overlapping functions of SKN-1A/Nrf1 and SKN-1C/Nrf2

The Nrf/NFE2L family of transcription factors regulates redox balance, xenobiotic detoxification, metabolism, proteostasis, and aging. Nrf1/NFE2L1 is primarily responsible for stress-responsive upregulation of proteasome subunit genes and is essential for adaptation to proteotoxic stress. Nrf2/NFE2L2 is mainly involved in activating oxidative stress responses and promoting xenobiotic detoxification. Nrf1 and Nrf2 contain very similar DNA binding domains and can drive similar transcriptional responses. In C. elegans, a single gene, skn-1, encodes distinct protein isoforms, SKN-1A and SKN-1C, that function analogously to mammalian Nrf1 and Nrf2, respectively, and share an identical DNA binding domain. Thus, the extent to which SKN-1A/Nrf1 and SKN-1C/Nrf2 functions are distinct or overlapping has been unclear. Regulation of the proteasome by SKN-1A/Nrf1 requires post-translational conversion of N-glycosylated asparagine residues to aspartate by the PNG-1/NGLY1 peptide:N-glycanase, a process we term 'sequence editing'. Here, we reveal the consequences of sequence editing for the transcriptomic output of activated SKN-1A. We confirm that activation of proteasome subunit genes is strictly dependent on sequence editing. In addition, we find that sequence edited SKN-1A can also activate genes linked to redox homeostasis and xenobiotic detoxification that are also regulated by SKN-1C, but the extent of these genes' activation is antagonized by sequence editing. Using mutant alleles that selectively inactivate either SKN-1A or SKN-1C, we show that both isoforms promote optimal oxidative stress resistance, acting as effectors for distinct signaling pathways. These findings suggest that sequence editing governs SKN-1/Nrf functions by tuning the SKN-1A/Nrf1 regulated transcriptome.

Immunopeptidomics for autoimmunity: unlocking the chamber of immune secrets

T cells mediate pathogenesis of several autoimmune disorders by recognizing self-epitopes presented on Major Histocompatibility Complex (MHC) or Human Leukocyte Antigen (HLA) complex. The majority of autoantigens presented to T cells in various autoimmune disorders are not known, which has impeded autoantigen identification. Recent advances in immunopeptidomics have started to unravel the repertoire of antigenic epitopes presented on MHC. In several autoimmune diseases, immunopeptidomics has led to the identification of novel autoantigens and has enhanced our understanding of the mechanisms behind autoimmunity. Especially, immunopeptidomics has provided key evidence to explain the genetic risk posed by HLA alleles. In this review, we shed light on how immunopeptidomics can be leveraged to discover potential autoantigens. We highlight the application of immunopeptidomics in Type 1 Diabetes (T1D), Systemic Lupus Erythematosus (SLE), and Rheumatoid Arthritis (RA). Finally, we highlight the practical considerations of implementing immunopeptidomics successfully and the technical challenges that need to be addressed. Overall, this review will provide an important context for using immunopeptidomics for understanding autoimmunity.

HLAPepBinder: An Ensemble Model for The Prediction Of HLA-Peptide Binding

Background

Human leukocyte antigens (HLAs) play a pivotal role in orchestrating the host's immune response, offering a promising avenue with reduced adverse effects compared to conventional treatments. Cancer immunotherapies use HLA class I molecules for T cells to recognize tumor antigens, emphasizing the importance of identifying peptides that bind effectively to HLAs. Computer modeling of HLA-peptide binding speeds up the search for immunogenic epitopes, which enhances the prospect of personalized medicine and targeted therapies. The Immune Epitope Database (IEDB) is a vital repository, housing curated immune epitope data and prediction tools for HLA-peptide binding. It can be challenging for immunologists to choose the best tool from the IEDB for predicting HLA-peptide binding. This has led to the creation of consensus-based methods that combine the results of several predictors. One of the major challenges in these methods is how to effectively integrate the results from multiple predictors.

Objectives

Previous consensus-based methods integrate at most three tools by relying on simple strategies, such as selecting prediction methods based on their proximity to HLA in training data. In this study, we introduce HLAPepBinder, a novel consensus approach using ensemble machine learning methods to predict HLA-peptide binding, addressing the challenges biologists face in model selection.

Materials and Methods

The key contribution is the development of an automatic pipeline named HLAPepBinder that integrates the predictions of multiple models using a random forest approach. Unlike previous approaches, HLAPepBinder seamlessly integrates results from all nine predictors, providing a comprehensive and accurate predictive framework. By combining the strengths of these models, HLAPepBinder eliminates the need for manual model selection, providing a streamlined and reliable solution for biologists.

Results

HLAPepBinder offers a practical and high-performing alternative for HLA-peptide binding predictions, outperforming both traditional methods and complex deep learning models. Compared to the recently introduced transformer-based model, TranspHLA, which requires substantial computational resources, HLAPepBinder demonstrates superior performance in both prediction accuracy and resource efficiency. Notably, it operates effectively in limited computational environments, making it accessible to researchers with minimal resources. The codes are available online at https://github.com/CBRC-lab/HLAPepBinder.

Conclusion

Our study introduces a novel ensemble-learning model designed to enhance the accuracy and efficiency of HLA-peptide binding predictions. Due to the lack of reliable negative data and the typical assumption of unknown interactions being negative, we focus on analyzing the unknown HLA-peptide bindings in the test set that our model predicts with 100% certainty as positive bindings. Using HLAPepBinder, we identify 26 HLA-peptide pairs with absolute prediction confidence. These predictions are validated through a multi-step pipeline involving literature review, BLAST sequence similarity analysis, and molecular docking studies. This comprehensive validation process highlights HLAPepBinder's ability to make accurate and reliable predictions, contributing significantly to advancements in immunotherapy and vaccine development.

α-Mannosylated HLA-II glycopeptide antigens dominate the immunopeptidome of immortalised cells and tumour tissues

Immunopeptides are cell surface-located protein fragments that aid our immune system to recognise and respond to pathogenic insult and malignant transformation. In this two-part communication, we firstly summarise and reflect on our recent discovery documenting that MHC-II-bound immunopeptides from immortalised cell lines prevalently carry N-glycans that differ from the cellular glycoproteome (Goodson, Front Immunol, 2023). These findings are important as immunopeptide glycosylation remains poorly understood in immunosurveillance. The study also opened up new technical and biological questions that we address in the second part of this communication. Our study highlighted that the performance of the search engines used to detect glycosylated immunopeptides from LC-MS/MS data remains untested and, importantly, that little biochemical in vivo evidence is available to document the nature of glycopeptide antigens in tumour tissues. To this end, we compared the N-glycosylated MHC-II-bound immunopeptides that were reported from tumour tissues of 14 meningioma patients in the MSFragger-HLA-Glyco database (Bedran, Nat Commun, 2023) to those we identified with the commercial Byonic software. Encouragingly, the search engines produced similar outputs supporting that N-glycosylated MHC-II-bound immunopeptides are prevalent in meningioma tumour tissues. Consistent also with in vitro findings, the tissue-derived MHC-II-bound immunopeptides were found to predominantly carry hyper-processed (paucimannosidic- and chitobiose core-type) and hypo-processed (oligomannosidic-type) N-glycans that varied in prevalence and distribution between patients. Taken together, evidence is emerging suggesting that α-mannosidic glycoepitopes abundantly decorate MHC-II-bound immunopeptides presented in both immortalised cells and tumour tissues warranting further research into their functional roles in immunosurveillance.

Mapping the immunopeptidome of seven SARS-CoV-2 antigens across common HLA haplotypes

Most COVID-19 vaccines elicit immunity against the SARS-CoV-2 Spike protein. However, Spike protein mutations in emerging strains and immune evasion by the SARS-CoV-2 virus demonstrates the need to develop more broadly targeting vaccines. To facilitate this, we use mass spectrometry to identify immunopeptides derived from seven relatively conserved structural and non-structural SARS-CoV-2 proteins (N, E, Nsp1/4/5/8/9). We use two different B-lymphoblastoid cell lines to map Human Leukocyte Antigen (HLA) class I and class II immunopeptidomes covering some of the prevalent HLA types across the global human population. We employ DNA plasmid transfection and direct antigen delivery approaches to sample different antigens and find 248 unique HLA class I and HLA class II bound peptides with 71 derived from N, 12 from E, 28 from Nsp1, 19 from Nsp4, 73 from Nsp8 and 45 peptides derived from Nsp9. Over half of the viral peptides are unpublished. T cell reactivity tested against 56 of the detected peptides shows CD8+ and CD4+ T cell responses against several peptides from the N, E, and Nsp9 proteins. Results from this study will aid the development of next-generation COVID vaccines targeting epitopes from across a number of SARS-CoV-2 proteins.

Exploring the dynamic landscape of immunopeptidomics: Unravelling posttranslational modifications and navigating bioinformatics terrain

Immunopeptidomics is becoming an increasingly important field of study. The capability to identify immunopeptides with pivotal roles in the human immune system is essential to shift the current curative medicine towards personalized medicine. Throughout the years, the field has matured, giving insight into the current pitfalls. Nowadays, it is commonly accepted that generalizing shotgun proteomics workflows is malpractice because immunopeptidomics faces numerous challenges. While many of these difficulties have been addressed, the road towards the ideal workflow remains complicated. Although the presence of Posttranslational modifications (PTMs) in the immunopeptidome has been demonstrated, their identification remains highly challenging despite their significance for immunotherapies. The large number of unpredictable modifications in the immunopeptidome plays a pivotal role in the functionality and these challenges. This review provides a comprehensive overview of the current advancements in immunopeptidomics. We delve into the challenges associated with identifying PTMs within the immunopeptidome, aiming to address the current state of the field.

Immunopeptidomics in the cancer immunotherapy era

Cancer is the primary cause of death worldwide, and conventional treatments are painful, complicated, and have negative effects on healthy cells. However, cancer immunotherapy has emerged as a promising alternative. Principle of cancer immunotherapy is the re-activation of T-cell to combat the tumor that presents the peptide antigen on major histocompatibility complex (MHC). Those peptide antigens are identified with the set of omics technology, proteomics, genomics, and bioinformatics, which referred to immunopeptidomics. Indeed, immunopeptidomics can identify the neoantigens that are very useful for cancer immunotherapies. This review explored the use of immunopeptidomics for various immunotherapies, i.e., peptide-based vaccines, immune checkpoint inhibitors, oncolytic viruses, and chimeric antigen receptor T-cell. We also discussed how the diversity of neoantigens allows for the discovery of novel antigenic peptides while post-translationally modified peptides diversify the overall peptides binding to MHC or so-called MHC ligandome. The development of immunopeptidomics is keeping up-to-date and very active, particularly for clinical application. Immunopeptidomics is expected to be fast, accurate and reliable for the application for cancer immunotherapies.

HLA-DQB1*05 subtypes and not DRB1*10:01 mediates risk in anti-IgLON5 disease

Anti-IgLON5 disease is a rare and likely underdiagnosed subtype of autoimmune encephalitis. The disease displays a heterogeneous phenotype that includes sleep, movement and bulbar-associated dysfunction. The presence of IgLON5-antibodies in CSF/serum, together with a strong association with HLA-DRB1*10:01∼DQB1*05:01, supports an autoimmune basis. In this study, a multicentric human leukocyte antigen (HLA) study of 87 anti-IgLON5 patients revealed a stronger association with HLA-DQ than HLA-DR. Specifically, we identified a predisposing rank-wise association with HLA-DQA1*01:05∼DQB1*05:01, HLA-DQA1*01:01∼DQB1*05:01 and HLA-DQA1*01:04∼DQB1*05:03 in 85% of patients. HLA sequences and binding cores for these three DQ heterodimers were similar, unlike those of linked DRB1 alleles, supporting a causal link to HLA-DQ. This association was further reflected in an increasingly later age of onset across each genotype group, with a delay of up to 11 years, while HLA-DQ-dosage dependent effects were also suggested by reduced risk in the presence of non-predisposing DQ1 alleles. The functional relevance of the observed HLA-DQ molecules was studied with competition binding assays. These proof-of-concept experiments revealed preferential binding of IgLON5 in a post-translationally modified, but not native, state to all three risk-associated HLA-DQ receptors. Further, a deamidated peptide from the Ig2-domain of IgLON5 activated T cells in two patients, compared with one control carrying HLA-DQA1*01:05∼DQB1*05:01. Taken together, these data support a HLA-DQ-mediated T-cell response to IgLON5 as a potentially key step in the initiation of autoimmunity in this disease.

Profound N-glycan remodelling accompanies MHC-II immunopeptide presentation

Immunopeptidomics, the study of peptide antigens presented on the cell surface by the major histocompatibility complex (MHC), offers insights into how our immune system recognises self/non-self in health and disease. We recently discovered that hyper-processed (remodelled) N-glycans are dominant features decorating viral spike immunopeptides presented via MHC-class II (MHC-II) molecules by dendritic cells pulsed with SARS-CoV-2 spike protein, but it remains unknown if endogenous immunopeptides also undergo N-glycan remodelling. Taking a multi-omics approach, we here interrogate published MHC-II immunopeptidomics datasets of cultured monocyte-like (THP-1) and breast cancer-derived (MDA-MB-231) cell lines for overlooked N-glycosylated peptide antigens, which we compare to their source proteins in the cellular glycoproteome using proteomics and N-glycomics data from matching cell lines. Hyper-processed chitobiose core and paucimannosidic N-glycans alongside under-processed oligomannosidic N-glycans were found to prevalently modify MHC-II-bound immunopeptides isolated from both THP-1 and MDA-MB-231, while complex/hybrid-type N-glycans were (near-)absent in the immunopeptidome as supported further by new N-glycomics data generated from isolated MHC-II-bound peptides derived from MDA-MB-231 cells. Contrastingly, the cellular proteomics and N-glycomics data from both cell lines revealed conventional N-glycosylation rich in complex/hybrid-type N-glycans, which, together with the identification of key lysosomal glycosidases, suggest that MHC-II peptide antigen processing is accompanied by extensive N-glycan trimming. N-glycan remodelling appeared particularly dramatic for cell surface-located glycoproteins while less remodelling was observed for lysosomal-resident glycoproteins. Collectively, our findings indicate that both under- and hyper-processed N-glycans are prevalent features of endogenous MHC-II immunopeptides, an observation that demands further investigation to enable a better molecular-level understanding of immune surveillance.

Unraveling the glycosylated immunopeptidome with HLA-Glyco

Recent interest in targeted therapies has been sparked by the study of MHC-associated peptides (MAPs) that undergo post-translational modifications (PTMs), particularly glycosylation. In this study, we introduce a fast computational workflow that merges the MSFragger-Glyco search algorithm with a false discovery rate control for glycopeptide analysis from mass spectrometry-based immunopeptidome data. By analyzing eight large-scale publicly available studies, we find that glycosylated MAPs are predominantly presented by MHC class II. Here, we present HLA-Glyco, a comprehensive resource containing over 3,400 human leukocyte antigen (HLA) class II N-glycopeptides from 1,049 distinct protein glycosylation sites. This resource provides valuable insights, including high levels of truncated glycans, conserved HLA-binding cores, and differences in glycosylation positional specificity between HLA allele groups. We integrate the workflow within the FragPipe computational platform and provide HLA-Glyco as a free web resource. Overall, our work provides a valuable tool and resource to aid the nascent field of glyco-immunopeptidomics.

The biogenesis of the immunopeptidome

The immunopeptidome is the repertoire of peptides bound and presented by the MHC class I, class II, and non-classical molecules. The peptides are produced by the degradation of most cellular proteins, and in some cases, peptides are produced from extracellular proteins taken up by the cells. This review attempts to first describe some of its known and well-accepted concepts, and next, raise some questions about a few of the established dogmas in this field: The production of novel peptides by splicing is questioned, suggesting here that spliced peptides are extremely rare, if existent at all. The degree of the contribution to the immunopeptidome by degradation of cellular protein by the proteasome is doubted, therefore this review attempts to explain why it is likely that this contribution to the immunopeptidome is possibly overstated. The contribution of defective ribosome products (DRiPs) and non-canonical peptides to the immunopeptidome is noted and methods are suggested to quantify them. In addition, the common misconception that the MHC class II peptidome is mostly derived from extracellular proteins is noted, and corrected. It is stressed that the confirmation of sequence assignments of non-canonical and spliced peptides should rely on targeted mass spectrometry using spiking-in of heavy isotope-labeled peptides. Finally, the new methodologies and modern instrumentation currently available for high throughput kinetics and quantitative immunopeptidomics are described. These advanced methods open up new possibilities for utilizing the big data generated and taking a fresh look at the established dogmas and reevaluating them critically.

Challenges and opportunities in analyzing and modeling peptide presentation by HLA-II proteins

The human leukocyte antigen (HLA) proteins are an indispensable component of adaptive immunity because of their role in presenting self and foreign peptides to T cells. Further, many complex diseases are associated with genetic variation in the HLA region, implying an important role for specific HLA-presented peptides in the etiology of these diseases. Identifying the specific set of peptides presented by an individual’s HLA proteins in vivo, as a whole being referred to as the immunopeptidome, has therefore gathered increasing attention for different reasons. For example, identifying neoepitopes for cancer immunotherapy, vaccine development against infectious pathogens, or elucidating the role of HLA in autoimmunity. Despite the tremendous progress made during the last decade in these areas, several questions remain unanswered. In this perspective, we highlight five remaining key challenges in the analysis of peptide presentation and T cell immunogenicity and discuss potential solutions to these problems. We believe that addressing these questions would not only improve our understanding of disease etiology but will also have a direct translational impact in terms of engineering better vaccines and in developing more potent immunotherapies.

Contemplating immunopeptidomes to better predict them

The identification of T-cell epitopes is key for a complete molecular understanding of immune recognition mechanisms in infectious diseases, autoimmunity and cancer. T-cell epitopes further provide targets for personalized vaccines and T-cell therapy, with several therapeutic applications in cancer immunotherapy and elsewhere. T-cell epitopes consist of short peptides displayed on Major Histocompatibility Complex (MHC) molecules. The recent advances in mass spectrometry (MS) based technologies to profile the ensemble of peptides displayed on MHC molecules - the so-called immunopeptidome - had a major impact on our understanding of antigen presentation and MHC ligands. On the one hand, these techniques enabled researchers to directly identify hundreds of thousands of peptides presented on MHC molecules, including some that elicited T-cell recognition. On the other hand, the data collected in these experiments revealed fundamental properties of antigen presentation pathways and significantly improved our ability to predict naturally presented MHC ligands and T-cell epitopes across the wide spectrum of MHC alleles found in human and other organisms. Here we review recent computational developments to analyze experimentally determined immunopeptidomes and harness these data to improve our understanding of antigen presentation and MHC binding specificities, as well as our ability to predict MHC ligands. We further discuss the strengths and limitations of the latest approaches to move beyond predictions of antigen presentation and tackle the challenges of predicting TCR recognition and immunogenicity.

Post-translational modifications reshape the antigenic landscape of the MHC I immunopeptidome in tumors

Post-translational modification (PTM) of antigens provides an additional source of specificities targeted by immune responses to tumors or pathogens, but identifying antigen PTMs and assessing their role in shaping the immunopeptidome is challenging. Here we describe the Protein Modification Integrated Search Engine (PROMISE), an antigen discovery pipeline that enables the analysis of 29 different PTM combinations from multiple clinical cohorts and cell lines. We expanded the antigen landscape, uncovering human leukocyte antigen class I binding motifs defined by specific PTMs with haplotype-specific binding preferences and revealing disease-specific modified targets, including thousands of new cancer-specific antigens that can be shared between patients and across cancer types. Furthermore, we uncovered a subset of modified peptides that are specific to cancer tissue and driven by post-translational changes that occurred in the tumor proteome. Our findings highlight principles of PTM-driven antigenicity, which may have broad implications for T cell-mediated therapies in cancer and beyond.

Regulation and Functions of the ER-Associated Nrf1 Transcription Factor

Nrf1 is a member of the nuclear erythroid 2-like family of transcription factors that regulate stress-responsive gene expression in animals. Newly synthesized Nrf1 is targeted to the endoplasmic reticulum (ER) where it is N-glycosylated. N-glycosylated Nrf1 is trafficked to the cytosol by the ER-associated degradation (ERAD) machinery and is subject to rapid proteasomal degradation. When proteasome function is impaired, Nrf1 escapes degradation and undergoes proteolytic cleavage and deglycosylation. Deglycosylation results in deamidation of N-glycosylated asparagine residues to edit the protein sequence encoded by the genome. This truncated and "sequence-edited" form of Nrf1 enters the nucleus where it induces up-regulation of proteasome subunit genes. Thus, Nrf1 drives compensatory proteasome biogenesis in cells exposed to proteasome inhibitor drugs and other proteotoxic insults. In addition to its role in proteasome homeostasis, Nrf1 is implicated in responses to oxidative stress, and maintaining lipid and cholesterol homeostasis. Here, we describe the conserved and complex mechanism by which Nrf1 is regulated and highlight emerging evidence linking this unusual transcription factor to development, aging, and disease.

Soluble HLA peptidome: A new resource for cancer biomarkers

Using circulating molecular biomarkers to screen for cancer and other debilitating disorders in a high-throughput and low-cost fashion is becoming increasingly attractive in medicine. One major limitation of investigating protein biomarkers in body fluids is that only one-fourth of the entire proteome can be routinely detected in these fluids. In contrast, Human Leukocyte Antigen (HLA) presents peptides from the entire proteome on the cell surface. While peptide-HLA complexes are predominantly membrane-bound, a fraction of HLA molecules is released into body fluids which is referred to as soluble HLAs (sHLAs). As such peptides bound by sHLA molecules represent the entire proteome of their cells/tissues of origin and more importantly, recent advances in mass spectrometry-based technologies have allowed for accurate determination of these peptides. In this perspective, we discuss the current understanding of sHLA-peptide complexes in the context of cancer, and their potential as a novel, relatively untapped repertoire for cancer biomarkers. We also review the currently available tools to detect and quantify these circulating biomarkers, and we discuss the challenges and future perspectives of implementing sHLA biomarkers in a clinical setting.

Mining the Immunopeptidome for Antigenic Peptides in Cancer

Although harnessing the immune system for cancer therapy has shown success, response to immunotherapy has been limited. The immunopeptidome of cancer cells presents an opportunity to discover novel antigens for immunotherapy applications. These neoantigens bind to MHC class I and class II molecules. Remarkably, the immunopeptidome encompasses protein post-translation modifications (PTMs) that may not be evident from genome or transcriptome profiling. A case in point is citrullination, which has been demonstrated to induce a strong immune response. In this review, we cover how the immunopeptidome, with a special focus on PTMs, can be utilized to identify cancer-specific antigens for immunotherapeutic applications.

Structural aspects of chemical modifications in the MHC-restricted immunopeptidome; Implications for immune recognition

Significant advances in mass-spectroscopy (MS) have made it possible to investigate the cellular immunopeptidome, a large collection of MHC-associated epitopes presented on the surface of healthy, stressed and infected cells. These approaches have hitherto allowed the unambiguous identification of large cohorts of epitope sequences that are restricted to specific MHC class I and II molecules, enhancing our understanding of the quantities, qualities and origins of these peptide populations. Most importantly these analyses provide essential information about the immunopeptidome in responses to pathogens, autoimmunity and cancer, and will hopefully allow for future tailored individual therapies. Protein post-translational modifications (PTM) play a key role in cellular functions, and are essential for both maintaining cellular homeostasis and increasing the diversity of the proteome. A significant proportion of proteins is post-translationally modified, and thus a deeper understanding of the importance of PTM epitopes in immunopeptidomes is essential for a thorough and stringent understanding of these peptide populations. The aim of the present review is to provide a structural insight into the impact of PTM peptides on stability of MHC/peptide complexes, and how these may alter/modulate immune responses.

Proteogenomic Analysis Unveils the HLA Class I-Presented Immunopeptidome in Melanoma and EGFR-Mutant Lung Adenocarcinoma

Immune checkpoint inhibitors and adoptive lymphocyte transfer–based therapies have shown great therapeutic potential in cancers with high tumor mutational burden (TMB), such as melanoma, but not in cancers with low TMB, such as mutant epidermal growth factor receptor (EGFR)–driven lung adenocarcinoma. Precision immunotherapy is an unmet need for most cancers, particularly for cancers that respond inadequately to immune checkpoint inhibitors. Here, we employed large-scale MS-based proteogenomic profiling to identify potential immunogenic human leukocyte antigen (HLA) class I-presented peptides in melanoma and EGFR-mutant lung adenocarcinoma. Similar numbers of peptides were identified from both tumor types. Cell line and patient-specific databases (DBs) were constructed using variants identified from whole-exome sequencing. A de novo search algorithm was used to interrogate the HLA class I immunopeptidome MS data. We identified 12 variant peptides and several classes of tumor-associated antigen-derived peptides. We constructed a cancer germ line (CG) antigen DB with 285 antigens. This allowed us to identify 40 class I-presented CG antigen–derived peptides. The class I immunopeptidome comprised more than 1000 post-translationally modified (PTM) peptides representing 58 different PTMs, underscoring the critical role PTMs may play in HLA binding. Finally, leveraging de novo search algorithm and an annotated long noncoding RNA (lncRNA) DB, we developed a novel lncRNA-encoded peptide discovery pipeline to identify 44 lncRNA-derived peptides that are presented by class I. We validated tandem MS spectra of select variant, CG antigen, and lncRNA-derived peptides using synthetic peptides and performed HLA class I-binding assays to demonstrate binding to class I proteins. In summary, we provide direct evidence of HLA class I presentation of a large number of variant and tumor-associated peptides in both low and high TMB cancer. These results can potentially be useful for precision immunotherapies, such as vaccine or adoptive cell therapies in melanoma and EGFR-mutant lung cancers.

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Proteogenomics identified ∼35,000 class I-presented peptides.

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CG antigen and PTM peptides identified in melanoma and lung cancer.

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De novo search identified variant and lncRNA-derived peptides.

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A new strategy to identify class I-presented lncRNA-derived peptides developed.

Cloud Computing Based Immunopeptidomics Utilizing Community Curated Variant Libraries Simplifies and Improves Neo-Antigen Discovery in Metastatic Melanoma

Unique peptide neo-antigens presented on the cell surface are attractive targets for researchers in nearly all areas of personalized medicine. Cells presenting peptides with mutated or other non-canonical sequences can be utilized for both targeted therapies and diagnostics. Today's state-of-the-art pipelines utilize complementary proteogenomic approaches where RNA or ribosomal sequencing data helps to create libraries from which tandem mass spectrometry data can be compared. In this study, we present an alternative approach whereby cloud computing is utilized to power neo-antigen searches against community curated databases containing more than 7 million human sequence variants. Using these expansive databases of high-quality sequences as a reference, we reanalyze the original data from two previously reported studies to identify neo-antigen targets in metastatic melanoma. Using our approach, we identify 79 percent of the non-canonical peptides reported by previous genomic analyses of these files. Furthermore, we report 18-fold more non-canonical peptides than previously reported. The novel neo-antigens we report herein can be corroborated by secondary analyses such as high predicted binding affinity, when analyzed by well-established tools such as NetMHC. Finally, we report 738 non-canonical peptides shared by at least five patient samples, and 3258 shared across the two studies. This illustrates the depth of data that is present, but typically missed by lower statistical power proteogenomic approaches. This large list of shared peptides across the two studies, their annotation, non-canonical origin, as well as MS/MS spectra from the two studies are made available on a web portal for community analysis.

HLA-B and cysteinylated ligands distinguish the antigen presentation landscape of extracellular vesicles

Extracellular vesicles can modulate diverse processes ranging from proliferation and tissue repair, to chemo-resistance and cellular differentiation. With the advent of tissue and immunological targeting, extracellular vesicles are also increasingly viewed as promising vectors to deliver peptide-based cancer antigens to the human immune system. Despite the clinical relevance and therapeutic potential of such 'cell-free' approaches, the natural antigen presentation landscape exported in extracellular vesicles is still largely uncharted, due to the challenging nature of such preparations and analyses. In the context of therapeutic vesicle production, a critical evaluation of the similarity in vesicular antigen presentation is also urgently needed. In this work, we compared the HLA-I peptide ligandomes of extracellular vesicles against that of whole-cells of the same cell line. We found that extracellular vesicles not only over-represent HLA-B complexes and peptide ligands, but also cysteinylated peptides that may modulate immune responses. Collectively, these findings describe the pre-existing provision of vesicular HLA complexes that may be utilized to carry peptide vaccines, as well as the propensity for different peptide and post-translationally modified ligands to be presented, and will outline critical considerations in devising novel EV vaccination strategies.

Genetic Analysis Reveals Differences in CD8+ T Cell Epitope Regions That May Impact Cross-Reactivity of Vaccine-Induced T Cells against Wild-Type Mumps Viruses

Nowadays, mumps is re-emerging in highly vaccinated populations. Waning of vaccine-induced immunity plays a role, but antigenic differences between vaccine and mumps outbreak strains could also contribute to reduced vaccine effectiveness. CD8⁺ T cells play a critical role in immunity to viruses. However, limited data are available about sequence variability in CD8⁺ T cell epitope regions of mumps virus (MuV) proteins. Recently, the first set of naturally presented human leukocyte antigen Class I (HLA-I) epitopes of MuV was identified by us. In the present study, sequences of 40 CD8⁺ T cell epitope candidates, including previously and newly identified, obtained from Jeryl–Lynn mumps vaccine strains were compared with genomes from 462 circulating MuV strains. In 31 epitope candidates (78%) amino acid differences were detected, and in 17 (43%) of the epitope candidates the corresponding sequences in wild-type strains had reduced predicted HLA-I-binding compared to the vaccine strains. These findings suggest that vaccinated persons may have reduced T cell immunity to circulating mumps viruses due to antigenic differences.

SARS-CoV-2-specific CD8+ T-cell responses and TCR signatures in the context of a prominent HLA-A*24:02 allomorph

In‐depth understanding of human T‐cell‐mediated immunity in coronavirus disease 2019 (COVID‐19) is needed if we are to optimize vaccine strategies and immunotherapies. Identification of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) T‐cell epitopes and generation of peptide–human leukocyte antigen (peptide–HLA) tetramers facilitate direct ex vivo analyses of SARS‐CoV‐2‐specific T cells and their T‐cell receptor (TCR) repertoires. We utilized a combination of peptide prediction and in vitro peptide stimulation to validate novel SARS‐CoV‐2 epitopes restricted by HLA‐A*24:02, one of the most prominent HLA class I alleles, especially in Indigenous and Asian populations. Of the peptides screened, three spike‐derived peptides generated CD8⁺IFNγ⁺ responses above background, S_1208–1216 (QYIKWPWYI), S_448–456 (NYNYLYRLF) and S_193–201 (VFKNIDGYF), with S₁₂₀₈ generating immunodominant CD8⁺IFNγ⁺ responses. Using peptide–HLA‐I tetramers, we performed direct ex vivo tetramer enrichment for HLA‐A*24:02‐restricted CD8⁺ T cells in COVID‐19 patients and prepandemic controls. The precursor frequencies for HLA‐A*24:02‐restricted epitopes were within the range previously observed for other SARS‐CoV‐2 epitopes for both COVID‐19 patients and prepandemic individuals. Naïve A24/SARS‐CoV‐2‐specific CD8⁺ T cells increased nearly 7.5‐fold above the average precursor frequency during COVID‐19, gaining effector and memory phenotypes. Ex vivo single‐cell analyses of TCRαβ repertoires found that the A24/S₄₄₈⁺CD8⁺ T‐cell TCRαβ repertoire was driven by a common TCRβ chain motif, whereas the A24/S₁₂₀₈⁺CD8⁺ TCRαβ repertoire was diverse across COVID‐19 patients. Our study provides an in depth characterization and important insights into SARS‐CoV‐2‐specific CD8⁺ T‐cell responses associated with a prominent HLA‐A*24:02 allomorph. This contributes to our knowledge on adaptive immune responses during primary COVID‐19 and could be exploited in vaccine or immunotherapeutic approaches.

CD8+ T cell landscape in Indigenous and non-Indigenous people restricted by influenza mortality-associated HLA-A*24:02 allomorph

Indigenous people worldwide are at high risk of developing severe influenza disease. HLA-A*24:02 allele, highly prevalent in Indigenous populations, is associated with influenza-induced mortality, although the basis for this association is unclear. Here, we define CD8⁺ T-cell immune landscapes against influenza A (IAV) and B (IBV) viruses in HLA-A*24:02-expressing Indigenous and non-Indigenous individuals, human tissues, influenza-infected patients and HLA-A*24:02-transgenic mice. We identify immunodominant protective CD8⁺ T-cell epitopes, one towards IAV and six towards IBV, with A24/PB2_550-558-specific CD8⁺ T cells being cross-reactive between IAV and IBV. Memory CD8⁺ T cells towards these specificities are present in blood (CD27⁺CD45RA^- phenotype) and tissues (CD103⁺CD69⁺ phenotype) of healthy individuals, and effector CD27^-CD45RA^-PD-1⁺CD38⁺CD8⁺ T cells in IAV/IBV patients. Our data show influenza-specific CD8⁺ T-cell responses in Indigenous Australians, and advocate for T-cell-mediated vaccines that target and boost the breadth of IAV/IBV-specific CD8⁺ T cells to protect high-risk HLA-A*24:02-expressing Indigenous and non-Indigenous populations from severe influenza disease.

Does Antigen Glycosylation Impact the HIV-Specific T Cell Immunity?

It is largely unknown how post-translational protein modifications, including glycosylation, impacts recognition of self and non-self T cell epitopes presented by HLA molecules. Data in the literature indicate that O- and N-linked glycosylation can survive epitope processing and influence antigen presentation and T cell recognition. In this perspective, we hypothesize that glycosylation of viral proteins and processed epitopes contribute to the T cell response to HIV. Although there is some evidence for T cell responses to glycosylated epitopes (glyco-epitopes) during viral infections in the literature, this aspect has been largely neglected for HIV. To explore the role of glyco-epitope specific T cell responses in HIV infection we conducted in silico and ex vivo immune studies in individuals with chronic HIV infection. We found that in silico viral protein segments with potentially glycosylable epitopes were less frequently targeted by T cells. Ex vivo synthetically added glycosylation moieties generally masked T cell recognition of HIV derived peptides. Nonetheless, in some cases, addition of simple glycosylation moieties produced neo-epitopes that were recognized by T cells from HIV infected individuals. Herein, we discuss the potential importance of these observations and compare limitations of the employed technology with new methodologies that may have the potential to provide a more accurate assessment of glyco-epitope specific T cell immunity. Overall, this perspective is aimed to support future research on T cells recognizing glycosylated epitopes in order to expand our understanding on how glycosylation of viral proteins could alter host T cell immunity against viral infections.

Anthem: a user customised tool for fast and accurate prediction of binding between peptides and HLA class I molecules

Neopeptide-based immunotherapy has been recognised as a promising approach for the treatment of cancers. For neopeptides to be recognised by CD8+ T cells and induce an immune response, their binding to human leukocyte antigen class I (HLA-I) molecules is a necessary first step. Most epitope prediction tools thus rely on the prediction of such binding. With the use of mass spectrometry, the scale of naturally presented HLA ligands that could be used to develop such predictors has been expanded. However, there are rarely efforts that focus on the integration of these experimental data with computational algorithms to efficiently develop up-to-date predictors. Here, we present Anthem for accurate HLA-I binding prediction. In particular, we have developed a user-friendly framework to support the development of customisable HLA-I binding prediction models to meet challenges associated with the rapidly increasing availability of large amounts of immunopeptidomic data. Our extensive evaluation, using both independent and experimental datasets shows that Anthem achieves an overall similar or higher area under curve value compared with other contemporary tools. It is anticipated that Anthem will provide a unique opportunity for the non-expert user to analyse and interpret their own in-house or publicly deposited datasets.

Digging deeper into the immunopeptidome: characterization of post-translationally modified peptides presented by MHC I

Peptides presented by MHC molecules on the cell surface, or the immunopeptidome, play an important role in the adaptive arm of the immune response. Antigen processing for MHC class I molecules is a ubiquitous pathway present in all nucleated cells which generates and presents peptides of both self and non-self-origin. Peptides with post-translational modifications represent one category of peptides presented by MHC class I molecules. However, owing to the complexity of self-peptides presented by cells, the diversity of peptides with post-translational modifications is not well-studied. In this study, we carried out MHC Class I immunopeptidomics analysis of Loucy T-cell leukemia and A375 malignant melanoma cell line to characterize the diversity of post-translational modifications of MHC class I-bound peptides. Using high resolution mass spectrometry, we identified 25,761 MHC-bound peptides across both cell lines using Bolt and Sequest search engines. The enrichment method was highly specific as ~ 90% of the peptides were of typical length (8-12 amino acids long) and the motifs were expected based on previously reported motifs for MHC I alleles. Among the MHC-bound peptides, we identified phosphorylation as a major post-translational modification followed by deamidation. We observed site-specific localization of these post-translational modifications, at position P4 for phosphorylated peptides and position P3 for deamidated peptides. We identified a smaller number of peptides with acetylated and methylated lysine, possibly due to very low stoichiometric levels of these PTMs compared to phosphorylation and deamidation. Using PEAKS de novo sequencing algorithm, we identified spliced peptides that accounted for ~ 5-7% of MHC-bound peptides that were otherwise similar in their features as normal MHC-bound peptides. We validated the identity of several post-translationally modified peptides and spliced peptides through mass spectrometric analysis of synthetic peptides. Our study confirms post-translationally modified peptides to be present at low stoichiometric levels along with unusual spliced peptides through unbiased identification using high resolution mass spectrometry.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42485-021-00066-x.