The Human Immunopeptidome Project: A Roadmap to Predict and Treat Immune Diseases

The Role of Antigen Processing and Presentation in Cancer and the Efficacy of Immune Checkpoint Inhibitor Immunotherapy

Recent clinical successes of cancer immunotherapy using immune checkpoint inhibitors (ICIs) are rapidly changing the landscape of cancer treatment. Regardless of initial impressive clinical results though, the therapeutic benefit of ICIs appears to be limited to a subset of patients and tumor types. Recent analyses have revealed that the potency of ICI therapies depends on the efficient presentation of tumor-specific antigens by cancer cells and professional antigen presenting cells. Here, we review current knowledge on the role of antigen presentation in cancer. We focus on intracellular antigen processing and presentation by Major Histocompatibility class I (MHCI) molecules and how it can affect cancer immune evasion. Finally, we discuss the pharmacological tractability of manipulating intracellular antigen processing as a complementary approach to enhance tumor immunogenicity and the effectiveness of ICI immunotherapy.

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.

DeepRescore: Leveraging Deep Learning to Improve Peptide Identification in Immunopeptidomics

The identification of major histocompatibility complex (MHC)-binding peptides in mass spectrometry (MS)-based immunopeptideomics relies largely on database search engines developed for proteomics data analysis. However, because immunopeptidomics experiments do not involve enzymatic digestion at specific residues, an inflated search space leads to a high false positive rate and low sensitivity in peptide identification. In order to improve the sensitivity and reliability of peptide identification, a post-processing tool named DeepRescore is developed. DeepRescore combines peptide features derived from deep learning predictions, namely accurate retention timeand MS/MS spectra predictions, with previously used features to rescore peptide-spectrum matches. Using two public immunopeptidomics datasets, it is shown that rescoring by DeepRescore increases both the sensitivity and reliability of MHC-binding peptide and neoantigen identifications compared to existing methods. It is also shown that the performance improvement is, to a large extent, driven by the deep learning-derived features. DeepRescore is developed using NextFlow and Docker and is available at https://github.com/bzhanglab/DeepRescore.

Self-Peptidome Variation Shapes Individual Immune Responses

The relationship between human genetic variation and disease has not been fully elucidated. According to the present view on infectious diseases pathogen resistance is linked to human leukocyte antigen (HLA) class I/II variants and their individual capacity to present pathogen-derived peptides. Yet, T cell education in the thymus occurs through negative and positive selection, and both processes are controlled by a combination of HLA class I/II variants and peptides from the self. Therefore, the capacity of given HLA class I/II variants to bind pathogen-derived peptides is only one part of the selective process to generate effective immune responses. We thus propose that peptidome variation contributes to shaping T cell receptor (TCR) repertoires and hence individual immune responses, and that this variation represents inherent modulator epitopes.

TCR repertoires emerge in the thymus in each individual as T cells undergo positive and negative selection.

T cell education is controlled by the combination of HLA class I/II molecules and their peptide pools (peptidome).

HLA class I/II molecules are highly plastic in human populations but the peptidome is also a source of variation. Hence combined diversity of HLA class I/II molecules and of self-peptides shapes individual immune responses.

Self-peptide variants that affect T cell repertoires represent inherent modulator epitopes.

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.

Peptide-Spectrum Match Validation with Internal Standards (P-VIS): Internally-Controlled Validation of Mass Spectrometry-Based Peptide Identifications

Liquid chromatography-tandem mass spectrometry is an increasingly powerful tool for studying proteins in the context of disease. As technological advances in instrumentation and data analysis have enabled deeper profiling of proteomes and peptidomes, the need for a rigorous, standardized approach to validate individual peptide-spectrum matches (PSMs) has emerged. To address this need, we developed a novel and broadly applicable workflow: PSM validation with internal standards (P-VIS). In this approach, the fragmentation spectrum and chromatographic retention time of a peptide within a biological sample are compared with those of a synthetic version of the putative peptide sequence match. Similarity measurements obtained for a panel of internal standard peptides are then used to calculate a prediction interval for valid matches. If the observed degree of similarity between the biological and the synthetic peptide falls within this prediction interval, then the match is considered valid. P-VIS enables systematic and objective assessment of the validity of individual PSMs, providing a measurable degree of confidence when identifying peptides by mass spectrometry.

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.

The Origin and Immune Recognition of Tumor-Specific Antigens

The dominant paradigm holds that spontaneous and therapeutically induced anti-tumor responses are mediated mainly by CD8 T cells and directed against tumor-specific antigens (TSAs). The presence of specific TSAs on cancer cells can only be proven by mass spectrometry analyses. Bioinformatic predictions and reverse immunology studies cannot provide this type of conclusive evidence. Most TSAs are coded by unmutated non-canonical transcripts that arise from cancer-specific epigenetic and splicing aberrations. When searching for TSAs, it is therefore important to perform mass spectrometry analyses that interrogate not only the canonical reading frame of annotated exome but all reading frames of the entire translatome. The majority of aberrantly expressed TSAs (aeTSAs) derive from unstable short-lived proteins that are good substrates for direct major histocompatibility complex (MHC) I presentation but poor substrates for cross-presentation. This is an important caveat, because cancer cells are poor antigen-presenting cells, and the immune system, therefore, depends on cross-presentation by dendritic cells (DCs) to detect the presence of TSAs. We, therefore, postulate that, in the untreated host, most aeTSAs are undetected by the immune system. We present evidence suggesting that vaccines inducing direct aeTSA presentation by DCs may represent an attractive strategy for cancer treatment.

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.

IFN-λ Enhances Constitutive Expression of MHC Class I Molecules on Thymic Epithelial Cells

Regulation of MHC class I (MHC I) expression has been studied almost exclusively in hematolymphoid cells. We report that thymic epithelial cells (TECs), particularly the medullary TECs, constitutively express up to 100-fold more cell surface MHC I proteins than epithelial cells (ECs) from the skin, colon, and lung. Differential abundance of cell surface MHC I in primary ECs is regulated via transcription of MHC I and of genes implicated in the generation of MHC I-binding peptides. Superior MHC I expression in TECs is unaffected by deletion of Ifnar1 or Ifngr1, but is lessened by deletion of Aire, Ifnlr1, Stat1, or Nlrc5, and is driven mainly by type III IFN produced by medullary TECs. Ifnlr1 ^-/- mice show impaired negative selection of CD8 thymocytes and, at 9 mo of age, present autoimmune manifestations. Our study shows unanticipated variation in MHC I expression by ECs from various sites and provides compelling evidence that superior expression of MHC I in TECs is crucial for proper thymocyte education.

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.