Soluble plasma HLA peptidome as a potential source for cancer biomarkers

Immunopeptidome mining reveals a novel ERS-induced target in T1D

Autoreactive CD8+ T cells play a key role in type 1 diabetes (T1D), but the antigen spectrum that activates autoreactive CD8+ T cells remains unclear. Endoplasmic reticulum stress (ERS) has been implicated in β-cell autoantigen generation. Here, we analyzed the major histocompatibility complex class I (MHC-I)-associated immunopeptidome (MIP) of islet β-cells under steady and ERS conditions and found that ERS reshaped the MIP of β-cells and promoted the MHC-I presentation of a panel of conventional self-peptides. Among them, OTUB258-66 showed immunodominance, and the corresponding autoreactive CD8+ T cells were diabetogenic in nonobese diabetic (NOD) mice. High glucose intake upregulated pancreatic OTUB2 expression and amplified the OTUB258-66-specific CD8+ T-cell response in NOD mice. Repeated OTUB258-66 administration significantly reduced the incidence of T1D in NOD mice. Interestingly, peripheral blood mononuclear cells (PBMCs) from patients with T1D, but not from healthy controls, showed a positive IFN-γ response to human OTUB2 peptides. This study provides not only a new explanation for the role of ERS in promoting β-cell-targeted autoimmunity but also a potential target for the prevention and treatment of T1D. The data are available via ProteomeXchange with the identifier PXD041227.

The SysteMHC Atlas v2.0, an updated resource for mass spectrometry-based immunopeptidomics

The SysteMHC Atlas v1.0 was the first public repository dedicated to mass spectrometry-based immunopeptidomics. Here we introduce a newly released version of the SysteMHC Atlas v2.0 (https://systemhc.sjtu.edu.cn), a comprehensive collection of 7190 MS files from 303 allotypes. We extended and optimized a computational pipeline that allows the identification of MHC-bound peptides carrying on unexpected post-translational modifications (PTMs), thereby resulting in 471K modified peptides identified over 60 distinct PTM types. In total, we identified approximately 1.0 million and 1.1 million unique peptides for MHC class I and class II immunopeptidomes, respectively, indicating a 6.8-fold increase and a 28-fold increase to those in v1.0. The SysteMHC Atlas v2.0 introduces several new features, including the inclusion of non-UniProt peptides, and the incorporation of several novel computational tools for FDR estimation, binding affinity prediction and motif deconvolution. Additionally, we enhanced the user interface, upgraded website framework, and provided external links to other resources related. Finally, we built and provided various spectral libraries as community resources for data mining and future immunopeptidomic and proteomic analysis. We believe that the SysteMHC Atlas v2.0 is a unique resource to provide key insights to the immunology and proteomics community and will accelerate the development of vaccines and immunotherapies.

Origins, Technological Advancement, and Applications of Peptidomics

Peptidomics is the comprehensive characterization of peptides from biological sources instead of heading for a few single peptides in former peptide research. Mass spectrometry allows to detect a multitude of peptides in complex mixtures and thus enables new strategies leading to peptidomics. The term was established in the year 2001, and up to now, this new field has grown to over 3000 publications. Analytical techniques originally developed for fast and comprehensive analysis of peptides in proteomics were specifically adjusted for peptidomics. Although it is thus closely linked to proteomics, there are fundamental differences with conventional bottom-up proteomics. Fundamental technological advancements of peptidomics since have occurred in mass spectrometry and data processing, including quantification, and more slightly in separation technology. Different strategies and diverse sources of peptidomes are mentioned by numerous applications, such as discovery of neuropeptides and other bioactive peptides, including the use of biochemical assays. Furthermore, food and plant peptidomics are introduced similarly. Additionally, applications with a clinical focus are included, comprising biomarker discovery as well as immunopeptidomics. This overview extensively reviews recent methods, strategies, and applications including links to all other chapters of this book.

IMBAS-MS Discovers Organ-Specific HLA Peptide Patterns in Plasma

Distinction of non-self from self is the major task of the immune system. Immunopeptidomics studies the peptide repertoire presented by the human leukocyte antigen (HLA) protein, usually on tissues. However, HLA peptides are also bound to plasma soluble HLA (sHLA), but little is known about their origin and potential for biomarker discovery in this readily available biofluid. Currently, immunopeptidomics is hampered by complex workflows and limited sensitivity, typically requiring several mL of plasma. Here, we take advantage of recent improvements in the throughput and sensitivity of mass spectrometry (MS)-based proteomics to develop a highly sensitive, automated, and economical workflow for HLA peptide analysis, termed Immunopeptidomics by Biotinylated Antibodies and Streptavidin (IMBAS). IMBAS-MS quantifies more than 5000 HLA class I peptides from only 200 μl of plasma, in just 30 min. Our technology revealed that the plasma immunopeptidome of healthy donors is remarkably stable throughout the year and strongly correlated between individuals with overlapping HLA types. Immunopeptides originating from diverse tissues, including the brain, are proportionately represented. We conclude that sHLAs are a promising avenue for immunology and potentially for precision oncology.

Current Challenges and Future Directions in Peptidomics

The field of peptidomics has been under development since its start more than 20 years ago. In this chapter we provide a personal outlook for future directions in this field. The applications of peptidomics technologies are spreading more and more from classical research of peptide hormones and neuropeptides towards commercial applications in plant and food-science. Many clinical applications have been developed to analyze the complexity of biofluids, which are being addressed with new instrumentation, automization, and data processing. Additionally, the newly developed field of immunopeptidomics is showing promise for cancer therapies. In conclusion, peptidomics will continue delivering important information in classical fields like neuropeptides and peptide hormones, benefiting from improvements in state-of-the-art technologies. Moreover, new directions of research such as immunopeptidomics will further complement classical omics technologies and may become routine clinical procedures. Taken together, discoveries of new substances, networks, and applications of peptides can be expected in different disciplines.

Peptide-based vaccine for cancer therapies

Different strategies based on peptides are available for cancer treatment, in particular to counter-act the progression of tumor growth and disease relapse. In the last decade, in the context of therapeutic strategies against cancer, peptide-based vaccines have been evaluated in different tumor models. The peptides selected for cancer vaccine development can be classified in two main type: tumor-associated antigens (TAAs) and tumor-specific antigens (TSAs), which are captured, internalized, processed and presented by antigen-presenting cells (APCs) to cell-mediated immunity. Peptides loaded onto MHC class I are recognized by a specific TCR of CD8+ T cells, which are activated to exert their cytotoxic activity against tumor cells presenting the same peptide-MHC-I complex. This process is defined as active immunotherapy as the host's immune system is either de novo activated or restimulated to mount an effective, tumor-specific immune reaction that may ultimately lead to tu-mor regression. However, while the preclinical data have frequently shown encouraging results, therapeutic cancer vaccines clinical trials, including those based on peptides have not provided satisfactory data to date. The limited efficacy of peptide-based cancer vaccines is the consequence of several factors, including the identification of specific target tumor antigens, the limited immunogenicity of peptides and the highly immunosuppressive tumor microenvironment (TME). An effective cancer vaccine can be developed only by addressing all such different aspects. The present review describes the state of the art for each of such factors.

A microfluidics-enabled automated workflow of sample preparation for MS-based immunopeptidomics

Mass spectrometry (MS)-based immunopeptidomics is an attractive antigen discovery method with growing clinical implications. However, the current experimental approach to extract HLA-restricted peptides requires a bulky sample source, which remains a challenge for obtaining clinical specimens. We present an innovative workflow that requires a low sample volume, which streamlines the immunoaffinity purification (IP) and C18 peptide cleanup on a single microfluidics platform with automated liquid handling and minimal sample transfers, resulting in higher assay sensitivity. We also demonstrate how the state-of-the-art data-independent acquisition (DIA) method further enhances the depth of tandem MS spectra-based peptide sequencing. Consequently, over 4,000 and 5,000 HLA-I-restricted peptides were identified from as few as 0.2 million RA957 cells and a melanoma tissue of merely 5 mg, respectively. We also identified multiple immunogenic tumor-associated antigens and hundreds of peptides derived from non-canonical protein sources. This workflow represents a powerful tool for identifying the immunopeptidome of sparse samples.

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.

The impact of immunopeptidomics: From basic research to clinical implementation

The immunopeptidome is the set of peptides presented by the major histocompatibility complex (MHC) molecules, in humans also known as the human leukocyte antigen (HLA), on the surface of cells that mediate T-cell immunosurveillance. The immunopeptidome is a sampling of the cellular proteome and hence it contains information about the health state of cells. The peptide repertoire is influenced by intra- and extra-cellular perturbations - such as in the case of drug exposure, infection, or oncogenic transformation. Immunopeptidomics is the bioanalytical method by which the presented peptides are extracted from biological samples and analyzed by high-performance liquid chromatography coupled to tandem mass spectrometry (MS), resulting in a deep qualitative and quantitative snapshot of the immunopeptidome. In this review, we discuss published immunopeptidomics studies from recent years, grouped into three main domains: i) basic, ii) pre-clinical and iii) clinical research and applications. We review selected fundamental immunopeptidomics studies on the antigen processing and presentation machinery, on HLA restriction and studies that advanced our understanding of various diseases, and how exploration of the antigenic landscape allowed immune targeting at the pre-clinical stage, paving the way to pioneering exploratory clinical trials where immunopeptidomics is directly implemented in the conception of innovative treatments for cancer patients.

Proteomic identification of MHC class I-associated peptidome derived from non-obese diabetic mouse thymus and pancreas

The peptides repertoire presented to CD8⁺ T cells by major histocompatibility complex (MHC) class I molecules is referred to as the MHC I-associated peptidome (MIP), which regulates thymus development, peripheral survival and function during lifetime of CD8⁺ T cells. Type 1 diabetes (T1D) is an organ-specific autoimmune disease caused by pancreatic β cells destruction mediated primarily by autoreactive CD8⁺ T cells. Non-obese diabetic (NOD) mouse is an important animal model of T1D. Here, we deeply analyzed the MIP derived from NOD mice thymus and pancreas, and demonstrated that the thymus MIP source proteins partially shared with the MIP source proteins derived from NOD mice pancreas and β cell line. One H-2Kd restricted peptide SLC35B1_26-34 which was shared by MIP derived from both NOD mice pancreatic tissues and islet β-cell line, but absent in MIP from NOD thymus tissues, showed ability to stimulate IFN-γ secretion and proliferation of NOD mice splenic CD8⁺ T cells. The global view of the MHC I-associated self-peptides repertoire in the thymus and pancreas of NOD mice may serve as a biological reference to identify potential autoantigens targeted by autoreactive CD8⁺ T cells in T1D. Data are available via ProteomeXchange with identifier PXD031966. SIGNIFICANCE: The peptides repertoire presented to CD8⁺ T cells by major histocompatibility complex (MHC) class I molecules is referred to as the MHC I-associated peptidome (MIP). The MIP presented by thymic antigen presenting cells (APCs) is crucial for shaping CD8⁺ T cell repertoire and self-tolerance, while the MIP presented by peripheral tissues and organs is not only involved in maintaining periphery CD8⁺ T cell survival and homeostasis, but also mediates immune surveillance and autoimmune responses of CD8⁺ T cells under pathological conditions. Type 1 diabetes (T1D) is an organ-specific autoimmune disease caused by the destruction of pancreatic β cells, mediated primarily by autoreactive CD8⁺ T cells. Non-obese diabetic (NOD) mouse is one of important animal models of spontaneous autoimmune diabetes that shares several key features with human T1D. The global view of the MHC I-associated self-peptides repertoire in the thymus and pancreas of NOD mice may serve as a good biological reference to identify potential autoantigens targeted by autoreactive CD8⁺ T cells in T1D. It has great significance for further clarifying the immune recognition and effect mechanism of autoreactive CD8⁺ T cells in the pathogenesis of T1D, and then developing antigen-specific immune intervention strategies.

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.

Physical and in silico immunopeptidomic profiling of a cancer antigen prostatic acid phosphatase reveals targets enabling TCR isolation

Tissue-specific antigens can serve as targets for adoptive T cell transfer-based cancer immunotherapy. Recognition of tumor by T cells is mediated by interaction between peptide-major histocompatibility complexes (pMHCs) and T cell receptors (TCRs). Revealing the identity of peptides bound to MHC is critical in discovering cognate TCRs and predicting potential toxicity. We performed multimodal immunopeptidomic analyses for human prostatic acid phosphatase (PAP), a well-recognized tissue antigen. Three physical methods, including mild acid elution, coimmunoprecipitation, and secreted MHC precipitation, were used to capture a thorough signature of PAP on HLA-A*02:01. Eleven PAP peptides that are potentially A*02:01-restricted were identified, including five predicted strong binders by NetMHCpan 4.0. Peripheral blood mononuclear cells (PBMCs) from more than 20 healthy donors were screened with the PAP peptides. Seven cognate TCRs were isolated which can recognize three distinct epitopes when expressed in PBMCs. One TCR shows reactivity toward cell lines expressing both full-length PAP and HLA-A*02:01. Our results show that a combined multimodal immunopeptidomic approach is productive in revealing target peptides and defining the cloned TCR sequences reactive with prostatic acid phosphatase epitopes.

T Cell Epitope Discovery in the Context of Distinct and Unique Indigenous HLA Profiles

CD8⁺ T cells are a pivotal part of the immune response to viruses, playing a key role in disease outcome and providing long-lasting immunity to conserved pathogen epitopes. Understanding CD8⁺ T cell immunity in humans is complex due to CD8⁺ T cell restriction by highly polymorphic Human Leukocyte Antigen (HLA) proteins, requiring T cell epitopes to be defined for different HLA allotypes across different ethnicities. Here we evaluate strategies that have been developed to facilitate epitope identification and study immunogenic T cell responses. We describe an immunopeptidomics approach to sequence HLA-bound peptides presented on virus-infected cells by liquid chromatography with tandem mass spectrometry (LC-MS/MS). Using antigen presenting cell lines that stably express the HLA alleles characteristic of Indigenous Australians, this approach has been successfully used to comprehensively identify influenza-specific CD8⁺ T cell epitopes restricted by HLA allotypes predominant in Indigenous Australians, including HLA-A*24:02 and HLA-A*11:01. This is an essential step in ensuring high vaccine coverage and efficacy in Indigenous populations globally, known to be at high risk from influenza disease and other respiratory infections.

Soluble HLA peptidome of pleural effusions is a valuable source for tumor antigens

Background

Soluble human leucocyte antigen (sHLA) molecules, released into the plasma, carry their original peptide cargo and provide insight into the protein synthesis and degradation schemes of their source cells and tissues. Other body fluids, such as pleural effusions, may also contain sHLA-peptide complexes, and can potentially serve as a source of tumor antigens since these fluids are drained from the tumor microenvironment. We explored this possibility by developing a methodology for purifying and analyzing large pleural effusion sHLA class I peptidomes of patients with malignancies or benign diseases.

Methods

Cleared pleural fluids, cell pellets present in the pleural effusions, and the primary tumor cells cultured from cancer patients’ effusions, were used for immunoaffinity purification of the HLA molecules. The recovered HLA peptides were analyzed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) and the resulting LC-MS/MS data were analyzed with the MaxQuant software tool. Selected tumor antigen peptides were tested for their immunogenicity potential with donor peripheral blood mononuclear cells (PBMCs) in an in vitro assay.

Results

Mass spectrometry analysis of the pleural effusions revealed 39,669 peptides attributable to 11,305 source proteins. The majority of peptides identified from the pleural effusions were defined as HLA ligands that fit the patients’ HLA consensus sequence motifs. The membranal and soluble HLA peptidomes of each individual patient correlated to each other. Additionally, soluble HLA peptidomes from the same patient, obtained at different visits to the clinic, were highly similar. Compared with benign effusions, the soluble HLA peptidomes of malignant pleural effusions were larger and included HLA peptides derived from known tumor-associated antigens, including cancer/testis antigens, lung-related proteins, and vascular endothelial growth factor pathway proteins. Selected tumor-associated antigens that were identified by the immunopeptidomics were able to successfully prime CD8⁺ T cells.

Conclusions

Pleural effusions contain sHLA-peptide complexes, and the pleural effusion HLA peptidome of patients with malignant tumors can serve as a rich source of biomarkers for tumor diagnosis and potential candidates for personalized immunotherapy.

Branca RM, Lehtiö J, Sikanen TM, Cerullo V. PeptiCHIP: A Microfluidic Platform for Tumor Antigen Landscape Identification

Identification of HLA class I ligands from the tumor surface (ligandome or immunopeptidome) is essential for designing T-cell mediated cancer therapeutic approaches. However, the sensitivity of the process for isolating MHC-I restricted tumor-specific peptides has been the major limiting factor for reliable tumor antigen characterization, making clear the need for technical improvement. Here, we describe our work from the fabrication and development of a microfluidic-based chip (PeptiCHIP) and its use to identify and characterize tumor-specific ligands on clinically relevant human samples. Specifically, we assessed the potential of immobilizing a pan-HLA antibody on solid surfaces via well-characterized streptavidin-biotin chemistry, overcoming the limitations of the cross-linking chemistry used to prepare the affinity matrix with the desired antibodies in the immunopeptidomics workflow. Furthermore, to address the restrictions related to the handling and the limited availability of tumor samples, we further developed the concept toward the implementation of a microfluidic through-flow system. Thus, the biotinylated pan-HLA antibody was immobilized on streptavidin-functionalized surfaces, and immune-affinity purification (IP) was carried out on customized microfluidic pillar arrays made of thiol-ene polymer. Compared to the standard methods reported in the field, our methodology reduces the amount of antibody and the time required for peptide isolation. In this work, we carefully examined the specificity and robustness of our customized technology for immunopeptidomics workflows. We tested this platform by immunopurifying HLA-I complexes from 1 × 10⁶ cells both in a widely studied B-cell line and in patients-derived ex vivo cell cultures, instead of 5 × 10⁸ cells as required in the current technology. After the final elution in mild acid, HLA-I-presented peptides were identified by tandem mass spectrometry and further investigated by in vitro methods. These results highlight the potential to exploit microfluidics-based strategies in immunopeptidomics platforms and in personalized immunopeptidome analysis from cells isolated from individual tumor biopsies to design tailored cancer therapeutic vaccines. Moreover, the possibility to integrate multiple identical units on a single chip further improves the throughput and multiplexing of these assays with a view to clinical needs.

Deregulation of HLA-I in cancer and its central importance for immunotherapy

It is now well accepted that many tumors undergo a process of clonal selection which means that tumor antigens arising at various stages of tumor progression are likely to be represented in just a subset of tumor cells. This process is thought to be driven by constant immunosurveillance which applies selective pressure by eliminating tumor cells expressing antigens that are recognized by T cells. It is becoming increasingly clear that the same selective pressure may also select for tumor cells that evade immune detection by acquiring deficiencies in their human leucocyte antigen (HLA) presentation pathways, allowing important tumor antigens to persist within cells undetected by the immune system. Deficiencies in antigen presentation pathway can arise by a variety of mechanisms, including genetic and epigenetic changes, and functional antigen presentation is a hard phenomenon to assess using our standard analytical techniques. Nevertheless, it is likely to have profound clinical significance and could well define whether an individual patient will respond to a particular type of therapy or not. In this review we consider the mechanisms by which HLA function may be lost in clinical disease, we assess the implications for current immunotherapy approaches using checkpoint inhibitors and examine the prognostic impact of HLA loss demonstrated in clinical trials so far. Finally, we propose strategies that might be explored for possible patient stratification.

Deciphering Human Leukocyte Antigen Susceptibility Maps From Immunopeptidomics Characterization in Oncology and Infections

Genetic variability across the three major histocompatibility complex (MHC) class I genes (human leukocyte antigen [HLA] A, B, and C) may affect susceptibility to many diseases such as cancer, auto-immune or infectious diseases. Individual genetic variation may help to explain different immune responses to microorganisms across a population. HLA typing can be fast and inexpensive; however, deciphering peptides loaded on MHC-I and II which are presented to T cells, require the design and development of high-sensitivity methodological approaches and subsequently databases. Hence, these novel strategies and databases could help in the generation of vaccines using these potential immunogenic peptides and in identifying high-risk HLA types to be prioritized for vaccination programs. Herein, the recent developments and approaches, in this field, focusing on the identification of immunogenic peptides have been reviewed and the next steps to promote their translation into biomedical and clinical practice are discussed.

Antigenic Essence: Upgrade of Cellular Cancer Vaccines

Simple Summary

Early cancer vaccines include whole-cell formulations, which operate on the principle that you should vaccinate with what you want to develop protection against. Such vaccines have been widely tested in various cancers and their advantages described but have not yet managed to pass clinical trials. Antigenic essence technology offers the possibility to revitalize the field of whole-cell-based vaccination, as the essence comprises the entire diversity of native cellular antigens. At the same time, the technology allows for precise control and purposeful change of essence composition as well as purification of essence from ballast cellular substances and also addresses issues of major histocompatibility complex restriction. Antigenic essence technology makes it possible to update many cellular vaccines that have already been developed, as well as to develop new ones, therefore introducing a new direction for anticancer vaccination research.

Abstract

The development of anticancer immunotherapy is characterized by several approaches, the most recognized of which include cellular vaccines, tumor-associated antigens (TAAs), neoantigens, and chimeric antigen receptor T cells (CAR-T). This paper presents antigenic essence technology as an effective means for the production of new antigen compositions for anticancer vaccination. This technology is developed via proteomics, cell culture technology, and immunological assays. In terms of vaccine development, it does not fit into any of the above-noted approaches and can be considered a new direction. Here we review the development of this technology, its main characteristics, comparison with existing approaches, and the features that distinguish it as a novel approach to anticancer vaccination. This review will also highlight the benefits of this technology over other approaches, such as the ability to control composition, optimize immunogenicity and similarity to target cells, and evade major histocompatibility complex restriction. The first antigenic essence products, presented under the SANTAVAC brand, are also described.

The Peptide Vaccine of the Future

The approach of peptide-based anticancer vaccination has proven the ability to induce cancer-specific immune responses in multiple studies for various cancer entities. However, clinical responses remain so far limited to single patients and broad clinical applicability was not achieved. Therefore, further efforts are required to improve peptide vaccination in order to integrate this low-side-effect therapy into the clinical routine of cancer therapy. To design clinically effective peptide vaccines in the future, different issues have to be addressed and optimized comprising antigen target selection as well as choice of optimal adjuvants and vaccination schedules. Furthermore, the combination of peptide-based vaccines with other immuno- and molecular targeted therapies as well as the development of predictive biomarkers could further improve efficacy. In this review, current approaches in the development of peptide-based vaccines and critical implications for optimal vaccine design are discussed.

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.

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.

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.

Mild Acid Elution and MHC Immunoaffinity Chromatography Reveal Similar Albeit Not Identical Profiles of the HLA Class I Immunopeptidome

To understand and treat immunology-related diseases, a comprehensive, unbiased characterization of major histocompatibility complex (MHC) peptide ligands is of key importance. Preceding the analysis by mass spectrometry, MHC class I peptide ligands are typically isolated by MHC immunoaffinity chromatography (MHC-IAC) and less often by mild acid elution (MAE). MAE may provide a cheap alternative to MHC-IAC for suspension cells but has been hampered by the high number of contaminating, MHC-unrelated peptides. Here, we optimized MAE, yielding MHC peptide ligand purities of more than 80%. When compared with MHC-IAC, obtained peptides were similar in numbers, identities, and to a large extent intensities, while the percentage of cysteinylated peptides was 5 times higher in MAE. The latter benefitted the discovery of MHC-allotype-specific, distinct cysteinylation frequencies at individual positions of MHC peptide ligands. MAE revealed many MHC ligands with unmodified, N-terminal cysteine residues which get lost in MHC-IAC workflows. The results support the idea that MAE might be particularly valuable for the high-confidence analysis of post-translational modifications by avoiding the exposure of the investigated peptides to enzymes and reactive molecules in the cell lysate. Our improved and carefully documented MAE workflow represents a high-quality, cost-effective alternative to MHC-IAC for suspension cells.

Cancer systems immunology

Tumor immunology is undergoing a renaissance due to the recent profound clinical successes of tumor immunotherapy. These advances have coincided with an exponential growth in the development of -omics technologies. Armed with these technologies and their associated computational and modeling toolsets, systems biologists have turned their attention to tumor immunology in an effort to understand the precise nature and consequences of interactions between tumors and the immune system. Such interactions are inherently multivariate, spanning multiple time and size scales, cell types, and organ systems, rendering systems biology approaches particularly amenable to their interrogation. While in its infancy, the field of 'Cancer Systems Immunology' has already influenced our understanding of tumor immunology and immunotherapy. As the field matures, studies will move beyond descriptive characterizations toward functional investigations of the emergent behavior that govern tumor-immune responses. Thus, Cancer Systems Immunology holds incredible promise to advance our ability to fight this disease.

Nanomedicine and Onco-Immunotherapy: From the Bench to Bedside to Biomarkers

The broad relationship between the immune system and cancer is opening a new hallmark to explore for nanomedicine. Here, all the common and synergy points between both areas are reviewed and described, and the recent approaches which show the progress from the bench to the beside to biomarkers developed in nanomedicine and onco-immunotherapy.

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.

Ulcerative Colitis in Hematological Malignancies: Paraneoplastic Manifestation or Coincidental Bystander?

Evidence of coexistence of diverse hematological malignancies—lymphoma, leukemia, multiple myeloma, and myelodysplastic syndromes—and either ulcerative colitis or Crohn's disease can be found in the literature. However, a more “systemic” effort to reach further and examine the potential of either one as paraneoplastic manifestation has not been performed. Based on these, three cases of ulcerative colitis manifesting before, simultaneously, and after the onset of different hematological malignancies are presented and critically evaluated.

Streamlined selection of cancer antigens for vaccine development through integrative multi-omics and high-content cell imaging

Identification of tumor antigens that induce cytotoxic T lymphocytes (CTLs) is crucial for cancer-vaccine development. Despite their predictive ability, current algorithmic approaches and human leukocyte antigen (HLA)-peptidomic analysis allow limited selectivity. Here, we optimized a method to rapidly screen and identify highly immunogenic epitopes that trigger CTL responses. We used a combined application of this method involving immune-specific signature analysis and HLA-associated peptidomics using samples from six patients with triple-negative breast cancer (TNBC) in order to select immunogenic HLA epitopes for in vitro testing. Additionally, we applied high-throughput imaging at the single-cell level in order to confirm the immunoreactivity of the selected peptides. The results indicated that this method enabled identification of promising CTL peptides capable of inducing antitumor immunity. This platform combining high-resolution computational analysis, HLA-peptidomics, and high-throughput immunogenicity testing allowed rapid and robust identification of highly immunogenic epitopes and represents a powerful technique for cancer-vaccine development.

Monitoring Immune Responses in Neuroblastoma Patients during Therapy

Neuroblastoma (NBL) is the most common extracranial solid tumor in childhood. Despite intense treatment, children with this high-risk disease have a poor prognosis. Immunotherapy showed a significant improvement in event-free survival in high-risk NBL patients receiving chimeric anti-GD2 in combination with cytokines and isotretinoin after myeloablative consolidation therapy. However, response to immunotherapy varies widely, and often therapy is stopped due to severe toxicities. Objective markers that help to predict which patients will respond or develop toxicity to a certain treatment are lacking. Immunotherapy guided via immune monitoring protocols will help to identify responders as early as possible, to decipher the immune response at play, and to adjust or develop new treatment strategies. In this review, we summarize recent studies investigating frequency and phenotype of immune cells in NBL patients prior and during current treatment protocols and highlight how these findings are related to clinical outcome. In addition, we discuss potential targets to improve immunogenicity and strategies that may help to improve therapy efficacy. We conclude that immune monitoring during therapy of NBL patients is essential to identify predictive biomarkers to guide patients towards effective treatment, with limited toxicities and optimal quality of life.

Analysis of Secondary Structure Biases in Naturally Presented HLA-I Ligands

Recent clinical developments in antitumor immunotherapy involving T-cell related therapeutics have led to a renewed interest for human leukocyte antigen class I (HLA-I) binding peptides, given their potential use as peptide vaccines. Databases of HLA-I binding peptides hold therefore information on therapeutic targets essential for understanding immunity. In this work, we use in depth and accurate HLA-I peptidomics datasets determined by mass-spectrometry (MS) and analyze properties of the HLA-I binding peptides with structure-based computational approaches. HLA-I binding peptides are studied grouping all alleles together or in allotype-specific contexts. We capitalize on the increasing number of structurally determined proteins to (1) map the 3D structure of HLA-I binding peptides into the source proteins for analyzing their secondary structure and solvent accessibility in the protein context, and (2) search for potential differences between these properties in HLA-I binding peptides and in a reference dataset of HLA-I motif-like peptides. This is performed by an in-house developed heuristic search that considers peptides across all the human proteome and converges to a collection of peptides that exhibit exactly the same motif as the HLA-I peptides. Our results, based on 9-mers matched to protein 3D structures, clearly show enriched sampling for HLA-I presentation of helical fragments in the source proteins. This enrichment is significant, as compared to 9-mer HLA-I motif-like peptides, and is not entirely explained by the helical propensity of the preferred residues in the HLA-I motifs. We give possible hypothesis for the secondary structure biases observed in HLA-I peptides. This contribution is of potential interest for researchers working in the field of antigen presentation and proteolysis. This knowledge refines the understanding of the rules governing antigen presentation and could be added to the parameters of the current peptide-MHC class I binding predictors to increase their antigen predictive ability.

Direct Detection and Quantification of Neoantigens

Many immunotherapeutic approaches under development rely on T-cell recognition of cancer-derived peptides bound to human leukocyte antigen molecules on the cell surface. Direct experimental demonstration that such peptides are processed and bound is currently challenging. Here, we describe a method that meets this challenge. The method entailed an optimized immunoprecipitation protocol coupled with two-dimensional chromatography and mass spectrometry. The ability to detect and quantify minute amounts of predefined antigens should be useful both for basic research in tumor immunology and for the development of rationally designed cancer vaccines.

Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data

The proteomic analysis of human blood and blood-derived products (e.g., plasma) offers an attractive avenue to translate research progress from the laboratory into the clinic. However, due to its unique protein composition, performing proteomics assays with plasma is challenging. Plasma proteomics has regained interest due to recent technological advances, but challenges imposed by both complications inherent to studying human biology (e.g., interindividual variability) and analysis of biospecimens (e.g., sample variability), as well as technological limitations remain. As part of the Human Proteome Project (HPP), the Human Plasma Proteome Project (HPPP) brings together key aspects of the plasma proteomics pipeline. Here, we provide considerations and recommendations concerning study design, plasma collection, quality metrics, plasma processing workflows, mass spectrometry (MS) data acquisition, data processing, and bioinformatic analysis. With exciting opportunities in studying human health and disease though this plasma proteomics pipeline, a more informed analysis of human plasma will accelerate interest while enhancing possibilities for the incorporation of proteomics-scaled assays into clinical practice.

UVB-Induced Tumor Heterogeneity Diminishes Immune Response in Melanoma

Although clonal neo-antigen burden is associated with improved response to immune therapy, the functional basis for this remains unclear. Here we study this question in a novel controlled mouse melanoma model that enables us to explore the effects of intra-tumor heterogeneity (ITH) on tumor aggressiveness and immunity independent of tumor mutational burden. Induction of UVB-derived mutations yields highly aggressive tumors with decreased anti-tumor activity. However, single-cell-derived tumors with reduced ITH are swiftly rejected. Their rejection is accompanied by increased T cell reactivity and a less suppressive microenvironment. Using phylogenetic analyses and mixing experiments of single-cell clones, we dissect two characteristics of ITH: the number of clones forming the tumor and their clonal diversity. Our analysis of melanoma patient tumor data recapitulates our results in terms of overall survival and response to immune checkpoint therapy. These findings highlight the importance of clonal mutations in robust immune surveillance and the need to quantify patient ITH to determine the response to checkpoint blockade.

Soluble HLA in the Aqueous Humour of Uveal Melanoma Is Associated with Unfavourable Tumour Characteristics

A high HLA expression in uveal melanoma (UM) is part of the prognostically unfavorable inflammatory phenotype. We wondered whether the presence of soluble HLA (sHLA) in the aqueous humour is associated with clinical, histopathological or genetic tumour characteristics, and represents tumour HLA expression and intratumoural inflammation. Aqueous humour from 108 UM patients was analysed for the presence of sHLA, using a Luminex assay specific for HLA Class I. Clinical and genetic parameters were compared between sHLA-positive and negative eyes. A qPCR analysis was performed on tumour tissue using a Fluidigm assay. In 19/108 UM-containing eyes, the sHLA level in the aqueous was above the detection limit. Tumours in sHLA-positive eyes were significantly larger, more frequently involved the ciliary body, and more often showed monosomy 3, gain of chromosome 8q and loss of BAP1 staining. Melanoma-related survival was worse in patients with sHLA-positive aqueous humour. sHLA in the aqueous did not represent the tumour's HLA expression and did not relate to immune cell infiltration in the tumour. We conclude that UM-containing eyes may contain sHLA in the aqueous humour, where it is a prognostically-unfavourable sign and may influence local immune responses.

Identification of Tumor Antigens Among the HLA Peptidomes of Glioblastoma Tumors and Plasma

Glioblastoma multiforme (GBM) is the most aggressive brain tumor with poor prognosis to most patients. Immunotherapy of GBM is a potentially beneficial treatment option, whose optimal implementation may depend on familiarity with tumor specific antigens, presented as HLA peptides by the GBM cells. Further, early detection of GBM, such as by a routine blood test, may improve survival, even with the current treatment modalities. This study includes large-scale analyses of the HLA peptidome (immunopeptidome) of the plasma-soluble HLA molecules (sHLA) of 142 plasma samples, and the membranal HLA of GBM tumors of 10 of these patients' tumor samples. Tumor samples were fresh-frozen immediately after surgery and the plasma samples were collected before, and at multiple visits after surgery. In total, this HLA peptidome analysis involved 52 different HLA allotypes and resulted in the identification of more than 35,000 different HLA peptides. Strong correlations were observed in the signal intensities and in the repertoires of identified peptides between the tumors and plasma-soluble HLA peptidomes of the individual patients, whereas low correlations were observed between these HLA peptidomes and the tumors' proteomes. HLA peptides derived from Cancer/Testis Antigens (CTAs) were selected based on their presence among the HLA peptidomes of the patients and absence of expression of their source genes from any healthy and essential human tissues, except from immune-privileged sites. Additionally, peptides were selected as potential biomarkers if their levels in the plasma-sHLA peptidome were significantly reduced after the removal of tumor mass. The CTAs identified among the analyzed HLA peptidomes provide new opportunities for personalized immunotherapy and for early diagnosis of GBM.

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

Peptide antigens bound to molecules encoded by the major histocompatibility complex (MHC) and presented on the cell surface form the targets of T lymphocytes. This critical arm of the adaptive immune system facilitates the eradication of pathogen-infected and cancerous cells, as well as the production of antibodies. Methods to identify these peptide antigens are critical to the development of new vaccines, for which the goal is the generation of effective adaptive immune responses and long-lasting immune memory. Here, we describe a robust protocol for the identification of MHC-bound peptides from cell lines and tissues, using nano-ultra-performance liquid chromatography coupled to high-resolution mass spectrometry (nUPLC-MS/MS) and recent improvements in methods for isolation and characterization of these peptides. The protocol starts with the immunoaffinity capture of naturally processed MHC-peptide complexes. The peptides dissociate from the class I human leukocyte antigens (HLAs) upon acid denaturation. This peptide cargo is then extracted and separated into fractions by HPLC, and the peptides in these fractions are identified using nUPLC-MS/MS. With this protocol, several thousand peptides can be identified from a wide variety of cell types, including cancerous and infected cells and those from tissues, with a turnaround time of 2-3 d.

Keratin 8 is a potential self-antigen in the coronary artery disease immunopeptidome: A translational approach

Background

Inflammation is an important risk factor in atherosclerosis, the underlying cause of coronary artery disease (CAD). Unresolved inflammation may result in maladaptive immune responses and lead to immune reactivity to self-antigens. We hypothesized that inflammation in CAD patients would manifest in immune reactivity to self-antigens detectable in soluble HLA-I/peptide complexes in the plasma.

Methods

Soluble HLA-I/peptide complexes were immuno-precipitated from plasma of male acute coronary syndrome (ACS) patients or age-matched controls and eluted peptides were subjected to mass spectrometry to generate the immunopeptidome. Self-peptides were ranked according to frequency and signal intensity, then mouse homologs of selected peptides were used to test immunologic recall in spleens of male apoE-/- mice fed either normal chow or high fat diet. The peptide detected with highest frequency in patient plasma samples and provoked T cell responses in mouse studies was selected for use as a self-antigen to stimulate CAD patient peripheral blood mononuclear cells (PBMCs).

Results

The immunopeptidome profile identified self-peptides unique to the CAD patients. The mouse homologs tested showed immune responses in apoE-/- mice. Keratin 8 was selected for further study in patient PBMCs which elicited T Effector cell responses in CAD patients compared to controls, associated with reduced PD-1 mRNA expression.

Conclusion

An immunopeptidomic strategy to search for self-antigens potentially involved in CAD identified Keratin 8. Self-reactive immune response to Keratin 8 may be an important factor in the inflammatory response in CAD.

High-Throughput, Fast, and Sensitive Immunopeptidomics Sample Processing for Mass Spectrometry

Comprehensive knowledge of the HLA class I and class II peptides presented to T cells is crucial for designing innovative therapeutics against cancer and other diseases. So far, methodologies for recovery of HLA class I and II peptides for subsequent mass spectrometry-based analysis have been a major limitation. In this chapter we describe a detailed protocol for a high-throughput, reproducible, and sensitive immunoaffinity-purification of HLA-I and HLA-II peptides from up to 96 samples in a plate format, suitable for tissue samples and cell lines. Our methodology reduces sample handling, has a competitive peptide yield, and can be completed within 5 h. This simplified pipeline is applicable for basic and clinical applications.

Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes

A number of machine learning-based predictors have been developed for identifying immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II binding affinities. Rationally selecting the most appropriate tool has been complicated by the evolving training data and machine learning methods. Despite the recent advances made in generating high-quality MHC-eluted, naturally processed ligandome, the reliability of new predictors on these epitopes has yet to be evaluated. This study reports the latest benchmarking on an extensive set of MHC-binding predictors by using newly available, untested data of both synthetic and naturally processed epitopes. 32 human leukocyte antigen (HLA) class I and 24 HLA class II alleles are included in the blind test set. Artificial neural network (ANN)-based approaches demonstrated better performance than regression-based machine learning and structural modeling. Among the 18 predictors benchmarked, ANN-based mhcflurry and nn_align perform the best for MHC class I 9-mer and class II 15-mer predictions, respectively, on binding/non-binding classification (Area Under Curves = 0.911). NetMHCpan4 also demonstrated comparable predictive power. Our customization of mhcflurry to a pan-HLA predictor has achieved similar accuracy to NetMHCpan. The overall accuracy of these methods are comparable between 9-mer and 10-mer testing data. However, the top methods deliver low correlations between the predicted versus the experimental affinities for strong MHC binders. When used on naturally processed MHC-ligands, tools that have been trained on elution data (NetMHCpan4 and MixMHCpred) shows better accuracy than pure binding affinity predictor. The variability of false prediction rate is considerable among HLA types and datasets. Finally, structure-based predictor of Rosetta FlexPepDock is less optimal compared to the machine learning approaches. With our benchmarking of MHC-binding and MHC-elution predictors using a comprehensive metrics, a unbiased view for establishing best practice of T-cell epitope predictions is presented, facilitating future development of methods in immunogenomics.

Identification of Tumor Antigens Among the HLA Peptidomes of Glioblastoma Tumors and Plasma

Glioblastoma multiforme (GBM) is the most aggressive brain tumor with poor prognosis to most patients. Immunotherapy of GBM is a potentially beneficial treatment option, whose optimal implementation may depend on familiarity with tumor specific antigens, presented as HLA peptides by the GBM cells. Furthermore, early detection of GBM, such as by a routine blood test, may improve survival, even with the current treatment modalities. This study includes large-scale analyses of the HLA peptidome (immunopeptidome) of the plasma-soluble HLA molecules (sHLA) of 142 plasma samples, and the membranal HLA of GBM tumors of 10 of these patients' tumor samples. Tumor samples were fresh-frozen immediately after surgery and the plasma samples were collected before, and at multiple visits after surgery. In total, this HLA peptidome analysis involved 52 different HLA allotypes and resulted in the identification of more than 35,000 different HLA peptides. Strong correlations were observed in the signal intensities and in the repertoires of identified peptides between the tumors and plasma-soluble HLA peptidomes of the individual patients, whereas low correlations were observed between these HLA peptidomes and the tumors' proteomes. HLA peptides derived from Cancer/Testis Antigens (CTAs) were selected based on their presence among the HLA peptidomes of the patients and absence of expression of their source genes from any healthy and essential human tissues, except from immune-privileged sites. Additionally, peptides were selected as potential biomarkers if their levels in the plasma-sHLA peptidome were significantly reduced after the removal of tumor mass. The CTAs identified among the analyzed HLA peptidomes provide new opportunities for personalized immunotherapy and for early diagnosis of GBM.

A tissue-based draft map of the murine MHC class I immunopeptidome

The large array of peptides presented to CD8+ T cells by major histocompatibility complex (MHC) class I molecules is referred to as the MHC class I immunopeptidome. Although the MHC class I immunopeptidome is ubiquitous in mammals and represents a critical component of the immune system, very little is known, in any species, about its composition across most tissues and organs in vivo. We applied mass spectrometry (MS) technologies to draft the first tissue-based atlas of the murine MHC class I immunopeptidome in health. Peptides were extracted from 19 normal tissues from C57BL/6 mice and prepared for MS injections, resulting in a total number of 28,448 high-confidence H2D^b/K^b-associated peptides identified and annotated in the atlas. This atlas provides initial qualitative data to explore the tissue-specificity of the immunopeptidome and serves as a guide to identify potential tumor-associated antigens from various cancer models. Our data were shared via PRIDE (PXD008733), SysteMHC Atlas (SYSMHC00018) and SWATH Atlas. We anticipate that this unique dataset will be expanded in the future and will find wide applications in basic and translational immunology.

The role of proteomics in the age of immunotherapies

The antigenic landscape of the adaptive immune response is determined by the peptides presented by immune cells. In recent years, a number of immune-based cancer therapies have been shown to induce remarkable clinical responses through the activation of the patient's immune system. As a result, there is a need to identify immune biomarkers capable of predicting clinical response. Recent advances in proteomics have led to considerable developments in the more comprehensive profiling of the immune response. "Immunoproteomics" utilises a rapidly increasing collection of technologies in order to identify and quantify antigenic peptides or proteins. This includes gel-based, array-based, mass spectrometry (MS), DNA-based, or computer-based (in silico) approaches. Immunoproteomics is yielding an understanding of disease and disease progression, vaccine candidates, and biomarkers to a depth not before understood. This review gives an overview of the emerging role of proteomics in improving personalisation of immunotherapy treatment.

Predicting Antigen Presentation-What Could We Learn From a Million Peptides?

Antigen presentation lies at the heart of immune recognition of infected or malignant cells. For this reason, important efforts have been made to predict which peptides are more likely to bind and be presented by the human leukocyte antigen (HLA) complex at the surface of cells. These predictions have become even more important with the advent of next-generation sequencing technologies that enable researchers and clinicians to rapidly determine the sequences of pathogens (and their multiple variants) or identify non-synonymous genetic alterations in cancer cells. Here, we review recent advances in predicting HLA binding and antigen presentation in human cells. We argue that the very large amount of high-quality mass spectrometry data of eluted (mainly self) HLA ligands generated in the last few years provides unprecedented opportunities to improve our ability to predict antigen presentation and learn new properties of HLA molecules, as demonstrated in many recent studies of naturally presented HLA-I ligands. Although major challenges still lie on the road toward the ultimate goal of predicting immunogenicity, these experimental and computational developments will facilitate screening of putative epitopes, which may eventually help decipher the rules governing T cell recognition.

The Role of Mass Spectrometry and Proteogenomics in the Advancement of HLA Epitope Prediction

A challenge in developing personalized cancer immunotherapies is the prediction of putative cancer-specific antigens. Currently, predictive algorithms are used to infer binding of peptides to human leukocyte antigen (HLA) heterodimers to aid in the selection of putative epitope targets. One drawback of current epitope prediction algorithms is that they are trained on datasets containing biochemical HLA-peptide binding data that may not completely capture the rules associated with endogenous processing and presentation. The field of MS has made great improvements in instrumentation speed and sensitivity, chromatographic resolution, and proteogenomic database search strategies to facilitate the identification of HLA-ligands from a variety of cell types and tumor tissues. As such, these advances have enabled MS profiling of HLA-binding peptides to be a tractable, orthogonal approach to lower throughput biochemical assays for generating comprehensive datasets to train epitope prediction algorithms. In this review, we will highlight the progress made in the field of HLA-ligand profiling enabled by MS and its impact on current and future epitope prediction strategies.

Mapping the tumour human leukocyte antigen (HLA) ligandome by mass spectrometry

The entirety of human leukocyte antigen (HLA)-presented peptides is referred to as the HLA ligandome of a cell or tissue, in tumours often termed immunopeptidome. Mapping the tumour immunopeptidome by mass spectrometry (MS) comprehensively views the pathophysiologically relevant antigenic signature of human malignancies. MS is an unbiased approach stringently filtering the candidates to be tested as opposed to epitope prediction algorithms. In the setting of peptide-specific immunotherapies, MS-based strategies significantly diminish the risk of lacking clinical benefit, as they yield highly enriched amounts of truly presented peptides. Early immunopeptidomic efforts were severely limited by technical sensitivity and manual spectra interpretation. The technological progress with development of orbitrap mass analysers and enhanced chromatographic performance led to vast improvements in mass accuracy, sensitivity, resolution, and speed. Concomitantly, bioinformatic tools were developed to process MS data, integrate sequencing results, and deconvolute multi-allelic datasets. This enabled the immense advancement of tumour immunopeptidomics. Studying the HLA-presented peptide repertoire bears high potential for both answering basic scientific questions and translational application. Mapping the tumour HLA ligandome has started to significantly contribute to target identification for the design of peptide-specific cancer immunotherapies in clinical trials and compassionate need treatments. In contrast to prediction algorithms, rare HLA allotypes and HLA class II can be adequately addressed when choosing MS-guided target identification platforms. Herein, we review the identification of tumour HLA ligands focusing on sources, methods, bioinformatic data analysis, translational application, and provide an outlook on future developments.

Circulating histocompatibility antigen (HLA) gene products may help differentiate benign from malignant indeterminate pulmonary lesions

BACKGROUND

This study explores the potential diagnostic utility of soluble Human Leukocyte Antigen (sHLA) molecules differentially released by lung adenocarcinoma and benign lung lesions.

METHODS

Conditioned media from the NSCLC cell lines H358 and H1703 were immunoblotted for soluble isoforms of major histocompatibility complex (MHC) class I (ABC) and II (DRB1, DMB, and DQ) antigens. Sera from 25 patients with benign and 25 patients with malignant lesions were similarly evaluated to appraise the potential diagnostic value.

RESULTS

Higher concentrations of soluble HLA class I molecules were observed in conditioned medium for the highly-invasive H1703 cell line, relative to the more indolent H358 cells. Evaluation of these markers against a cohort of 50 cases demonstrated that patients with malignant lesions possess higher levels of HLA class I and II molecules relative to those with benign lesions (p < 0.05), with exception to the primary isoform, DQA1, which was suppressed in malignancies. An analysis of biomarker performance via ROC analysis revealed promising performance (AUC > 0.75) for DMB and the 26 kDa isoform of DQ in distinguishing lesion pathology.

CONCLUSIONS

Soluble HLA molecules may have diagnostic value for early-stage NSCLC. Validation studies are currently underway using sera from a lung cancer screening cohort.

A meta-analysis of HLA peptidome composition in different hematological entities: entity-specific dividing lines and "pan-leukemia" antigens

Hematological malignancies (HM) are highly amenable targets for immunotherapeutic intervention and may be effectively treated by antigen-specific T-cell based treatment. Recent studies demonstrate that physiologically occurring anti-cancer T-cell responses in certain HM entities target broadly presented non-mutated epitopes. HLA ligands are thus implied as prime targets for broadly applicable and antigen-specific off-the-shelf compounds. With the aim of assessing the presence of common targets shared among different HM which may enable addressing a larger patient collective we conducted a meta-analysis of 83 mass spectrometry-based HLA peptidome datasets (comprising 40,361 unique peptide identifications) across four major HM (19 AML, 16 CML, 35 CLL, and 13 MM/MCL samples) and investigated similarities and differences within the HLA presented antigenic landscape. We found the cancer HLA peptidome datasets to cluster specifically along entity and lineage lines, suggesting that the immunopeptidome directly reflects the differences in the underlying (tumor-)biology. In line with these findings, we only detected a small set of entity-spanning antigens, which were predominantly characterized by low presentation frequencies within the different patient cohorts. These findings suggest that design of T-cell immunotherapies for the treatment of HM should ideally be conducted in an entity-specific fashion.

High-throughput and Sensitive Immunopeptidomics Platform Reveals Profound Interferonγ-Mediated Remodeling of the Human Leukocyte Antigen (HLA) Ligandome

Comprehensive knowledge of the human leukocyte antigen (HLA) class-I and class-II peptides presented to T-cells is crucial for designing innovative therapeutics against cancer and other diseases. However methodologies for their purification for mass-spectrometry analysis have been a major limitation. We designed a novel high-throughput, reproducible and sensitive method for sequential immuno-affinity purification of HLA-I and -II peptides from up to 96 samples in a plate format, suitable for both cell lines and tissues. Our methodology drastically reduces sample-handling and can be completed within five hours. We challenged our methodology by extracting HLA peptides from multiple replicates of tissues (n = 7) and cell lines (n = 21, 108 cells per replicate), which resulted in unprecedented depth, sensitivity and high reproducibility (Pearson correlations up to 0.98 and 0.97 for HLA-I and HLA-II). Because of the method's achieved sensitivity, even single measurements of peptides purified from 107 B-cells resulted in the identification of more than 1700 HLA-I and 2200 HLA-II peptides. We demonstrate the feasibility of performing drug-screening by using ovarian cancer cells treated with interferon gamma (IFNγ). Our analysis revealed an augmented presentation of chymotryptic-like and longer ligands associated with IFNγ induced changes of the antigen processing and presentation machinery. This straightforward method is applicable for basic and clinical applications.