Immunopeptidomics: Reading the Immune Signal That Defines Self From Nonself

Fifty years have passed since the study of Benacerraf and McDevitt (1Benacerraf B. McDevitt H.O. Histocompatibility-linked immune response genes.Science. 1972; 175: 273-279Crossref PubMed Scopus (813) Google Scholar) describing the exquisite regulation of the immune response by the major histocompatibility complex (MHC). The landmark discovery that T-cell activation requires corecognition of peptide antigens and self-MHC molecules (2Zinkernagel R.M. Doherty P.C. Restriction of in vitro T cell-mediated cytotoxicity in lymphocytic choriomeningitis within a syngeneic or semiallogeneic system.Nature. 1974; 248: 701-702Crossref PubMed Scopus (1424) Google Scholar) revealed not only a unique receptor–ligand interaction but also a delicate balance between autoimmune response and effective protection against infection. These seminal studies laid the foundation to our current understanding of how immune cells distinguish between self and nonself. T cells display a remarkable selectivity and discriminate self and nonself from an astonishing number of antigen peptides presented by MHC molecules, a property that is largely defined during their development in the thymus. Furthermore, the MHC locus is the most polymorphic region of the human genome, and this structural diversity enables MHC molecules to present a wide distribution of peptide antigens originating from the degradation of endogenous (MHC class I) or exogenous (MHC class II) proteins. The biogenesis of peptide antigens is an intricate process shaped not only by environmental stimuli but also by specific proteolytic enzymes located in distinct organelles. The antigen repertoire, collectively referred to as the immunopeptidome, cannot be inferred from transcript or protein abundance and mainly relies on mass spectrometry analyses of peptides eluted from MHC complex. However, mass spectrometry alone is not sufficient to unveil the full repertoire of antigens concealed by MHC molecules. Indeed, structural variants arising from genomic polymorphisms or noncanonical regions of the genome are absent from the reference proteomes, and their discovery requires more elaborated databases that leverage proteogenomic search strategies (3Nesvizhskii A.I. Proteogenomics: Concepts, applications and computational strategies.Nat. Methods. 2014; 11: 1114-1125Crossref PubMed Scopus (0) Google Scholar). Recent technological advances in MHC isolation methods, mass spectrometry sensitivity, and novel database search approaches have fueled immunopeptidomic discoveries and open up new perspectives for cancer immunotherapy. It is in this context that we assembled experts and opinion leaders in immunopeptidomics to contribute to this special issue and share their findings and views of this blossoming field of research. A perspective article by Jonathan Yewdell (4Yewdell J. MHC class I immunopeptidome: Past, present & future.Mol. Cell. Proteomics. 2022; 21: 100230Abstract Full Text Full Text PDF Scopus (1) Google Scholar) takes us on an historical journey of the immunopeptidome from the discovery of antigens presented by MHC to its future outlook in tumor immunology. All nucleated cells express MHC I molecules that present not only normal and abnormal self-antigens but also nonself pathogens to the effector CD8+ T cells. Defective ribosomal products account for a major source of misfolded nascent proteins that are subsequently degraded, thus contributing to the pool of peptides available to MHC I molecules. Defective ribosomal products have been implicated in early alert of the immune system about impending infections, and work from Arie Admon (5Komov L. Melamed Kadosh D. Barnea E. Admon A. The effect of interferons on presentation of defective ribosomal products as HLA peptides.Mol. Cell. Proteomics. 2021; 20: 100105Abstract Full Text Full Text PDF PubMed Google Scholar) suggests that the corresponding proteins represent a sizeable proportion of MHC I peptides upon cell stimulation with type I and II interferons. Immunopeptidomic studies have also enabled the identification of modified and noncanonical peptides. The discovery of proteasome-catalyzed peptide splicing has raised important questions regarding the actual proportion of these peptides in the immunopeptidome, and Arie Admon (6Admon A. Are there indeed spliced peptides in the immunopeptidome?.Mol. Cell. Proteomics. 2021; 20: 100099Abstract Full Text Full Text PDF PubMed Google Scholar) and Michele Mishto (7Mishto M. Commentary: Are there indeed spliced peptides in the immunopeptidome?.Mol. Cell. Proteomics. 2021; 20: 100158Abstract Full Text Full Text PDF PubMed Scopus (4) Google Scholar) are providing opposing views on the occurrence of these events. A review by Mahoney et al. (8Mahoney K.E. Shabanowitz J. Hunt D.F. MHC phosphopeptides: Promising targets for immunotherapy of cancer and other chronic diseases.Mol. Cell. Proteomics. 2021; 20: 100112Abstract Full Text Full Text PDF PubMed Google Scholar) discusses the occurrence of phosphorylated antigens in cancer and viral infections with a particular emphasis on dysregulation of p53, pRb, and PP2A. Macrophages, dendritic cells, and B cells express MHC II molecules and typically present abnormal or nonself pathogen antigens for the activation of CD4+ T cells. In many tumor types including glioblastoma, MHC II complexes are often not expressed. Work from Forlani et al. (9Forlani G. Michaux J. Pak H. Huber F. Marie Joseph E.L. Ramia E. Stevenson B.J. Linnebacher M. Accolla R.S. Bassani-Sternberg M. CIITA-transduced glioblastoma cells uncover a rich repertoire of clinically relevant tumor-associated HLA-II antigens.Mol. Cell. Proteomics. 2021; 20: 100032Abstract Full Text Full Text PDF PubMed Google Scholar) revealed the expression of MHC II peptides following the stable expression of the MHC II transactivator in glioblastoma cell lines and highlight their potential as peptide vaccines. Demers et al. (10Demmers L.C. Wu W. Heck A.J.R. HLA class II presentation is specifically altered at elevated temperatures in the B-lymphoblastic cell line JY.Mol. Cell. Proteomics. 2021; 20: 100089Abstract Full Text Full Text PDF PubMed Google Scholar) used B cells to show the intrinsic responses and adaptations in antigen presentation after heat shock without infection and found that upregulation of costimulatory molecules and MHC II proteins specifically reshaped the MHC II immunopeptidome and primed B cells for an immune response. Antigen presentation in MHC II complexes depends on its peptide-loading catalyst (human leukocyte antigen [HLA]-DM) and its associated modulator (HLA-DO) though this interaction is still incompletely understood. By using single MHC II allele antigen-presenting cells, Olsson et al. (11Olsson N. Jiang W. Adler L.N. Mellins E.D. Elias J.E. Tuning DO:DM ratios modulates MHC class II immunopeptidomes.Mol. Cell. Proteomics. 2022; 21: 100204Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar) described how the ratio of HLA-DM and HLA-DO affects MHC II peptide presentation. Taylor et al. (12Taylor H.B. Klaeger S. Clauser K.R. Sarkizova S. Weingarten-Gabbay S. Graham D.B. Carr S.A. Abelin J.G. MS-based HLA-II peptidomics combined with multiomics will aid the development of future immunotherapies.Mol. Cell. Proteomics. 2021; 20: 100116Abstract Full Text Full Text PDF PubMed Google Scholar) reviewed MHC II immunopeptidomics and discussed current challenges in immunoaffinity enrichment, improvement in peptide identification and epitope prediction, and the potential of MHC II peptides as targets for future immunotherapies. Immunopeptidomic workflows typically use different mass spectrometry acquisition methods, search engines, and allele prediction algorithms. While data-dependent acquisition is typically used in immunopeptidomic workflow, Pak et al. (13Pak H. Michaux J. Huber F. Chong C. Stevenson B.J. Muller M. Coukos G. Bassani-Sternberg M. Sensitive immunopeptidomics by leveraging available large-scale multi-HLA spectral libraries, data-independent acquisition, and MS/MS prediction.Mol. Cell. Proteomics. 2021; 20: 100080Abstract Full Text Full Text PDF PubMed Google Scholar) implemented data-independent acquisition and assessed its sensitivity and accuracy by matching these data against libraries of growing complexity. Klaeger et al. (14Klaeger S. Apffel A. Clauser K.R. Sarkizova S. Oliveira G. Rachimi S. Le P.M. Tarren A. Chea V. Abelin J.G. Braun D.A. Ott P.A. Keshishian H. Hacohen N. Keskin D.B. et al.Optimized liquid and gas phase fractionation increases HLA-peptidome coverage for primary cell and tissue samples.Mol. Cell. Proteomics. 2021; 20: 100133Abstract Full Text Full Text PDF PubMed Google Scholar) achieved deeper immunopeptidome coverage and sensitivity using microscale basic reverse-phase fractionation and ion mobility separation. A contribution by Pollock et al. (15Pollock S.B. Rose C.M. Darwish M. Bouziat R. Delamarre L. Blanchette C. Lill J.R. Sensitive and quantitative detection of MHC-I displayed neoepitopes using a semiautomated workflow and TOMAHAQ mass spectrometry.Mol. Cell. Proteomics. 2021; 20: 100108Abstract Full Text Full Text PDF PubMed Scopus (5) Google Scholar) described a semiautomated workflow for the isolation and multiplex quantification of MHC I peptides and demonstrated the routine identification of >4000 unique antigens from 250 million cells. Parker et al. (16Parker R. Tailor A. Peng X. Nicastri A. Zerweck J. Reimer U. Wenschuh H. Schnatbaum K. Ternette N. The choice of search engine affects sequencing depth and HLA class I allele-specific peptide repertoires.Mol. Cell. Proteomics. 2021; 20: 100124Abstract Full Text Full Text PDF PubMed Google Scholar) provided a detailed analysis of the performance of four search engines commonly used in the field of immunopeptidomics and highlighted differences in sensitivity and bias for each. MHC-binding prediction tools are commonly used in immunopeptidomics to identify peptide antigens likely present in the study population. To improve allele prediction, Pyke et al. (17Pyke R.M. Mellacheruvu D. Dea S. Abbott C.W. Zhang S.V. Phillips N.A. Harris J. Bartha G. Desai S. McClory R. West J. Snyder M.P. Chen R. Boyle S.M. Precision neoantigen discovery using large-scale immunopeptidomes and composite modeling of MHC peptide presentation.Mol. Cell. Proteomics. 2021; 20: 100111Abstract Full Text Full Text PDF PubMed Google Scholar) developed a pan-allele MHC-binding algorithm (SHERPA) using 167 HLA alleles and obtained increased precision compared with competing algorithms. While a fix affinity threshold is generally applied across all alleles, work from Reardon et al. (18Reardon B. Kosaloglu-Yalcin Z. Paul S. Peters B. Sette A. Allele-specific thresholds of eluted ligands for T-cell epitope prediction.Mol. Cell. Proteomics. 2021; 20: 100122Abstract Full Text Full Text PDF PubMed Scopus (2) Google Scholar) found that allele-specific thresholds are preferable when analyzing a few alleles. A computational and analytical approach to discriminate true HLA ligands from coisolated HLA-independent proteolytic peptides is proposed by Fritsche et al. (19Fritsche J. Kowalewski D.J. Backert L. Gwinner F. Dorner S. Priemer M. Tsou C.C. Hoffgaard F. Romer M. Schuster H. Schoor O. Weinschenk T. Pitfalls in HLA ligandomics-how to catch a li(e)gand.Mol. Cell. Proteomics. 2021; 20: 100110Abstract Full Text Full Text PDF PubMed Google Scholar), where they described tools and highlighted how to circumvent false ligand identification. To view immunopeptidomic data, Sirois et al. (20Kovalchik K.A. Ma Q. Wessling L. Saab F. Duquette J.D. Kubiniok P. Hamelin D.J. Faridi P. Li C. Purcell A.W. Jang A. Paramithiotis E. Tognetti M. Reiter L. Bruderer R. et al.MhcVizPipe: A quality control software for rapid assessment of small- to large-scale immunopeptidome datasets.Mol. Cell. Proteomics. 2022; 21: 100178Abstract Full Text Full Text PDF PubMed Scopus (3) Google Scholar) developed MhcVizPipe, a graphical user interface–based software tool for quality control in mass spectrometry–based immunopeptidomics. Several contributions of this issue leveraged immunopeptidomic workflow to identify putative tumor-specific antigens. Qi et al. (21Qi Y.A. Maity T.K. Cultraro C.M. Misra V. Zhang X. Ade C. Gao S. Milewski D. Nguyen K.D. Ebrahimabadi M.H. Hanada K.I. Khan J. Sahinalp C. Yang J.C. Guha U. Proteogenomic analysis unveils the HLA class I-presented immunopeptidome in melanoma and EGFR-mutant lung adenocarcinoma.Mol. Cell. Proteomics. 2021; 20: 100136Abstract Full Text Full Text PDF PubMed Google Scholar) described a proteogenomic approach to identify MHC I tumor-specific antigens in melanoma (“hot” tumor) and in an epidermal growth factor receptor mutant lung adenocarcinoma (“cold” tumor). MHC-I immunopeptidome analyses of murine fibrosarcoma following oncolytic reovirus and immune checkpoint blockade combination therapy identified a subset of peptide antigens that stimulate CD8 T-cell responses in treated animals (22Kim Y. Konda P. Murphy J.P. Paulo J.A. Gygi S.P. Gujar S. Immune checkpoint blockade augments changes within oncolytic virus-induced cancer MHC-I peptidome, creating novel antitumor CD8 T cell reactivities.Mol. Cell. Proteomics. 2022; 21: 100182Abstract Full Text Full Text PDF PubMed Google Scholar). The combination of immunopeptidomics and RNA-Seq enabled the identification of tumor-specific antigens in an acute myeloid leukemia cell line THP-1 (23Scull K.E. Pandey K. Ramarathinam S.H. Purcell A.W. Immunopeptidogenomics: Harnessing RNA-seq to illuminate the dark immunopeptidome.Mol. Cell. Proteomics. 2021; 20: 100143Abstract Full Text Full Text PDF PubMed Scopus (2) Google Scholar) and in colorectal cell lines and primary specimens (24Cleyle J. Hardy M.P. Minati R. Courcelles M. Durette C. Lanoix J. Laverdure J.P. Vincent K. Perreault C. Thibault P. Immunopeptidomic analyses of colorectal cancers with and without microsatellite instability.Mol. Cell. Proteomics. 2022; : 100228Abstract Full Text Full Text PDF PubMed Scopus (2) Google Scholar) and revealed that a large proportion of these antigens derived from alternative reading frames or noncoding genomic regions. Vaccines based on peptide antigens specific to neoplastic cells offer a glimmer of hope for the treatment of cancer. However, significant optimization is required in terms of antigen selection, modes of delivery, biomarker of drug efficacy, and combination therapy, before peptide vaccines can become an effective therapy. Nelde et al. (25Nelde A. Rammensee H.G. Walz J.S. The peptide vaccine of the future.Mol. Cell. Proteomics. 2021; 20: 100022Abstract Full Text Full Text PDF PubMed Google Scholar) reviewed current approaches in the development of peptide vaccines and their practical implications as future therapeutics. This special issue aims at taking the pulse of the evolving field of immunopeptidomics. Here, we attempted to feature many recent developments in immunopeptidomic workflows encompassing different enrichment and labeling strategies, mass spectrometry acquisition methods, sequencing, and allele prediction softwares. Although multiple challenges still exist in terms of standardization and sensitivity, we believe that continuing technological advancements in immunopeptidomics will provide new opportunities for basic and applied research in immunology. Such improvements represent a critical unmet need, particularly in immuno-oncology, where leveraging immunopeptidomic discoveries could improve the efficacy of current immunotherapies, including therapeutic vaccines and bispecific T-cell engagers. MHC Phosphopeptides: Promising Targets for Immunotherapy of Cancer and Other Chronic DiseasesMolecular & Cellular ProteomicsVol. 20PreviewIn Brief Although mutated antigens are currently the main focus of immunopeptidomics, disease-associated PTMs create potential targets for immunotherapeutic treatment of cancers and other diseases. We have found that many phosphorylated antigens are expressed across multiple cancers and patients. We propose that the most likely cause of this increased MHC phosphorylation is inhibition of PP2A, which is ubiquitously inhibited across cancers. If valid, a multitude of other diseases that inhibit PP2A could be targeted using the same antigen targets. Full-Text PDF Open AccessSensitive Immunopeptidomics by Leveraging Available Large-Scale Multi-HLA Spectral Libraries, Data-Independent Acquisition, and MS/MS PredictionMolecular & Cellular ProteomicsVol. 20PreviewIn Brief The implementation of DIA in the immunopeptidomics translational research domain has remained limited because the amount of HLA peptides eluted from clinical samples is typically not sufficient for acquiring both meaningful DDA data for generating comprehensive spectral libraries and DIA MS measurements. We implemented a DIA immunopeptidomics workflow and assessed its sensitivity and accuracy with libraries of growing complexity and multi-HLA libraries. In addition, we demonstrated the analysis of DIA data with predicted MS/MS spectra of clinically relevant HLA ligands. Full-Text PDF Open AccessAre There Indeed Spliced Peptides in the Immunopeptidome?Molecular & Cellular ProteomicsVol. 20PreviewIn Brief Peptide splicing was suggested to significantly contribute ligands to the immunopeptidome. This article argues that peptide splicing is at most very rare, even if it happens at all. Considerations against peptide splicing are based on bioinformatics calculations related to the analysis of the LC-MS/MS data, and on the abundance of water in the cells, which should compete effectively with the transpeptidation reaction, needed for peptide splicing. Full-Text PDF Open AccessCommentary: Are There Indeed Spliced Peptides in the Immunopeptidome?Molecular & Cellular ProteomicsVol. 20PreviewIn Brief Poteasome-generated spliced peptides can be attractive targets for novel immunotherapies. Admon’s perspective “argued that peptide splicing is, at most, an extremely rare event and likely does not happen at all.” This statement is in contrast with data obtained through (i) MS on in vitro digestions of polypeptides and HLA class I immunopeptidomes, (ii) T cell clone assays with cell lines, (iii) ex vivo experiments in mouse models and human blood, (iv) anticancer in mouse models and human patients. Full-Text PDF Open a of HLA-II & Cellular ProteomicsVol. 20PreviewIn Brief CD4+ T cell responses are for and effective anticancer in glioblastoma and many HLA-II complexes are expressed. is about HLA-II in stable expression of the class II major histocompatibility complex transactivator to a detailed immunopeptidomics, we a remarkable of the in glioblastoma cell lines and identified many ligands with implications for the development of cancer immunotherapies. Full-Text PDF Open DO:DM MHC II & Cellular ProteomicsVol. Brief presentation by The noncanonical MHC molecules HLA-DM and HLA-DO and their across and this We this by creating cell lines HLA-DM and and their We found that to their presentation across different DO:DM affinity to but not account for these Full-Text PDF Open I Past, and & Cellular ProteomicsVol. Brief A in CD8+ T-cell of and the critical contributions of MS-based studies to and future understanding of how cells the MHC class I immunopeptidome: the repertoire of and presented by MHC class I molecules for T-cell Full-Text PDF Open of on of Defective as HLA & Cellular ProteomicsVol. 20PreviewIn Brief of protein complexes are degraded, and of their degradation products are for presentation by the MHC molecules at the and degradation of by presentation of peptides by the MHC molecules. The was in this study using the in identification of many defective ribosomal for from of the and Full-Text PDF Open HLA-II the of & Cellular ProteomicsVol. 20PreviewIn Brief Although challenges in leveraging MS-based HLA-II the between and the presentation of HLA-II peptides to CD4+ T cells will the development of future immunotherapies. In this we our current understanding of HLA-II peptidomics and questions in the field and how MS-based will us to and improve our to antigens as targets for immunotherapies. Full-Text PDF Open II at in the & Cellular ProteomicsVol. 20PreviewIn Brief the response in a was by in the and the HLA class I and II quantitative and immunopeptidomics, we found that a is in after growing the cells for only at and that it is largely by in the HLA class II HLA class I Full-Text PDF Open

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