Global Identification of Post-Translationally Spliced Peptides with Neo-Fusion

Immunopeptidomics for autoimmunity: unlocking the chamber of immune secrets

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

Protein degradation by human 20S proteasomes elucidates the interplay between peptide hydrolysis and splicing

If and how proteasomes catalyze not only peptide hydrolysis but also peptide splicing is an open question that has divided the scientific community. The debate has so far been based on immunopeptidomics, in vitro digestions of synthetic polypeptides as well as ex vivo and in vivo experiments, which could only indirectly describe proteasome-catalyzed peptide splicing of full-length proteins. Here we develop a workflow-and cognate software - to analyze proteasome-generated non-spliced and spliced peptides produced from entire proteins and apply it to in vitro digestions of 15 proteins, including well-known intrinsically disordered proteins such as human tau and α-Synuclein. The results confirm that 20S proteasomes produce a sizeable variety of cis-spliced peptides, whereas trans-spliced peptides are a minority. Both peptide hydrolysis and splicing produce peptides with well-defined characteristics, which hint toward an intricate regulation of both catalytic activities. At protein level, both non-spliced and spliced peptides are not randomly localized within protein sequences, but rather concentrated in hotspots of peptide products, in part driven by protein sequence motifs and proteasomal preferences. At sequence level, the different peptide sequence preference of peptide hydrolysis and peptide splicing suggests a competition between the two catalytic activities of 20S proteasomes during protein degradation.

Neoantigen-targeted TCR-engineered T cell immunotherapy: current advances and challenges

Adoptive cell therapy using T cell receptor-engineered T cells (TCR-T) is a promising approach for cancer therapy with an expectation of no significant side effects. In the human body, mature T cells are armed with an incredible diversity of T cell receptors (TCRs) that theoretically react to the variety of random mutations generated by tumor cells. The outcomes, however, of current clinical trials using TCR-T cell therapies are not very successful especially involving solid tumors. The therapy still faces numerous challenges in the efficient screening of tumor-specific antigens and their cognate TCRs. In this review, we first introduce TCR structure-based antigen recognition and signaling, then describe recent advances in neoantigens and their specific TCR screening technologies, and finally summarize ongoing clinical trials of TCR-T therapies against neoantigens. More importantly, we also present the current challenges of TCR-T cell-based immunotherapies, e.g., the safety of viral vectors, the mismatch of T cell receptor, the impediment of suppressive tumor microenvironment. Finally, we highlight new insights and directions for personalized TCR-T therapy.

iBench: A ground truth approach for advanced validation of mass spectrometry identification method

The discovery of many noncanonical peptides detectable with sensitive mass spectrometry inside, outside, and on cells shepherded the development of novel methods for their identification, often not supported by a systematic benchmarking with other methods. We here propose iBench, a bioinformatic tool that can construct ground truth proteomics datasets and cognate databases, thereby generating a training court wherein methods, search engines, and proteomics strategies can be tested, and their performances estimated by the same tool. iBench can be coupled to the main database search engines, allows the selection of customized features of mass spectrometry spectra and peptides, provides standard benchmarking outputs, and is open source. The proof-of-concept application to tryptic proteome digestions, immunopeptidomes, and synthetic peptide libraries dissected the impact that noncanonical peptides could have on the identification of canonical peptides by Mascot search with rescoring via Percolator (Mascot+Percolator).

Sources of Cancer Neoantigens beyond Single-Nucleotide Variants

The success of checkpoint blockade therapy against cancer has unequivocally shown that cancer cells can be effectively recognized by the immune system and eliminated. However, the identity of the cancer antigens that elicit protective immunity remains to be fully explored. Over the last decade, most of the focus has been on somatic mutations derived from non-synonymous single-nucleotide variants (SNVs) and small insertion/deletion mutations (indels) that accumulate during cancer progression. Mutated peptides can be presented on MHC molecules and give rise to novel antigens or neoantigens, which have been shown to induce potent anti-tumor immune responses. A limitation with SNV-neoantigens is that they are patient-specific and their accurate prediction is critical for the development of effective immunotherapies. In addition, cancer types with low mutation burden may not display sufficient high-quality [SNV/small indels] neoantigens to alone stimulate effective T cell responses. Accumulating evidence suggests the existence of alternative sources of cancer neoantigens, such as gene fusions, alternative splicing variants, post-translational modifications, and transposable elements, which may be attractive novel targets for immunotherapy. In this review, we describe the recent technological advances in the identification of these novel sources of neoantigens, the experimental evidence for their presentation on MHC molecules and their immunogenicity, as well as the current clinical development stage of immunotherapy targeting these neoantigens.

Computational cancer neoantigen prediction: current status and recent advances

Over the last few decades, immunotherapy has shown significant therapeutic efficacy in a broad range of cancer types. Antitumor immune responses are contingent on the recognition of tumor-specific antigens, which are termed neoantigens. Tumor neoantigens are ideal targets for immunotherapy since they can be recognized as non-self antigens by the host immune system and thus are able to elicit an antitumor T-cell response. There are an increasing number of studies that highlight the importance of tumor neoantigens in immunoediting and in the sensitivity to immune checkpoint blockade. Therefore, one of the most fundamental tasks in the field of immuno-oncology research is the identification of patient-specific neoantigens. To this end, a plethora of computational approaches have been developed in order to predict tumor-specific aberrant peptides and quantify their likelihood of binding to patients' human leukocyte antigen molecules in order to be recognized by T cells. In this review, we systematically summarize and present the most recent advances in computational neoantigen prediction, and discuss the challenges and novel methods that are being developed to resolve them.

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Tumors have the ability to acquire immune escape mechanisms.

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Tumor-specific aberrant peptides (neoantigens) can elicit an immune response by the host immune system.

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The identification of neoantigens is one of the most fundamental tasks in the field of immuno-oncology research.

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A plethora of computational approaches have been developed in order to predict patient-specificneoantigens.

Identification of tumor antigens with immunopeptidomics

The identification of actionable tumor antigens is indispensable for the development of several cancer immunotherapies, including T cell receptor-transduced T cells and patient-specific mRNA or peptide vaccines. Most known tumor antigens have been identified through extensive molecular characterization and are considered canonical if they derive from protein-coding regions of the genome. By eluting human leukocyte antigen-bound peptides from tumors and subjecting these to mass spectrometry analysis, the peptides can be identified by matching the resulting spectra against reference databases. Recently, mass-spectrometry-based immunopeptidomics has enabled the discovery of noncanonical antigens-antigens derived from sequences outside protein-coding regions or generated by noncanonical antigen-processing mechanisms. Coupled with transcriptomics and ribosome profiling, this method enables the identification of thousands of noncanonical peptides, of which a substantial fraction may be detected exclusively in tumors. Spectral matching against the immense noncanonical reference may generate false positives. However, sensitive mass spectrometry, analytical validation and advanced bioinformatics solutions are expected to uncover the full landscape of presented antigens and clinically relevant targets.

Characterization of HLA-A*02:01 MHC Immunopeptide Antigens Enhanced by Ultraviolet Photodissociation Mass Spectrometry

Identifying major histocompatibility complex (MHC) class I immunopeptide antigens represents a key step in the development of immune-based targeted therapeutics and vaccines. However, the complete characterization of these antigens by tandem mass spectrometry remains challenging due to their short sequence length, high degree of hydrophobicity, and/or lack of sufficiently basic amino acids. This study seeks to address the potential for 193 nm ultraviolet photodissociation (UVPD) to improve the analysis of MHC class I immunopeptides by offering enhanced characterization of these sequences in lower charge states and differentiation of prominent isomeric leucine and isoleucine residues in the HLA-A*02:01 motif. Although electron transfer dissociation-higher energy collisional dissociation (EThcD) offered some success in the differentiation of leucine and isoleucine, 193 nm UVPD was able to confirm the identity of nearly 60% of leucine and isoleucine residues in a synthetic peptide mixture. Furthermore, 193 nm UVPD led to significantly more peptide identifications and higher scoring metrics than EThcD for peptides obtained from immunoprecipitation of MHC class I immunopeptides from in vitro cell culture. Additionally, 193 nm UVPD represents a promising complementary technique to higher-energy collisional dissociation (HCD), in which 424 of the 2593 peptides identified by 193 nm UVPD were not identified by HCD in HLA-A*02:01-specific immunoprecipitation and 804 of the 3300 peptides identified by 193 nm UVPD were not identified by HCD for pan HLA-A, -B, and -C immunoprecipitation. These results highlight that 193 nm UVPD offers an option for the characterization of immunopeptides, including differentiation of leucine and isoleucine residues.

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

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

The MHC Class-I Transactivator NLRC5: Implications to Cancer Immunology and Potential Applications to Cancer Immunotherapy

The immune system constantly monitors the emergence of cancerous cells and eliminates them. CD8⁺ cytotoxic T lymphocytes (CTLs), which kill tumor cells and provide antitumor immunity, select their targets by recognizing tumor antigenic peptides presented by MHC class-I (MHC-I) molecules. Cancer cells circumvent immune surveillance using diverse strategies. A key mechanism of cancer immune evasion is downregulation of MHC-I and key proteins of the antigen processing and presentation machinery (APM). Even though impaired MHC-I expression in cancers is well-known, reversing the MHC-I defects remains the least advanced area of tumor immunology. The discoveries that NLRC5 is the key transcriptional activator of MHC-I and APM genes, and genetic lesions and epigenetic modifications of NLRC5 are the most common cause of MHC-I defects in cancers, have raised the hopes for restoring MHC-I expression. Here, we provide an overview of cancer immunity mediated by CD8⁺ T cells and the functions of NLRC5 in MHC-I antigen presentation pathways. We describe the impressive advances made in understanding the regulation of NLRC5 expression, the data supporting the antitumor functions of NLRC5 and a few reports that argue for a pro-tumorigenic role. Finally, we explore the possible avenues of exploiting NLRC5 for cancer immunotherapy.

An Algorithm to Improve the Speed of Semi and Non-Specific Enzyme Searches in Proteomics

Background

The identification of non-specifically cleaved peptides in proteomics and peptidomics poses a significant computational challenge. Current strategies for the identification of such peptides are typically time consuming and hinder routine data analysis.

Objective

We aimed to design an algorithm that would improve the speed of semi- and non-specific enzyme searches and could be applicable to existing search programs.

Method

We developed a novel search algorithm that leverages fragment-ion redundancy to simultaneously search multiple non-specifically cleaved peptides at once. Briefly, a theoretical peptide tandem mass spectrum is generated using only the fragment-ion series from a single terminus. This spectrum serves as a proxy for several shorter theoretical peptides sharing the same terminus. After database searching, amino acids are removed from the opposing terminus until the observed and theoretical precursor masses match within a given mass tolerance.

Results

The algorithm was implemented in the search program MetaMorpheus and found to perform an order of magnitude faster than the traditional MetaMorpheus search and produce superior results.

Conclusion

We report a speedy non-specific enzyme search algorithm which is open-source and enables search programs to utilize fragment-ion redundancy to achieve a notable increase in search speed.

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.

A few good peptides: MHC class I-based cancer immunosurveillance and immunoevasion

The remarkable success of immune checkpoint inhibitors demonstrates the potential of tumour-specific CD8⁺ T cells to prevent and treat cancer. Although the number of lives saved by immunotherapy mounts, only a relatively small fraction of patients are cured. Here, we review two of the factors that limit the application of CD8⁺ T cell immunotherapies: difficulties in identifying tumour-specific peptides presented by MHC class I molecules and the ability of tumour cells to impair antigen presentation as they evolve under T cell selection. We describe recent advances in understanding how peptides are generated from non-canonical translation of defective ribosomal products, relate this to the dysregulated translation that is a feature of carcinogenesis and propose dysregulated translation as an important new source of tumour-specific peptides. We discuss how the synthesis and function of components of the antigen-processing and presentation pathway, including the recently described immunoribosome, are manipulated by tumours for immunoevasion and point to common druggable targets that may enhance immunotherapy.

Comment on "A subset of HLA-I peptides are not genomically templated: Evidence for cis- and trans-spliced peptide ligands"

There is still no convincing evidence for the frequent occurrence of posttranslationally spliced HLA-I peptides.

A large peptidome dataset improves HLA class I epitope prediction across most of the human population

Prediction of HLA epitopes is important for the development of cancer immunotherapies and vaccines. However, current prediction algorithms have limited predictive power, in part because they were not trained on high-quality epitope datasets covering a broad range of HLA alleles. To enable prediction of endogenous HLA class I-associated peptides across a large fraction of the human population, we used mass spectrometry to profile >185,000 peptides eluted from 95 HLA-A, -B, -C and -G mono-allelic cell lines. We identified canonical peptide motifs per HLA allele, unique and shared binding submotifs across alleles and distinct motifs associated with different peptide lengths. By integrating these data with transcript abundance and peptide processing, we developed HLAthena, providing allele-and-length-specific and pan-allele-pan-length prediction models for endogenous peptide presentation. These models predicted endogenous HLA class I-associated ligands with 1.5-fold improvement in positive predictive value compared with existing tools and correctly identified >75% of HLA-bound peptides that were observed experimentally in 11 patient-derived tumor cell lines.

Contribution of proteasome-catalyzed peptide cis-splicing to viral targeting by CD8+ T cells in HIV-1 infection

Peptides generated by proteasome-catalyzed splicing of noncontiguous amino acid sequences have been shown to constitute a source of nontemplated human leukocyte antigen class I (HLA-I) epitopes, but their role in pathogen-specific immunity remains unknown. CD8+ T cells are key mediators of HIV type 1 (HIV-1) control, and identification of novel epitopes to enhance targeting of infected cells is a priority for prophylactic and therapeutic strategies. To explore the contribution of proteasome-catalyzed peptide splicing (PCPS) to HIV-1 epitope generation, we developed a broadly applicable mass spectrometry-based discovery workflow that we employed to identify spliced HLA-I-bound peptides on HIV-infected cells. We demonstrate that HIV-1-derived spliced peptides comprise a relatively minor component of the HLA-I-bound viral immunopeptidome. Although spliced HIV-1 peptides may elicit CD8+ T cell responses relatively infrequently during infection, CD8+ T cells primed by partially overlapping contiguous epitopes in HIV-infected individuals were able to cross-recognize spliced viral peptides, suggesting a potential role for PCPS in restricting HIV-1 escape pathways. Vaccine-mediated priming of responses to spliced HIV-1 epitopes could thus provide a novel means of exploiting epitope targets typically underutilized during natural infection.

An in silico-in vitro Pipeline Identifying an HLA-A*02:01+ KRAS G12V+ Spliced Epitope Candidate for a Broad Tumor-Immune Response in Cancer Patients

Targeting CD8⁺ T cells to recurrent tumor-specific mutations can profoundly contribute to cancer treatment. Some of these mutations are potential tumor antigens although they can be displayed by non-spliced epitopes only in a few patients, because of the low affinity of the mutated non-spliced peptides for the predominant HLA class I alleles. Here, we describe a pipeline that uses the large sequence variety of proteasome-generated spliced peptides and identifies spliced epitope candidates, which carry the mutations and bind the predominant HLA-I alleles with high affinity. They could be used in adoptive T cell therapy and other anti-cancer immunotherapies for large cohorts of cancer patients. As a proof of principle, the application of this pipeline led to the identification of a KRAS G12V mutation-carrying spliced epitope candidate, which is produced by proteasomes, transported by TAPs and efficiently presented by the most prevalent HLA class I molecules, HLA-A^*02:01 complexes.

HIPs and HIP-reactive T cells

Mounting evidence implicates hybrid insulin peptides (HIPs) as important autoantigens in the development of type 1 diabetes (T1D). These fusion peptides formed between insulin and other pancreatic beta cell-derived peptides contain non-genomically encoded amino acid sequences, making them plausible targets for autoreactive T cells in T1D. HIPs are detectable by mass spectrometry in human and murine islets and are targeted by diabetes-inducing T cells in non-obese diabetic mice as well as by T cells isolated from the residual pancreatic islets of human organ donors with T1D. The discovery of HIPs comes with numerous new challenges, as well as opportunities to study the pathogenesis of T1D. Here we review the original discovery of HIPs and describe recent studies investigating the role of HIP-reactive T cells in the development of diabetes. We also discuss potential mechanisms that may be responsible for the generation of HIPs in beta cells and describe challenges that need to be addressed in the field of mass spectrometry to enable the discovery of new HIPs. The identification of these potentially disease-driving antigens in T1D is of key interest to the field as it may provide new tools to predict, prevent and potentially reverse the disease.

Identification of Hybrid Insulin Peptides (HIPs) in Mouse and Human Islets by Mass Spectrometry

We recently discovered hybrid insulin peptides (HIPs) as a novel class of post-translationally modified peptides in murine-derived beta cell tumors, and we demonstrated that these molecules are autoantigens in type 1 diabetes (T1D). A HIP consists of an insulin fragment linked to another secretory granule peptide via a peptide bond. We verified that autoreactive CD4 T cells in both mouse and human autoimmune diabetes recognize these modified peptides. Here, we use mass spectrometric analyses to confirm the presence of HIPs in both mouse and human pancreatic islets. We also present criteria for the confident identification of these peptides. This work supports the hypothesis that HIPs are autoantigens in human T1D and provides a foundation for future efforts to interrogate this previously unknown component of the beta cell proteome.