Immunopeptidogenomics: Harnessing RNA-Seq to Illuminate the Dark Immunopeptidome

Proteogenomics offers a novel avenue in neoantigen identification for cancer immunotherapy

Cancer neoantigens are tumor-specific non-synonymous mutant peptides that activate the immune system to produce an anti-tumor response. Personalized cancer vaccines based on neoantigens are currently one of the most promising therapeutic approaches for cancer treatment. By utilizing the unique mutations within each patient's tumor, these vaccines aim to elicit a strong and specific immune response against cancer cells. However, the identification of neoantigens remains challenging due to the low accuracy of current prediction tools and the high false-positive rate of candidate neoantigens. Since the concept of "proteogenomics" emerged in 2004, it has evolved rapidly with the increased sequencing depth of next-generation sequencing technologies and the maturation of mass spectrometry-based proteomics technologies to become a more comprehensive approach to neoantigen identification, allowing the discovery of high-confidence candidate neoantigens. In this review, we summarize the reason why cancer neoantigens have become attractive targets for immunotherapy, the mechanism of cancer vaccines and the advances in cancer immunotherapy. Considerations relevant to the application emerging of proteogenomics technologies for neoantigen identification and challenges in this field are described.

Proteasome isoforms in human thymi and mouse models

The thymus is the organ where functional and self-tolerant T cells are selected through processes of positive and negative selection before migrating to the periphery. The antigenic peptides presented on MHC class I molecules of thymic epithelial cells (TECs) in the cortex and medulla of the thymus are key players in these processes. It has been theorized that these cells express different proteasome isoforms, which generate MHC class I immunopeptidomes with features that differentiate cortex and medulla, and hence positive and negative CD8+ T cell selection. This theory is largely based on mouse models and does not consider the large variety of noncanonical antigenic peptides that could be produced by proteasomes and presented on MHC class I molecules. Here, we review the multi-omics, biochemical and cellular studies carried out on mouse models and human thymi to investigate their content of proteasome isoforms, briefly summarize the implication that noncanonical antigenic peptide presentation in the thymus could have on CD8+ T cell repertoire and put these aspects in the larger framework of anatomical and immunological differences between these two species.

Exploring the dynamic landscape of immunopeptidomics: Unravelling posttranslational modifications and navigating bioinformatics terrain

Immunopeptidomics is becoming an increasingly important field of study. The capability to identify immunopeptides with pivotal roles in the human immune system is essential to shift the current curative medicine towards personalized medicine. Throughout the years, the field has matured, giving insight into the current pitfalls. Nowadays, it is commonly accepted that generalizing shotgun proteomics workflows is malpractice because immunopeptidomics faces numerous challenges. While many of these difficulties have been addressed, the road towards the ideal workflow remains complicated. Although the presence of Posttranslational modifications (PTMs) in the immunopeptidome has been demonstrated, their identification remains highly challenging despite their significance for immunotherapies. The large number of unpredictable modifications in the immunopeptidome plays a pivotal role in the functionality and these challenges. This review provides a comprehensive overview of the current advancements in immunopeptidomics. We delve into the challenges associated with identifying PTMs within the immunopeptidome, aiming to address the current state of the field.

Immunopeptidomics in the cancer immunotherapy era

Cancer is the primary cause of death worldwide, and conventional treatments are painful, complicated, and have negative effects on healthy cells. However, cancer immunotherapy has emerged as a promising alternative. Principle of cancer immunotherapy is the re-activation of T-cell to combat the tumor that presents the peptide antigen on major histocompatibility complex (MHC). Those peptide antigens are identified with the set of omics technology, proteomics, genomics, and bioinformatics, which referred to immunopeptidomics. Indeed, immunopeptidomics can identify the neoantigens that are very useful for cancer immunotherapies. This review explored the use of immunopeptidomics for various immunotherapies, i.e., peptide-based vaccines, immune checkpoint inhibitors, oncolytic viruses, and chimeric antigen receptor T-cell. We also discussed how the diversity of neoantigens allows for the discovery of novel antigenic peptides while post-translationally modified peptides diversify the overall peptides binding to MHC or so-called MHC ligandome. The development of immunopeptidomics is keeping up-to-date and very active, particularly for clinical application. Immunopeptidomics is expected to be fast, accurate and reliable for the application for cancer immunotherapies.

pXg: Comprehensive Identification of Noncanonical MHC-I-Associated Peptides From De Novo Peptide Sequencing Using RNA-Seq Reads

Discovering noncanonical peptides has been a common application of proteogenomics. Recent studies suggest that certain noncanonical peptides, known as noncanonical major histocompatibility complex-I (MHC-I)-associated peptides (ncMAPs), that bind to MHC-I may make good immunotherapeutic targets. De novo peptide sequencing is a great way to find ncMAPs since it can detect peptide sequences from their tandem mass spectra without using any sequence databases. However, this strategy has not been widely applied for ncMAP identification because there is not a good way to estimate its false-positive rates. In order to completely and accurately identify immunopeptides using de novo peptide sequencing, we describe a unique pipeline called proteomics X genomics. In contrast to current pipelines, it makes use of genomic data, RNA-Seq abundance and sequencing quality, in addition to proteomic features to increase the sensitivity and specificity of peptide identification. We show that the peptide-spectrum match quality and genetic traits have a clear relationship, showing that they can be utilized to evaluate peptide-spectrum matches. From 10 samples, we found 24,449 canonical MHC-I-associated peptides and 956 ncMAPs by using a target-decoy competition. Three hundred eighty-seven ncMAPs and 1611 canonical MHC-I-associated peptides were new identifications that had not yet been published. We discovered 11 ncMAPs produced from a squirrel monkey retrovirus in human cell lines in addition to the two ncMAPs originating from a complementarity determining region 3 in an antibody thanks to the unrestricted search space assumed by de novo sequencing. These entirely new identifications show that proteomics X genomics can make the most of de novo peptide sequencing's advantages and its potential use in the search for new immunotherapeutic targets.

What do cancer-specific CD8+ T cells see? The contribution of immunopeptidomics

Immunopeptidomics is the survey of all peptides displayed on a cell or tissue when bound to human leukocyte antigen (HLA) molecules using tandem mass spectrometry. When attempting to determine the targets of tumour-specific CD8+ T cells, a survey of the potential ligands in tumour tissues is invaluable, and, in comparison with in-silico predictions, provides greater certainty of the existence of individual epitopes, as immunopeptidomics-confirmed CD8+ T-cell epitopes are known to be immunogenic, and direct observation should avoid the risk of autoreactivity which could arise following immunisation with structural homologues. The canonical sources of CD8+ T-cell tumour specific epitopes, such as tumour associated antigens, may be well conserved between patients and tumour types, but are often only weakly immunogenic. Direct observation of tumour-specific neoantigens by immunopeptidomics is rare, although valuable. Thus, there has been increasing interest in the non-canonical origins of tumour-reactive CD8+ T-cell epitopes, such as those arising from proteasomal splicing events, translational/turnover defects and alternative open reading frame reads. Such epitopes can be identified in silico, although validation is more challenging. Non-self CD8+ T-cell epitopes such as viral epitopes may be useful in certain cancer types with known viral origins, however these have been relatively unexplored with immunopeptidomics to date, possibly due to the paucity of source viral proteins in tumour tissues. This review examines the latest evidence for canonical, non-canonical and non-human CD8+ T-cell epitopes identified by immunopeptidomics, and concludes that the relative contribution for each of these sources to anti-tumour CD8+ T-cell reactivity is currently uncertain.

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.

Exploring the Immunogenicity of Noncanonical HLA-I Tumor Ligands Identified through Proteogenomics

PURPOSE

Tumor antigens are central to antitumor immunity. Recent evidence suggests that peptides from noncanonical (nonC) aberrantly translated proteins can be presented on HLA-I by tumor cells. Here, we investigated the immunogenicity of nonC tumor HLA-I ligands (nonC-TL) to better understand their contribution to cancer immunosurveillance and their therapeutic applicability.

EXPERIMENTAL DESIGN

Peptides presented on HLA-I were identified in 9 patient-derived tumor cell lines from melanoma, gynecologic, and head and neck cancer through proteogenomics. A total of 507 candidate tumor antigens, including nonC-TL, neoantigens, cancer-germline, or melanocyte differentiation antigens, were tested for T-cell recognition of preexisting responses in patients with cancer. Donor peripheral blood lymphocytes (PBL) were in vitro sensitized against 170 selected nonC-TL to isolate antigen-specific T-cell receptors (TCR) and evaluate their therapeutic potential.

RESULTS

We found no recognition of the 507 nonC-TL tested by autologous ex vivo expanded tumor-reactive T-cell cultures while the same cultures demonstrated reactivity to mutated, cancer-germline, or melanocyte differentiation antigens. However, in vitro sensitization of donor PBL against 170 selected nonC-TL, led to the identification of TCRs specific to three nonC-TL, two of which mapped to the 5' UTR regions of HOXC13 and ZKSCAN1, and one mapping to a noncoding spliced variant of C5orf22C. T cells targeting these nonC-TL recognized cancer cell lines naturally presenting their corresponding antigens. Expression of the three immunogenic nonC-TL was shared across tumor types and barely or not detected in normal cells.

CONCLUSIONS

Our findings predict a limited contribution of nonC-TL to cancer immunosurveillance but demonstrate they may be attractive novel targets for widely applicable immunotherapies. See related commentary by Fox et al., p. 2173.

Antigen discovery for the development of cancer immunotherapy

Central to successful cancer immunotherapy is effective T cell antitumor immunity. Multiple targeted immunotherapies engineered to invigorate T cell-driven antitumor immunity rely on identifying the repertoire of T cell antigens expressed on the tumor cell surface. Mass spectrometry-based survey of such antigens ("immunopeptidomics") combined with other omics platforms and computational algorithms has been instrumental in identifying and quantifying tumor-derived T cell antigens. In this review, we discuss the types of tumor antigens that have emerged for targeted cancer immunotherapy and the immunopeptidomics methods that are central in MHC peptide identification and quantification. We provide an overview of the strength and limitations of mass spectrometry-driven approaches and how they have been integrated with other technologies to discover targetable T cell antigens for cancer immunotherapy. We highlight some of the emerging cancer immunotherapies that successfully capitalized on immunopeptidomics, their challenges, and mass spectrometry-based strategies that can support their development.

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).

New insights and approaches for analyses of immunopeptidomes

Human leucocyte antigen (HLA) molecules play a key role in health and disease by presenting antigen to T-lymphocytes for immunosurveillance. Immunopeptidomics involves the study of the collection of peptides presented within the antigen-binding groove of HLA molecules. Identifying their nature and diversity is crucial to understanding immunosurveillance especially during infection or for the recognition and potential eradication of tumours. This review discusses recent advances in the isolation, identification, and quantitation of these peptide antigens. New informatics approaches and databases have shed light on the extent of peptide antigens derived from unconventional sources including peptides derived from transcripts associated with frame shifts, long noncoding RNA, incorrectly annotated untranslated regions, post-translational modifications, and proteasomal splicing. Several challenges remain in successful analysis of immunopeptides, yet recent developments point to unexplored biology waiting to be unravelled.