Mass spectrometry-based identification of MHC-bound peptides for immunopeptidomics

Vaccines for immunoprevention of cancer

The immunoprevention of cancer and cancer recurrence is an important area of concern for the scientific community and society as a whole. Researchers have been working for decades to develop vaccines with the potential to alleviate these health care and economic burdens. So far, vaccines have made more progress in preventing cancer than in eliminating already established cancer. In particular, vaccines targeting oncogenic viruses, such as the human papillomavirus and the hepatitis B virus, are exceptional examples of successful prevention of virus-associated cancers, such as cervical cancer and hepatocellular carcinoma. Cancer-preventive vaccines targeting nonviral antigens, such as tumor-associated antigens and neoantigens, are also being extensively tested. Here, we review the currently approved preventive cancer vaccines; discuss the challenges in this field by covering ongoing preclinical and clinical human trials in various cancers; and address various issues related to maximizing cancer vaccine benefit.

Spliced HLA-bound peptides: a Black Swan event in immunology

Peptides that bind to and are presented on the cell surface by human leucocyte antigen (HLA) molecules play a critical role in adaptive immunity. For a long time it was believed that all the HLA-bound peptides were generated through simple proteolysis of linear sequences of cellular proteins, and therefore are templated in the genome and proteome. However, evidence for untemplated peptide ligands of HLA molecules has accumulated during the last two decades, with a recent global analysis of HLA-bound peptides suggesting that a considerable proportion of HLA-bound peptides are potentially generated through splicing/fusion of discontinuous peptide segments from one or two distinct proteins. In this review, we will evaluate recent discoveries and debates on the contribution of spliced peptides to the HLA class I immunopeptidome, consider biochemical rules for splicing and the potential role of these spliced peptides in immune recognition.

Targeting public neoantigens for cancer immunotherapy

Several current immunotherapy approaches target private neoantigens derived from mutations that are unique to individual patients' tumors. However, immunotherapeutic agents can also be developed against public neoantigens derived from recurrent mutations in cancer driver genes. The latter approaches target proteins that are indispensable for tumor growth, and each therapeutic agent can be applied to numerous patients. Here we review the opportunities and challenges involved in the identification of suitable public neoantigen targets and the development of therapeutic agents targeting them.

Direct Priming of CD8+ T Cells Persists in the Face of Cowpox Virus Inhibitors of Antigen Presentation

Vaccinia virus (VACV) was the vaccine used to eradicate smallpox and is being repurposed as a vaccine vector. CD8+ T cells are key anti-viral mediators, but require priming to become effector or memory cells. Priming requires an interaction with dendritic cells that are either infected (direct priming), or that have acquired virus proteins but remain uninfected (cross priming). To investigate CD8+ T cell priming pathways for VACV, we engineered the virus to express CPXV12 and CPXV203, two inhibitors of antigen presentation encoded by cowpox virus. These intracellular proteins would be expected to block direct but not cross priming. The inhibitors had diverse impacts on the size of anti-VACV CD8+ T cell responses across epitopes and by different infection routes in mice, superficially suggesting variable use of direct and cross priming. However, when we then tested a form of antigen that requires direct priming, we found surprisingly that CD8+ T cell responses were not diminished by co-expression with CPXV12 and CPXV203. We then directly quantified the impact of CPXV12 and CPXV203 on viral antigen presentation using mass spectrometry, which revealed strong, but incomplete inhibition of antigen presentation by the CPXV proteins. Therefore, direct priming of CD8+ T cells by poxviruses is robust enough to withstand highly potent viral inhibitors of antigen presentation. This is a reminder of the limits of viral immune evasion and shows that viral inhibitors of antigen presentation cannot be assumed to dissect cleanly direct and cross priming of anti-viral CD8+ T cells.ImportanceCD8+ T cells are key to anti-viral immunity, so it is important to understand how they are activated. Many viruses have proteins that protect infected cells from T cell attack by interfering with the process that allows virus infection to be recognised by CD8+ T cells. It is thought that these proteins would also stop infected cells from activating T cells in the first place. However, we show here that this is not the case for two very powerful inhibitory proteins from cowpox virus. This demonstrates the flexibility and robustness of immune processes that turn on the immune responses required to fight infection.

IFNγ Modulates the Immunopeptidome of Triple Negative Breast Cancer Cells by Enhancing and Diversifying Antigen Processing and Presentation

Peptide vaccination remains a viable approach to induce T-cell mediated killing of tumors. To identify potential T-cell targets for Triple-Negative Breast Cancer (TNBC) vaccination, we examined the effect of the pro-inflammatory cytokine interferon-γ (IFNγ) on the transcriptome, proteome, and immunopeptidome of the TNBC cell line MDA-MB-231. Using high resolution mass spectrometry, we identified a total of 84,131 peptides from 9,647 source proteins presented by human leukocyte antigen (HLA)-I and HLA-II alleles. Treatment with IFNγ resulted in a remarkable remolding of the immunopeptidome, with only a 34% overlap between untreated and treated cells across the HLA-I immunopeptidome, and expression of HLA-II only detected on treated cells. IFNγ increased the overall number, diversity, and abundance of peptides contained within the immunopeptidome, as well increasing the coverage of individual source antigens. The suite of peptides displayed under conditions of IFNγ treatment included many known tumor associated antigens, with the HLA-II repertoire sampling 17 breast cancer associated antigens absent from those sampled by HLA-I molecules. Quantitative analysis of the transcriptome (10,248 transcripts) and proteome (6,783 proteins) of these cells revealed 229 common proteins and transcripts that were differentially expressed. Most of these represented downstream targets of IFNγ signaling including components of the antigen processing machinery such as tapasin and HLA molecules. However, these changes in protein expression did not explain the dramatic modulation of the immunopeptidome following IFNγ treatment. These results demonstrate the high degree of plasticity in the immunopeptidome of TNBC cells following cytokine stimulation and provide evidence that under pro-inflammatory conditions a greater variety of potential HLA-I and HLA-II vaccine targets are unveiled to the immune system. This has important implications for the development of personalized cancer vaccination strategies.

In-Vitro Approaches to Predict and Study T-Cell Mediated Hypersensitivity to Drugs

Mitigating the risk of drug hypersensitivity reactions is an important facet of a given pharmaceutical, with poor performance in this area of safety often leading to warnings, restrictions and withdrawals. In the last 50 years, efforts to diagnose, manage, and circumvent these obscure, iatrogenic diseases have resulted in the development of assays at all stages of a drugs lifespan. Indeed, this begins with intelligent lead compound selection/design to minimize the existence of deleterious chemical reactivity through exclusion of ominous structural moieties. Preclinical studies then investigate how compounds interact with biological systems, with emphasis placed on modeling immunological/toxicological liabilities. During clinical use, competent and accurate diagnoses are sought to effectively manage patients with such ailments, and pharmacovigilance datasets can be used for stratification of patient populations in order to optimise safety profiles. Herein, an overview of some of the in-vitro approaches to predict intrinsic immunogenicity of drugs and diagnose culprit drugs in allergic patients after exposure is detailed, with current perspectives and opportunities provided.

Carbamazepine Induces Focused T Cell Responses in Resolved Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis Cases But Does Not Perturb the Immunopeptidome for T Cell Recognition

Antiseizure medications (ASMs) are frequently implicated in T cell-mediated drug hypersensitivity reactions and cause skin tropic pathologies that range in severity from mild rashes to life-threatening systemic syndromes. During the acute stages of the more severe manifestations of these reactions, drug responsive proinflammatory CD8⁺ T cells display classical features of Th1 cytokine production (e.g. IFNγ) and cytolysis (e.g. granzyme B, perforin). These T cells may be found locally at the site of pathology (e.g. blister cells/fluid), as well as systemically (e.g. blood, organs). What is less understood are the long-lived immunological effects of the memory T cell pool following T cell-mediated drug hypersensitivity reactions. In this study, we examine the ASM carbamazepine (CBZ) and the CBZ-reactive memory T cell pool in patients who have a history of either Stevens-Johnson syndrome (SJS) or toxic epidermal necrolysis (TEN) from 3-to-20 years following their initial adverse reaction. We show that in vitro drug restimulation of CBZ-reactive CD8⁺ T cells results in a proinflammatory profile and produces a mainly focused, yet private, T cell receptor (TCR) usage amongst human leukocyte antigen (HLA)-B*15:02-positive SJS or TEN patients. Additionally, we show that expression of these CBZ-reactive TCRs in a reporter cell line, lacking endogenous αβTCR, recapitulates the features of TCR activation reported for ASM-treated T cell lines/clones, providing a useful tool for further functional validations. Finally, we conduct a comprehensive evaluation of the HLA-B*15:02 immunopeptidome following ASM (or a metabolite) treatment of a HLA-B*15:02-positive B-lymphoblastoid cell line (C1R.B*15:02) and minor perturbation of the peptide repertoire. Collectively, this study shows that the CBZ-reactive T cells characterized require both the drug and HLA-B*15:02 for activation and that reactivation of memory T cells from blood results in a focused private TCR profile in patients with resolved disease.

The dominantly expressed class II molecule from a resistant MHC haplotype presents only a few Marek's disease virus peptides by using an unprecedented binding motif

Viral diseases pose major threats to humans and other animals, including the billions of chickens that are an important food source as well as a public health concern due to zoonotic pathogens. Unlike humans and other typical mammals, the major histocompatibility complex (MHC) of chickens can confer decisive resistance or susceptibility to many viral diseases. An iconic example is Marek's disease, caused by an oncogenic herpesvirus with over 100 genes. Classical MHC class I and class II molecules present antigenic peptides to T lymphocytes, and it has been hard to understand how such MHC molecules could be involved in susceptibility to Marek's disease, given the potential number of peptides from over 100 genes. We used a new in vitro infection system and immunopeptidomics to determine peptide motifs for the 2 class II molecules expressed by the MHC haplotype B2, which is known to confer resistance to Marek's disease. Surprisingly, we found that the vast majority of viral peptide epitopes presented by chicken class II molecules arise from only 4 viral genes, nearly all having the peptide motif for BL2*02, the dominantly expressed class II molecule in chickens. We expressed BL2*02 linked to several Marek's disease virus (MDV) peptides and determined one X-ray crystal structure, showing how a single small amino acid in the binding site causes a crinkle in the peptide, leading to a core binding peptide of 10 amino acids, compared to the 9 amino acids in all other reported class II molecules. The limited number of potential T cell epitopes from such a complex virus can explain the differential MHC-determined resistance to MDV, but raises questions of mechanism and opportunities for vaccine targets in this important food species, as well as providing a basis for understanding class II molecules in other species including humans.

Neoantigen vaccine platforms in clinical development: understanding the future of personalized immunotherapy

INTRODUCTION

Derived from genetic alterations, cancer neoantigens are proteins with novel amino acid sequences that can be recognized by the immune system. Recent evidence demonstrates that cancer neoantigens represent important targets of cancer immunotherapy. The goal of cancer neoantigen vaccines is to induce neoantigen-specific immune responses and antitumor immunity, while minimizing the potential for autoimmune toxicity. Advances in sequencing technologies, neoantigen prediction ?algorithms,? and other technologies have dramatically improved the ability to identify and prioritize cancer neoantigens. These advances have generated considerable enthusiasm for ?the ?development of neoantigen vaccines. Several neoantigen vaccine platforms are currently being evaluated in early phase clinical trials including the synthetic long peptide (SLP), RNA, dendritic cell (DC), and DNA vaccine platforms.

AREAS COVERED

In this review, we describe, evaluate the mechanism(s) of action, compare the advantages and disadvantages, and summarize early clinical experience with each vaccine platform. We provide perspectives on the future directions of the neoantigen vaccine field. All data are derived from PubMed and ClinicalTrials search updated in October 2020.

EXPERT OPINION

Although the initial clinical experience is promising, significant challenges to the success of neoantigen vaccines include limitations in neoantigen identification and the need to successfully target the immunosuppressive tumor microenvironment.

Integral Use of Immunopeptidomics and Immunoinformatics for the Characterization of Antigen Presentation and Rational Identification of BoLA-DR-Presented Peptides and Epitopes

MHC peptide binding and presentation is the most selective event defining the landscape of T cell epitopes. Consequently, understanding the diversity of MHC alleles in a given population and the parameters that define the set of ligands that can be bound and presented by each of these alleles (the immunopeptidome) has an enormous impact on our capacity to predict and manipulate the potential of protein Ags to elicit functional T cell responses. Liquid chromatography-mass spectrometry analysis of MHC-eluted ligand data has proven to be a powerful technique for identifying such peptidomes, and methods integrating such data for prediction of Ag presentation have reached a high level of accuracy for both MHC class I and class II. In this study, we demonstrate how these techniques and prediction methods can be readily extended to the bovine leukocyte Ag class II DR locus (BoLA-DR). BoLA-DR binding motifs were characterized by eluted ligand data derived from bovine cell lines expressing a range of DRB3 alleles prevalent in Holstein-Friesian populations. The model generated (NetBoLAIIpan, available as a Web server at www.cbs.dtu.dk/services/NetBoLAIIpan) was shown to have unprecedented predictive power to identify known BoLA-DR-restricted CD4 epitopes. In summary, the results demonstrate the power of an integrated approach combining advanced mass spectrometry peptidomics with immunoinformatics for characterization of the BoLA-DR Ag presentation system and provide a prediction tool that can be used to assist in rational evaluation and selection of bovine CD4 T cell epitopes.

Robust induction of TRMs by combinatorial nanoshells confers cross-strain sterilizing immunity against lethal influenza viruses

Antigen-specific lung-resident memory T cells (T_RMs) constitute the first line of defense that mediates rapid protection against respiratory pathogens and inspires novel vaccine designs against infectious pandemic threats, yet effective means of inducing T_RMs, particularly via non-viral vectors, remain challenging. Here, we demonstrate safe and potent induction of lung-resident T_RMs using a biodegradable polymeric nanoshell that co-encapsulates antigenic peptides and TLR9 agonist CpG-oligodeoxynucleotide (CpG-ODN) in a virus-mimicking structure. Through subcutaneous priming and intranasal boosting, the combinatorial nanoshell vaccine elicits prominent lung-resident CD4⁺ and CD8⁺ T cells that surprisingly show better durability than live viral infections. In particular, nanoshells containing CpG-ODN and a pair of conserved class I and II major histocompatibility complex-restricted influenza nucleoprotein-derived antigenic peptides are demonstrated to induce near-sterilizing immunity against lethal infections with influenza A viruses of different strains and subtypes in mice, resulting in rapid elimination of replicating viruses. We further examine the pulmonary transport dynamic and optimal composition of the nanoshell vaccine conducive for robust T_RM induction as well as the benefit of subcutaneous priming on T_RM replenishment. The study presents a practical vaccination strategy for inducing protective T_RM-mediated immunity, offering a compelling platform and critical insights in the ongoing quest toward a broadly protective vaccine against universal influenza as well as other respiratory pathogens.

Most non-canonical proteins uniquely populate the proteome or immunopeptidome

Combining RNA sequencing, ribosome profiling, and mass spectrometry, we elucidate the contribution of non-canonical translation to the proteome and major histocompatibility complex (MHC) class I immunopeptidome. Remarkably, of 14,498 proteins identified in three human B cell lymphomas, 2,503 are non-canonical proteins. Of these, 28% are novel isoforms and 72% are cryptic proteins encoded by ostensibly non-coding regions (60%) or frameshifted canonical genes (12%). Cryptic proteins are translated as efficiently as canonical proteins, have more predicted disordered residues and lower stability, and critically generate MHC-I peptides 5-fold more efficiently per translation event. Translating 5' "untranslated" regions hinders downstream translation of genes involved in transcription, translation, and antiviral responses. Novel protein isoforms show strong enrichment for signaling pathways deregulated in cancer. Only a small fraction of cryptic proteins detected in the proteome contribute to the MHC-I immunopeptidome, demonstrating the high preferential access of cryptic defective ribosomal products to the class I pathway.

IDENTIFICATION OF MHC PEPTIDES USING MASS SPECTROMETRY FOR NEOANTIGEN DISCOVERY AND CANCER VACCINE DEVELOPMENT

Immunotherapy with neoantigens presented by major histocompatibility complex (MHC) is one of the most promising approaches in cancer treatment. Using this approach, cancer vaccines can be designed to target tumor-specific mutations that are not found in normal tissues. Clinical trials have demonstrated an increased immune response and eradication of tumors after injecting synthetic peptides selected from the immunopeptidome. Although the sequence of MHC binding peptides can be predicted from genome sequencing and prediction algorithms, this approach results in large numbers of predicted peptides, requiring the confirmation by mass spectrometry (MS) analysis. Identification of MHC peptides by direct MS analysis of immunopeptidome is accurate and sensitive, with tens of thousands of unique peptides potentially identified from either cancer cell line or tumor tissue. Peptides with mutations can also be identified with patient-specific protein databases constructed from genome or transcriptome sequencing data. MS analysis also enables the characterization of the post-translational modifications (PTMs) of those antigens that cannot be predicted. Moreover, PTMs were found to be more efficient in triggering an immune response. In addition to reviewing recent advances in the identification of neoantigens using MS, the techniques for cancer vaccine candidate selection and formulation, vaccine delivery systems, and the potential for use in combination with other therapeutics are also discussed. It is anticipated that MS-based techniques will play an important role in future cancer vaccine development. © 2019 John Wiley & Sons Ltd. Mass Spec Rev 40:110-125, 2021.

The immunopeptidomes of two transmissible cancers and their host have a common, dominant peptide motif

Transmissible cancers are malignant cells that can spread between individuals of a population, akin to both a parasite and a mobile graft. The survival of the Tasmanian devil, the largest remaining marsupial carnivore, is threatened by the remarkable emergence of two independent lineages of transmissible cancer, devil facial tumour (DFT) 1 and devil facial tumour 2 (DFT2). To aid the development of a vaccine and to interrogate how histocompatibility barriers can be overcome, we analysed the peptides bound to major histocompatibility complex class I (MHC‐I) molecules from Tasmanian devil cells and representative cell lines of each transmissible cancer. Here, we show that DFT1 + IFN‐γ and DFT2 cell lines express a restricted repertoire of MHC‐I allotypes compared with fibroblast cells, potentially reducing the breadth of peptide presentation. Comparison of the peptidomes from DFT1 + IFNγ, DFT2 and host fibroblast cells demonstrates a dominant motif, despite differences in MHC‐I allotypes between the cell lines, with preference for a hydrophobic leucine residue at position 3 and position Ω of peptides. DFT1 and DFT2 both present peptides derived from neural proteins, which reflects a shared cellular origin that could be exploited for vaccine design. These results suggest that polymorphisms in MHC‐I molecules between tumours and host can be ‘hidden’ by a common peptide motif, providing the potential for permissive passage of infectious cells and demonstrating complexity in mammalian histocompatibility barriers.

Glycoproteogenomics: Setting the Course for Next-generation Cancer Neoantigen Discovery for Cancer Vaccines

Molecular-assisted precision oncology gained tremendous ground with high-throughput next-generation sequencing (NGS), supported by robust bioinformatics. The quest for genomics-based cancer medicine set the foundations for improved patient stratification, while unveiling a wide array of neoantigens for immunotherapy. Upfront pre-clinical and clinical studies have successfully used tumor-specific peptides in vaccines with minimal off-target effects. However, the low mutational burden presented by many lesions challenges the generalization of these solutions, requiring the diversification of neoantigen sources. Oncoproteogenomics utilizing customized databases for protein annotation by mass spectrometry (MS) is a powerful tool toward this end. Expanding the concept toward exploring proteoforms originated from post-translational modifications (PTMs) will be decisive to improve molecular subtyping and provide potentially targetable functional nodes with increased cancer specificity. Walking through the path of systems biology, we highlight that alterations in protein glycosylation at the cell surface not only have functional impact on cancer progression and dissemination but also originate unique molecular fingerprints for targeted therapeutics. Moreover, we discuss the outstanding challenges required to accommodate glycoproteomics in oncoproteogenomics platforms. We envisage that such rationale may flag a rather neglected research field, generating novel paradigms for precision oncology and immunotherapy.

Identification and selection of immunodominant B and T cell epitopes for dengue multi-epitope-based vaccine

Dengue virus (DENV) comprises four serotypes (DENV1-4) which cause 390 million global infections with 500,000 hospitalizations and 25,000 fatalities annually. Currently, the only FDA approved DENV vaccine is the chimeric live-attenuated vaccine, Dengvaxia®, which is based on the yellow fever virus (YFV) genome that carries the prM and E genes of the respective DENV 1, 2, 3, and 4 serotypes. However, it has lower efficacies against serotypes DENV1 (51%) and DENV2 (34%) when compared with DENV3 (75%) and DENV4 (77%). The absence of T cell epitopes from non-structural (NS) and capsid (C) proteins of the yellow fever vaccine strain might have prevented Dengvaxia® to elicit robust cellular immune responses, as CD8⁺ T cell epitopes are mainly localized in the NS3 and NS5 regions. Multi-epitope-based peptide vaccines carrying CD4⁺, CD8⁺ T cell and B cell epitopes represent a novel approach to generate specific immune responses. Therefore, assessing and selecting epitopes that can induce robust B and T cell responses is a prerequisite for constructing an efficient multi-epitope peptide vaccine. Potent B and T cell epitopes can be identified by utilizing immunoinformatic analysis, but the immunogenicity of the epitopes have to be experimentally validated. In this review, we presented T cell epitopes that have been predicted by bioinformatic approaches as well as recent experimental validations of CD4⁺ and CD8⁺ T cell epitopes by ex-vivo stimulation of PBMCs with specific peptides. Immunoproteomic analysis could be utilized to uncover HLA-specific epitopes presented by DENV-infected cells. Based on various approaches, immunodominant epitopes capable of inducing strong immune responses could be selected and incorporated to form a universally applicable multi-epitope-based peptide dengue vaccine.

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.

Automated Ligand Purification Platform Accelerates Immunopeptidome Analysis by Mass Spectrometry

Major histocompatibility complex (MHC)-presented peptides (pMHC) give insight into T cell immune responses, a critical step toward developing a new generation of targeted immunotherapies. Recent instrumentation advances have propelled mass spectrometry to being arguably the most robust technology for discovering and quantifying naturally presented pMHC from cells and tissues. However, sample preparation has remained a major limitation due to time-consuming and labor-intensive workflows. We developed a high-throughput and automated platform with enhanced speed, sensitivity, and reproducibility relative to prior studies. This pipeline is capable of processing up to 96 samples in 6 h or less yielding high-quality pMHC mixtures ready for mass spectrometry. Here, we describe our efforts to optimize purification and mass spectrometer parameters, ultimately allowing us to identify as many as almost 5000 pMHC I and 7400 pMHC II from as little as 2.5 × 107 Raji cells each. We believe that this platform will facilitate and accelerate immunopeptidome profiling and benefit clinical research for immunotherapies.

The Potential of Soluble Human Leukocyte Antigen Molecules for Early Cancer Detection and Therapeutic Vaccine Design

Human leukocyte antigen (HLA) molecules are essential for anti-tumor immunity, as they display tumor-derived peptides to drive tumor eradication by cytotoxic T lymphocytes. HLA molecules are primarily studied as peptide-loaded complexes on cell membranes (mHLA) and much less attention is given to their secretion as soluble HLA–peptide complexes (sHLA) into bodily fluids. Yet sHLA levels are altered in various pathologies including cancer, and are thus of high interest as biomarkers. Disconcordance in results across studies, however, hampers interpretation and generalization of the relationship between sHLA levels and cancer presence, thereby impairing its use as a biomarker. Furthermore, the question remains to what extent sHLA complexes exert immunomodulatory effects and whether shifts in sHLA levels contribute to disease or are only a consequence of disease. sHLA complexes can also bear tumor-derived peptides and recent advancements in mass spectrometry now permit closer sHLA peptide cargo analysis. sHLA peptide cargo may represent a “liquid biopsy” that could facilitate the use of sHLA for cancer diagnosis and target identification for therapeutic vaccination. This review aims to outline the contradictory and unexplored aspects of sHLA and to provide direction on how the full potential of sHLA as a quantitative and qualitative biomarker can be exploited.

Fast Deisotoping Algorithm and Its Implementation in the MSFragger Search Engine

Deisotoping, or the process of removing peaks in a mass spectrum resulting from the incorporation of naturally occurring heavy isotopes, has long been used to reduce complexity and improve the effectiveness of spectral annotation methods in proteomics. We have previously described MSFragger, an ultrafast search engine for proteomics, that did not utilize deisotoping in processing input spectra. Here, we present a new, high-speed parallelized deisotoping algorithm, based on elements of several existing methods, that we have incorporated into the MSFragger search engine. Applying deisotoping with MSFragger reveals substantial improvements to database search speed and performance, particularly for complex methods like open or nonspecific searches. Finally, we evaluate our deisotoping method on data from several instrument types and vendors, revealing a wide range in performance and offering an updated perspective on deisotoping in the modern proteomics environment.

Thermostability profiling of MHC-bound peptides: a new dimension in immunopeptidomics and aid for immunotherapy design

The features of peptide antigens that contribute to their immunogenicity are not well understood. Although the stability of peptide-MHC (pMHC) is known to be important, current assays assess this interaction only for peptides in isolation and not in the context of natural antigen processing and presentation. Here, we present a method that provides a comprehensive and unbiased measure of pMHC stability for thousands of individual ligands detected simultaneously by mass spectrometry (MS). The method allows rapid assessment of intra-allelic and inter-allelic differences in pMHC stability and reveals profiles of stability that are broader than previously appreciated. The additional dimensionality of the data facilitated the training of a model which improves the prediction of peptide immunogenicity, specifically of cancer neoepitopes. This assay can be applied to any cells bearing MHC or MHC-like molecules, offering insight into not only the endogenous immunopeptidome, but also that of neoepitopes and pathogen-derived sequences.

Is the Proteome of Bronchoalveolar Lavage Extracellular Vesicles a Marker of Advanced Lung Cancer?

Simple Summary

Bronchoalveolar lavage is routinely collected during bronchoscopy for cytology analysis in the diagnostic of lung cancer. Due to low sensitivity of this method, early-stage cancers are undetected, lowering the treatment success. In this study, we analyzed extracellular vesicles isolated from bronchoalveolar lavage of lung cancer suspects by mass spectrometry-based proteomics. The protein composition of bronchoalveolar lavage extracellular vesicles of late-stage cancer showed a higher proteome complexity associated with mortality within the two year follow-up period. We identified a potential therapeutic target DNMT3B complex which was significantly expressed in bronchoalveolar lavage extracellular vesicles as well as in tumor tissue. Bronchoalveolar lavage extracellular vesicles proteome analysis of immune markers indicates the presence of markers of innate immune and fibroblast cells.

Abstract

Acellular bronchoalveolar lavage (BAL) proteomics can partially separate lung cancer from non-lung cancer patients based on principal component analysis and multivariate analysis. Furthermore, the variance in the proteomics data sets is correlated mainly with lung cancer status and, to a lesser extent, smoking status and gender. Despite these advances BAL small and large extracellular vehicles (EVs) proteomes reveal aberrant protein expression in paracrine signaling mechanisms in cancer initiation and progression. We consequently present a case-control study of 24 bronchoalveolar lavage extracellular vesicle samples which were analyzed by state-of-the-art liquid chromatography-mass spectrometry (LC-MS). We obtained evidence that BAL EVs proteome complexity correlated with lung cancer stage 4 and mortality within two years´ follow-up (p value = 0.006). The potential therapeutic target DNMT3B complex is significantly up-regulated in tumor tissue and BAL EVs. The computational analysis of the immune and fibroblast cell markers in EVs suggests that patients who deceased within the follow-up period display higher marker expression indicative of innate immune and fibroblast cells (four out of five cases). This study provides insights into the proteome content of BAL EVs and their correlation to clinical outcomes.

Critical Review of Existing MHC I Immunopeptidome Isolation Methods

Major histocompatibility complex class I (MHC I) plays a crucial role in the development of adaptive immune response in vertebrates. MHC molecules are cell surface protein complexes loaded with short peptides and recognized by the T-cell receptors (TCR). Peptides associated with MHC are named immunopeptidome. The MHC I immunopeptidome is produced by the proteasome degradation of intracellular proteins. The knowledge of the immunopeptidome repertoire facilitates the creation of personalized antitumor or antiviral vaccines. A huge number of publications on the immunopeptidome diversity of different human and mouse biological samples-plasma, peripheral blood mononuclear cells (PBMCs), and solid tissues, including tumors-appeared in the scientific journals in the last decade. Significant immunopeptidome identification efficiency was achieved by advances in technology: the immunoprecipitation of MHC and mass spectrometry-based approaches. Researchers optimized common strategies to isolate MHC-associated peptides for individual tasks. They published many protocols with differences in the amount and type of biological sample, amount of antibodies, type and amount of insoluble support, methods of post-fractionation and purification, and approaches to LC-MS/MS identification of immunopeptidome. These parameters have a large impact on the final repertoire of isolated immunopeptidome. In this review, we summarize and compare immunopeptidome isolation techniques with an emphasis on the results obtained.

Emerging mass spectrometry-based proteomics methodologies for novel biomedical applications

Research into the basic biology of human health and disease, as well as translational human research and clinical applications, all benefit from the growing accessibility and versatility of mass spectrometry (MS)-based proteomics. Although once limited in throughput and sensitivity, proteomic studies have quickly grown in scope and scale over the last decade due to significant advances in instrumentation, computational approaches, and bio-sample preparation. Here, we review these latest developments in MS and highlight how these techniques are used to study the mechanisms, diagnosis, and treatment of human diseases. We first describe recent groundbreaking technological advancements for MS-based proteomics, including novel data acquisition techniques and protein quantification approaches. Next, we describe innovations that enable the unprecedented depth of coverage in protein signaling and spatiotemporal protein distributions, including studies of post-translational modifications, protein turnover, and single-cell proteomics. Finally, we explore new workflows to investigate protein complexes and structures, and we present new approaches for protein-protein interaction studies and intact protein or top-down MS. While these approaches are only recently incipient, we anticipate that their use in biomedical MS proteomics research will offer actionable discoveries for the improvement of human health.

Single-cell derived tumor organoids display diversity in HLA class I peptide presentation

Tumor heterogeneity is a major cause of therapeutic resistance. Immunotherapy may exploit alternative vulnerabilities of drug-resistant cells, where tumor-specific human leukocyte antigen (HLA) peptide ligands are promising leads to invoke targeted anti-tumor responses. Here, we investigate the variability in HLA class I peptide presentation between different clonal cells of the same colorectal cancer patient, using an organoid system. While clone-specific differences in HLA peptide presentation were observed, broad inter-clone variability was even more prevalent (15–25%). By coupling organoid proteomics and HLA peptide ligandomics, we also found that tumor-specific ligands from DNA damage control and tumor suppressor source proteins were prominently presented by tumor cells, coinciding likely with the silencing of such cytoprotective functions. Collectively, these data illustrate the heterogeneous HLA peptide presentation landscape even within one individual, and hint that a multi-peptide vaccination approach against highly conserved tumor suppressors may be a viable option in patients with low tumor-mutational burden.

Immunotherapy may exploit alternative vulnerabilities of drug resistant cells. Here, the authors show that the HLA peptide presentation landscape is heterogeneous even within one individual, hinting that a multi-peptide vaccination approach against highly conserved tumor suppressors may be needed.

Improved prediction of HLA antigen presentation hotspots: Applications for immunogenicity risk assessment of therapeutic proteins

Immunogenicity risk assessment is a critical element in protein drug development. Currently, the risk assessment is most often performed using MHC-associated peptide proteomics (MAPPs) and/or T-cell activation assays. However, this is a highly costly procedure that encompasses limited sensitivity imposed by sample sizes, the MHC repertoire of the tested donor cohort and the experimental procedures applied. Recent work has suggested that these techniques could be complemented by accurate, high-throughput and cost-effective prediction of in silico models. However, this work covered a very limited set of therapeutic proteins and eluted ligand (EL) data. Here, we resolved these limitations by showcasing, in a broader setting, the versatility of in silico models for assessment of protein drug immunogenicity. A method for prediction of MHC class II antigen presentation was developed on the hereto largest available mass spectrometry (MS) HLA-DR EL data set. Using independent test sets, the performance of the method for prediction of HLA-DR antigen presentation hotspots was benchmarked. In particular, the method was showcased on a set of protein sequences including four therapeutic proteins and demonstrated to accurately predict the experimental MS hotspot regions at a significantly lower false-positive rate compared with other methods. This gain in performance was particularly pronounced when compared to the NetMHCIIpan-3.2 method trained on binding affinity data. These results suggest that in silico methods trained on MS HLA EL data can effectively and accurately be used to complement MAPPs assays for the risk assessment of protein drugs.

Solving an MHC allele-specific bias in the reported immunopeptidome

Identification of MHC class I–bound peptides by immunopurification of MHC complexes and subsequent analysis by mass spectrometry is crucial for understanding T cell immunology and immunotherapy. Investigation of the steps for the MHC ligand isolation process revealed biases in widely used isolation techniques toward peptides of lower hydrophobicity. As MHC ligand hydrophobicity correlates positively with immunogenicity, identification of more hydrophobic MHC ligands could potentially lead to more effective isolation of immunogenic peptides as targets for immunotherapies. We solved this problem by use of higher concentrations of acetonitrile for the separation of MHC ligands and their respective complexes. This increased overall MHC ligand identifications by 2-fold, increased detection of cancer germline antigen–derived peptides by 50%, and resulted in profound variations in isolation efficacy between different MHC alleles correlating with the hydrophobicity of their anchor residues. Overall, these insights enabled a more complete view of the immunopeptidome and overcame a systematic underrepresentation of these critical MHC ligands of high hydrophobicity.

An approach is identified to prevent bias in the immunopeptidome towards MHC ligands of lower hydrophobicity and therefore immunogenicity.

Variations in MHC class I antigen presentation and immunopeptidome selection pathways

Major histocompatibility class I (MHC-I) proteins mediate immunosurveillance against pathogens and cancers by presenting antigenic or mutated peptides to antigen receptors of CD8+ T cells and by engaging receptors of natural killer (NK) cells. In humans, MHC-I molecules are highly polymorphic. MHC-I variations permit the display of thousands of distinct peptides at the cell surface. Recent mass spectrometric studies have revealed unique and shared characteristics of the peptidomes of individual MHC-I variants. The cell surface expression of MHC-I–peptide complexes requires the functions of many intracellular assembly factors, including the transporter associated with antigen presentation (TAP), tapasin, calreticulin, ERp57, TAP-binding protein related (TAPBPR), endoplasmic reticulum aminopeptidases (ERAPs), and the proteasomes. Recent studies provide important insights into the structural features of these factors that govern MHC-I assembly as well as the mechanisms underlying peptide exchange. Conformational sensing of MHC-I molecules mediates the quality control of intracellular MHC-I assembly and contributes to immune recognition by CD8 at the cell surface. Recent studies also show that several MHC-I variants can follow unconventional assembly routes to the cell surface, conferring selective immune advantages that can be exploited for immunotherapy.

Spliced Peptides and Cytokine-Driven Changes in the Immunopeptidome of Melanoma

Antigen recognition by CD8⁺ T cells is governed by the pool of peptide antigens presented on the cell surface in the context of HLA class I complexes. Studies have shown not only a high degree of plasticity in the immunopeptidome, but also that a considerable fraction of all presented peptides is generated through proteasome-mediated splicing of noncontiguous regions of proteins to form novel peptide antigens. Here, we used high-resolution mass spectrometry combined with new bioinformatic approaches to characterize the immunopeptidome of melanoma cells in the presence or absence of IFNγ. In total, we identified more than 60,000 peptides from a single patient-derived cell line (LM-MEL-44) and demonstrated that IFNγ induced changes in the peptidome, with an overlap of only approximately 50% between basal and treated cells. Around 6% to 8% of the peptides were identified as cis-spliced peptides, and 2,213 peptides (1,827 linear and 386 cis-spliced peptides) were derived from known melanoma-associated antigens. These peptide antigens were equally distributed between the constitutive- and IFNγ-induced peptidome. We next examined additional HLA-matched patient-derived cell lines to investigate how frequently these peptides were identified and found that a high proportion of both linear and spliced peptides was conserved between individual patient tumors, drawing on data amassing to more than 100,000 peptide sequences. Several of these peptides showed in vitro immunogenicity across multiple patients with melanoma. These observations highlight the breadth and complexity of the repertoire of immunogenic peptides that can be exploited therapeutically and suggest that spliced peptides are a major class of tumor antigens.

HNSCC: Tumour Antigens and Their Targeting by Immunotherapy

Head and neck squamous cell carcinomas (HNSCC) are a heterogeneous group of malignant tumours typically caused by alcohol and tobacco consumption, although an increasing number of HNSCC arise due to persistent infection with high-risk human papilloma virus (HPV). The treatment of HNSCC remains challenging, and the first-line setting is focused on surgery and chemoradiotherapy. A substantial proportion of HNSCC patients die from their disease, especially those with recurrent and metastatic disease. Among factors linked with good outcome, immune cell infiltration appears to have a major role. HPV-driven HNSCC are often T-cell rich, reflecting the presence of HPV antigens that are immunogenic. Tumour-associated antigens that are shared between patients or that are unique to an individual person may also induce varying degrees of immune response; studying these is important for the understanding of the interaction between the host immune system and the cancer. The resulting knowledge is critical for the design of better immunotherapies. Key questions are: Which antigens lead to an adaptive immune response in the tumour? Which of these are exploitable for immunotherapy? Here, we review the current thinking regarding tumour antigens in HNSCC and what has been learned from early phase clinical trials.

Breaking Bottlenecks for the TCR Therapy of Cancer

Immune checkpoint inhibitors have redefined the treatment of cancer, but their efficacy depends critically on the presence of sufficient tumor-specific lymphocytes, and cellular immunotherapies develop rapidly to fill this gap. The paucity of suitable extracellular and tumor-associated antigens in solid cancers necessitates the use of neoantigen-directed T-cell-receptor (TCR)-engineered cells, while prevention of tumor evasion requires combined targeting of multiple neoepitopes. These can be currently identified within 2 weeks by combining cutting-edge next-generation sequencing with bioinformatic pipelines and used to select tumor-reactive TCRs in a high-throughput manner for expeditious scalable non-viral gene editing of autologous or allogeneic lymphocytes. "Young" cells with a naive, memory stem or central memory phenotype can be additionally armored with "next-generation" features against exhaustion and the immunosuppressive tumor microenvironment, where they wander after reinfusion to attack heavily pretreated and hitherto hopeless neoplasms. Facilitated by major technological breakthroughs in critical manufacturing steps, based on a solid preclinical rationale, and backed by rapidly accumulating evidence, TCR therapies break one bottleneck after the other and hold the promise to become the next immuno-oncological revolution.

Mass spectrometry profiling of low molecular weight proteins and peptides isolated by acetone precipitation

Solvent-based protein precipitation provides exceptional recovery, particularly when the ionic strength of the solution is controlled. While precipitation is ideally suited for intact protein purification ahead of mass-spectrometry, low molecular weight (LMW) proteins and peptides are considered less susceptible to aggregation in organic solvent. As the combination of salt and organic solvent (i.e. acetone) has yet to be exploited to precipitate LMW proteins, we herein determine the low mass limit for solvent-based protein precipitation. We establish optimized conditions for high recovery precipitation of LMW proteins and peptides. Our results demonstrate a strong dependence on the type of salt to recover LMW components from complex mixtures. Inclusion of 100 mM ZnSO₄ with 97% acetone provides near quantitative recovery of all peptides down to 2 kDa, and continues to exceed 90% yield for peptides at a molecular weight of 1 kDa. A detailed characterization of the precipitated peptides resulting from trypsin and pepsin digestion of complex systems is provided by bottom-up mass spectrometry.

Large-Scale Structure-Based Prediction of Stable Peptide Binding to Class I HLAs Using Random Forests

Prediction of stable peptide binding to Class I HLAs is an important component for designing immunotherapies. While the best performing predictors are based on machine learning algorithms trained on peptide-HLA (pHLA) sequences, the use of structure for training predictors deserves further exploration. Given enough pHLA structures, a predictor based on the residue-residue interactions found in these structures has the potential to generalize for alleles with little or no experimental data. We have previously developed APE-Gen, a modeling approach able to produce pHLA structures in a scalable manner. In this work we use APE-Gen to model over 150,000 pHLA structures, the largest dataset of its kind, which were used to train a structure-based pan-allele model. We extract simple, homogenous features based on residue-residue distances between peptide and HLA, and build a random forest model for predicting stable pHLA binding. Our model achieves competitive AUROC values on leave-one-allele-out validation tests using significantly less data when compared to popular sequence-based methods. Additionally, our model offers an interpretation analysis that can reveal how the model composes the features to arrive at any given prediction. This interpretation analysis can be used to check if the model is in line with chemical intuition, and we showcase particular examples. Our work is a significant step toward using structure to achieve generalizable and more interpretable prediction for stable pHLA binding.

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

The presentation of post-translationally modified (PTM) peptides by cell surface HLA molecules has the potential to increase the diversity of targets for surveilling T cells. Although immunopeptidomics studies routinely identify thousands of HLA-bound peptides from cell lines and tissue samples, in-depth analyses of the proportion and nature of peptides bearing one or more PTMs remains challenging. Here we have analyzed HLA-bound peptides from a variety of allotypes and assessed the distribution of mass spectrometry-detected PTMs, finding deamidation of asparagine or glutamine to be highly prevalent. Given that asparagine deamidation may arise either spontaneously or through enzymatic reaction, we assessed allele-specific and global motifs flanking the modified residues. Notably, we found that the N-linked glycosylation motif NX(S/T) was highly abundant across asparagine-deamidated HLA-bound peptides. This finding, demonstrated previously for a handful of deamidated T cell epitopes, implicates a more global role for the retrograde transport of nascently N-glycosylated polypeptides from the ER and their subsequent degradation within the cytosol to form HLA-ligand precursors. Chemical inhibition of Peptide:N-Glycanase (PNGase), the endoglycosidase responsible for the removal of glycans from misfolded and retrotranslocated glycoproteins, greatly reduced presentation of this subset of deamidated HLA-bound peptides. Importantly, there was no impact of PNGase inhibition on peptides not containing a consensus NX(S/T) motif. This indicates that a large proportion of HLA-I bound asparagine deamidated peptides are generated from formerly glycosylated proteins that have undergone deglycosylation via the ER-associated protein degradation (ERAD) pathway. The information herein will help train deamidation prediction models for HLA-peptide repertoires and aid in the design of novel T cell therapeutic targets derived from glycoprotein antigens.

Neoantigen-Specific Adoptive Cell Therapies for Cancer: Making T-Cell Products More Personal

Mutation-derived neoantigens are taking central stage as a determinant in eliciting effective antitumor immune responses following adoptive T-cell therapies. These mutations are patient-specific, and their targeting calls for highly personalized pipelines. The promising clinical outcomes of tumor-infiltrating lymphocyte (TIL) therapy have spurred interest in generating T-cell infusion products that have been selectively enriched in neoantigen (or autologous tumor) reactivity. The implementation of an isolation step, prior to T-cell in vitro expansion and reinfusion, may provide a way to improve the overall response rates achieved to date by adoptive T-cell therapies in metastatic cancer patients. Here we provide an overview of the main technologies [i.e., peptide major histocompatibility complex (pMHC) multimers, cytokine capture, and activation markers] to enrich infiltrating or circulating T-cells in predefined neoantigen specificities (or tumor reactivity). The unique technical and regulatory challenges faced by such highly specialized and patient-specific manufacturing T-cell platforms are also discussed.

The Age of Data-Driven Proteomics: How Machine Learning Enables Novel Workflows

A lot of energy in the field of proteomics is dedicated to the application of challenging experimental workflows, which include metaproteomics, proteogenomics, data independent acquisition (DIA), non-specific proteolysis, immunopeptidomics, and open modification searches. These workflows are all challenging because of ambiguity in the identification stage; they either expand the search space and thus increase the ambiguity of identifications, or, in the case of DIA, they generate data that is inherently more ambiguous. In this context, machine learning-based predictive models are now generating considerable excitement in the field of proteomics because these predictive models hold great potential to drastically reduce the ambiguity in the identification process of the above-mentioned workflows. Indeed, the field has already produced classical machine learning and deep learning models to predict almost every aspect of a liquid chromatography-mass spectrometry (LC-MS) experiment. Yet despite all the excitement, thorough integration of predictive models in these challenging LC-MS workflows is still limited, and further improvements to the modeling and validation procedures can still be made. Therefore, highly promising recent machine learning developments in proteomics are pointed out in this viewpoint, alongside some of the remaining challenges.

Uncovering the Tumor Antigen Landscape: What to Know about the Discovery Process

According to the latest available data, cancer is the second leading cause of death, highlighting the need for novel cancer therapeutic approaches. In this context, immunotherapy is emerging as a reliable first-line treatment for many cancers, particularly metastatic melanoma. Indeed, cancer immunotherapy has attracted great interest following the recent clinical approval of antibodies targeting immune checkpoint molecules, such as PD-1, PD-L1, and CTLA-4, that release the brakes of the immune system, thus reviving a field otherwise poorly explored. Cancer immunotherapy mainly relies on the generation and stimulation of cytotoxic CD8 T lymphocytes (CTLs) within the tumor microenvironment (TME), priming T cells and establishing efficient and durable anti-tumor immunity. Therefore, there is a clear need to define and identify immunogenic T cell epitopes to use in therapeutic cancer vaccines. Naturally presented antigens in the human leucocyte antigen-1 (HLA-I) complex on the tumor surface are the main protagonists in evocating a specific anti-tumor CD8+ T cell response. However, the methodologies for their identification have been a major bottleneck for their reliable characterization. Consequently, the field of antigen discovery has yet to improve. The current review is intended to define what are today known as tumor antigens, with a main focus on CTL antigenic peptides. We also review the techniques developed and employed to date for antigen discovery, exploring both the direct elution of HLA-I peptides and the in silico prediction of epitopes. Finally, the last part of the review analyses the future challenges and direction of the antigen discovery field.

Approaching complexity: systems biology and ms-based techniques to address immune signaling

INTRODUCTION

Studying immune signaling has been critical for our understanding of immunology, pathogenesis, cancer, and homeostasis. To enhance the breadth of the analysis, high throughput methods have been developed to survey multiple areas simultaneously, including transcriptomics, reporter assays, and ELISAs. While these techniques have been extremely informative, mass-spectrometry-based technologies have been gaining momentum and starting to be widely used in the studies of immune signaling and systems immunology.

AREAS COVERED

We present established proteomic methods that have been used to address immune signaling and discuss the new mass-spectrometry- based techniques of interest to the expanding field of systems immunology. Established and new proteomic methods and their applications discussed here include post-translational modification analysis, protein quantification, secretome analysis, and interactomics. In addition, we present developments in small molecule and metabolite analysis, mass spectrometry imaging, and single cell analysis. Finally, we discuss the role of multi-omic integration in aiding leading edge investigation.

EXPERT OPINION

In science, available techniques enhance the breadth and depth of the studies. By incorporating proteomic techniques and their innovative use, it will be possible to expand the current studies and to address novel questions at the forefront of scientific discovery.

Orf Virus-Based Vaccine Vector D1701-V Induces Strong CD8+ T Cell Response against the Transgene but Not against ORFV-Derived Epitopes

The potency of viral vector-based vaccines depends on their ability to induce strong transgene-specific immune response without triggering anti-vector immunity. Previously, Orf virus (ORFV, Parapoxvirus) strain D1701-V was reported as a novel vector mediating protection against viral infections. The short-lived ORFV-specific immune response and the absence of virus neutralizing antibodies enables repeated immunizations and enhancement of humoral immune responses against the inserted antigens. However, only limited information exists about the D1701-V induced cellular immunity. In this study we employed major histocompatibility complex (MHC) ligandomics and immunogenicity analysis to identify ORFV-specific epitopes. Using liquid chromatography-tandem mass spectrometry we detected 36 ORFV-derived MHC I peptides, originating from various proteins. Stimulated splenocytes from ORFV-immunized mice did not exhibit specific CD8+ T cell responses against the tested peptides. In contrast, immunization with ovalbumin-expressing ORFV recombinant elicited strong SIINFEKL-specific CD8+ T lymphocyte response. In conclusion, our data indicate that cellular immunity to the ORFV vector is negligible, while strong CD8+ T cell response is induced against the inserted transgene. These results further emphasize the ORFV strain D1701-V as an attractive vector for vaccine development. Moreover, the presented experiments describe prerequisites for the selection of T cell epitopes exploitable for generation of ORFV-based vaccines by reverse genetics.

Opportunities for an atherosclerosis vaccine: From mice to humans

Atherosclerosis, the major underlying cause of cardiovascular diseases (CVD), is the number one killer globally. The disease pathogenesis involves a complex interplay between metabolic and immune components. Although lipid-lowering drugs such as statins curb the risks associated with CVD, significant residual inflammatory risk remains. Substantial evidence from experimental models and clinical studies has established the role of inflammation and immune effector mechanisms in the pathogenesis of atherosclerosis. Several stages of the disease are affected by host-mediated antigen-specific adaptive immune responses that play either protective or proatherogenic roles. Therefore, strategies to boost an anti-atherogenic humoral and T regulatory cell response are emerging as preventative or therapeutic strategies to lowering inflammatory residual risks. Vaccination holds promise as an efficient, durable and relatively inexpensive approach to induce protective adaptive immunity in atherosclerotic patients. In this review, we discuss the status and opportunities for a human atherosclerosis vaccine. We describe (1) some of the immunomodulatory therapeutic interventions tested in atherosclerosis (2) the immune targets identified in pre-clinical and clinical investigations (3) immunization strategies evaluated in animal models (4) past and ongoing clinical trials to examine the safety and efficacy of human atherosclerosis vaccines and (5) strategies to improve and optimize vaccination in humans (antigen selection, formulation, dose and delivery).

Multiplexed relative and absolute quantitative immunopeptidomics reveals MHC I repertoire alterations induced by CDK4/6 inhibition

Peptides bound to class I major histocompatibility complexes (MHC) play a critical role in immune cell recognition and can trigger an antitumor immune response in cancer. Surface MHC levels can be modulated by anticancer agents, altering immunity. However, understanding the peptide repertoire's response to treatment remains challenging and is limited by quantitative mass spectrometry-based strategies lacking normalization controls. We describe an experimental platform that leverages recombinant heavy isotope-coded peptide MHCs (hipMHCs) and multiplex isotope tagging to quantify peptide repertoire alterations using low sample input. HipMHCs improve quantitative accuracy of peptide repertoire changes by normalizing for variation across analyses and enable absolute quantification using internal calibrants to determine copies per cell of MHC antigens, which can inform immunotherapy design. Applying this platform in melanoma cell lines to profile the immunopeptidome response to CDK4/6 inhibition and interferon-γ - known modulators of antigen presentation - uncovers treatment-specific alterations, connecting the intracellular response to extracellular immune presentation.

The Choice of HLA-Associated Peptide Enrichment and Purification Strategy Affects Peptide Yields and Creates a Bias in Detected Sequence Repertoire

Understanding the most appropriate workflow for biochemical human leukocyte antigen (HLA)-associated peptide enrichment prior to ligand sequencing is essential to achieve optimal sensitivity in immunopeptidomics experiments. The use of different detergents for HLA solubilization as well as complementary workflows to separate HLA-bound peptides from HLA protein complex components after their immunoprecipitation including HPLC, C18 cartridge, and 5 kDa filter are described. It is observed that all solubilization approaches tested led to similar peptide ligand identification rates; however, a higher number of peptides are identified in samples lysed with CHAPS compared with other methods. The HPLC method is superior in terms of HLA-I peptide recovery compared with 5 kDa filter and C18 cartridge peptide purification methods. Most importantly, it is observed that both the choice of detergent and peptide purification strategy creates a significant bias for the identified peptide sequences, and that allele-specific peptide repertoires are affected depending on the workflow of choice. The results highlight the importance of employing a suitable strategy for HLA peptide enrichment and that the obtained peptide repertoires do not necessarily reflect the true distributions of peptide sequences in the sample.

HLA Class II Specificity Assessed by High-Density Peptide Microarray Interactions

The ability to predict and/or identify MHC binding peptides is an essential component of T cell epitope discovery, something that ultimately should benefit the development of vaccines and immunotherapies. In particular, MHC class I prediction tools have matured to a point where accurate selection of optimal peptide epitopes is possible for virtually all MHC class I allotypes; in comparison, current MHC class II (MHC-II) predictors are less mature. Because MHC-II restricted CD4⁺ T cells control and orchestrated most immune responses, this shortcoming severely hampers the development of effective immunotherapies. The ability to generate large panels of peptides and subsequently large bodies of peptide-MHC-II interaction data are key to the solution of this problem, a solution that also will support the improvement of bioinformatics predictors, which critically relies on the availability of large amounts of accurate, diverse, and representative data. In this study, we have used rHLA-DRB1*01:01 and HLA-DRB1*03:01 molecules to interrogate high-density peptide arrays, in casu containing 70,000 random peptides in triplicates. We demonstrate that the binding data acquired contains systematic and interpretable information reflecting the specificity of the HLA-DR molecules investigated, suitable of training predictors able to predict T cell epitopes and peptides eluted from human EBV-transformed B cells. Collectively, with a cost per peptide reduced to a few cents, combined with the flexibility of rHLA technology, this poses an attractive strategy to generate vast bodies of MHC-II binding data at an unprecedented speed and for the benefit of generating peptide-MHC-II binding data as well as improving MHC-II prediction tools.

In-depth mining of the immunopeptidome of an acute myeloid leukemia cell line using complementary ligand enrichment and data acquisition strategies

The identification of T cell epitopes derived from tumour specific antigens remains a significant challenge for the development of peptide-based vaccines and immunotherapies. The use of mass spectrometry-based approaches (immunopeptidomics) can provide powerful new avenues for the identification of such epitopes. In this study we report the use of complementary peptide antigen enrichment methods and a comprehensive mass spectrometric acquisition strategy to provide in-depth immunopeptidome data for the THP-1 cell line, a cell line used widely as a model of human leukaemia. To accomplish this, we combined robust experimental workflows that incorporated ultrafiltration or off-line reversed phase chromatography to enrich peptide ligand as well as a multifaceted data acquisition strategy using an Orbitrap Fusion LC-MS instrument. Using the combined datasets from the two ligand enrichment methods we gained significant depth in immunopeptidome coverage by identifying a total of 41,816 HLA class I peptides from THP-1 cells, including a significant number of peptides derived from different oncogenes or over expressed proteins associated with cancer. The physicochemical properties of the HLA-bound peptides dictated their recovery using the two ligand enrichment approaches and their distribution across the different precursor charge states considered in the data acquisition strategy. The data highlight the complementarity of the two enrichment procedures, and in cases where sample is not limiting, suggest that the combination of both approaches will yield the most comprehensive immunopeptidome information.

Post-mortem tissue donation programs as platforms to accelerate cancer research

Given recent advances in the treatment of cancer, patients are surviving longer but frequently develop treatment-resistant and inoperable metastases. Biomedical research has advanced to the stage where in-depth study of these lesions is feasible, with the goal of further refining our understanding of metastatic dissemination, therapeutic resistance and inoperable tumors. However, there is a lack of tissue specimens derived from multiple metastatic sites within the same patient that would permit the study of these processes. Furthermore, patients with rapidly progressing or metastatic disease are rarely candidates for surgery, making those most in need of innovation and discovery extremely difficult to study. For this reason, post-mortem tissue donation programs are an approach that is quickly gaining traction in the cancer research community. Herein, we discuss what post-mortem tissue donation entails, attitudes towards these procedures, and highlight important studies already utilizing these resources. In addition, we propose future directions for use of this tissue that can directly improve clinical management of advanced cancer patients.

Mass Spectrometry-Based Identification of MHC-Associated Peptides

Neoantigen-based immunotherapies promise to improve patient outcomes over the current standard of care. However, detecting these cancer-specific antigens is one of the significant challenges in the field of mass spectrometry. Even though the first sequencing of the immunopeptides was done decades ago, today there is still a diversity of the protocols used for neoantigen isolation from the cell surface. This heterogeneity makes it difficult to compare results between the laboratories and the studies. Isolation of the neoantigens from the cell surface is usually done by mild acid elution (MAE) or immunoprecipitation (IP) protocol. However, limited amounts of the neoantigens present on the cell surface impose a challenge and require instrumentation with enough sensitivity and accuracy for their detection. Detecting these neopeptides from small amounts of available patient tissue limits the scope of most of the studies to cell cultures. Here, we summarize protocols for the extraction and identification of the major histocompatibility complex (MHC) class I and II peptides. We aimed to evaluate existing methods in terms of the appropriateness of the isolation procedure, as well as instrumental parameters used for neoantigen detection. We also focus on the amount of the material used in the protocols as the critical factor to consider when analyzing neoantigens. Beyond experimental aspects, there are numerous readily available proteomics suits/tools applicable for neoantigen discovery; however, experimental validation is still necessary for neoantigen characterization.

Computational Prediction and Validation of Tumor-Associated Neoantigens

Tumor progression is typically accompanied by an accumulation of driver and passenger somatic mutations. A handful of those mutations occur in protein coding genes which introduce non-synonymous polymorphisms. Certain substitutions may give rise to novel, tumor-associated antigens or neoantigens, presentable by cancer cells to the host adaptive immune system. As antigen recognition is the core of an effective immune response, the identification of patient tumor specific antigens derived from transformed cells is of importance for immunotherapeutic approaches. Recent technological advances in DNA sequencing of tumor genomes, advances in gene expression analysis, algorithm development for antigen predictions and methods for T-cell receptor (TCR) repertoire sequencing have facilitated the selection of candidate immunogenic neoantigens. In this regard, multiple research groups have reported encouraging results of neoantigen-based cancer vaccines that generate tumor antigen specific immune responses, both in mouse models and clinical trials. Additionally, both the quantity and quality of neoantigens has been shown to have predictive value for clinical outcomes in checkpoint-blockade immunotherapy in certain tumor types. Neoantigen recognition by vaccination or through adoptive T cell therapy may have unprecedented potential to advance cancer immunotherapy in combination with other approaches. In our review we discuss three parameters regarding neoantigens: computational methods for epitope prediction, experimental methods for epitope immunogenicity validation and future directions for improvement of those methods. Within each section, we will describe the advantages and limitations of existing methods as well as highlight pressing fundamental problems to be addressed.

Peptide Presentation to T Cells: Solving the Immunogenic Puzzle: Systems Immunology Profiling of Antigen Presentation for Prediction of CD8+ T Cell Immunogenicity

The vertebrate immune system uses an impressive arsenal of mechanisms to combat harmful cellular states such as infection. One way is via cells delivering real-time snapshots of their protein content to the cell surface in the form of short peptides. Specialized immune cells (T cells) sample these peptides and assess whether they are foreign, warranting an action such as destruction of the infected cell. The delivery of peptides to the cell surface is termed antigen processing and presentation, and decades of research have provided unprecedented understanding of this process. However, predicting the capacity for a given peptide to be immunogenic-to elicit a T cell response-has remained both enigmatic and a long sought-after goal. In the era of big data, a point is being approached where the steps of antigen processing and presentation can be quantified and assessed against peptide immunogenicity in order to build predictive models. This review presents new findings in this area and contemplates challenges ahead.