Global proteogenomic analysis of human MHC class I-associated peptides derived from non-canonical reading frames

Relevance of mutation-derived neoantigens and non-classical antigens for anticancer therapies

Efficacy of cancer immunotherapies relies on correct recognition of tumor antigens by lymphocytes, eliciting thus functional responses capable of eliminating tumor cells. Therefore, important efforts have been carried out in antigen identification, with the aim of understanding mechanisms of response to immunotherapy and to design safer and more efficient strategies. In addition to classical tumor-associated antigens identified during the last decades, implementation of next-generation sequencing methodologies is enabling the identification of neoantigens (neoAgs) arising from mutations, leading to the development of new neoAg-directed therapies. Moreover, there are numerous non-classical tumor antigens originated from other sources and identified by new methodologies. Here, we review the relevance of neoAgs in different immunotherapies and the results obtained by applying neoAg-based strategies. In addition, the different types of non-classical tumor antigens and the best approaches for their identification are described. This will help to increase the spectrum of targetable molecules useful in cancer immunotherapies.

Enhancing Mass spectrometry-based tumor immunopeptide identification: machine learning filter leveraging HLA binding affinity, aliphatic index and retention time deviation

Accurately identifying neoantigens is crucial for developing effective cancer vaccines and improving tumor immunotherapy. Mass spectrometry-based immunopeptidomics has emerged as a promising approach to identifying human leukocyte antigen (HLA) peptides presented on the surface of cancer cells, but false-positive identifications remain a significant challenge. In this study, liquid chromatography-tandem mass spectrometry-based proteomics and next-generation sequencing were utilized to identify HLA-presenting neoantigenic peptides resulting from non-synonymous single nucleotide variations in tumor tissues from 18 patients with renal cell carcinoma or pancreatic cancer. Machine learning was utilized to evaluate Mascot identifications through the prediction of MS/MS spectral consistency, and four descriptors for each candidate sequence: the max Mascot ion score, predicted HLA binding affinity, aliphatic index and retention time deviation, were selected as important features in filtering out identifications with inadequate fragmentation consistency. This suggests that incorporating rescoring filters based on peptide physicochemical characteristics could enhance the identification rate of MS-based immunopeptidomics compared to the traditional Mascot approach predominantly used for proteomics, indicating the potential for optimizing neoantigen identification pipelines as well as clinical applications.

Components, Formulations, Deliveries, and Combinations of Tumor Vaccines

Tumor vaccines, an important part of immunotherapy, prevent cancer or kill existing tumor cells by activating or restoring the body's own immune system. Currently, various formulations of tumor vaccines have been developed, including cell vaccines, tumor cell membrane vaccines, tumor DNA vaccines, tumor mRNA vaccines, tumor polypeptide vaccines, virus-vectored tumor vaccines, and tumor-in-situ vaccines. There are also multiple delivery systems for tumor vaccines, such as liposomes, cell membrane vesicles, viruses, exosomes, and emulsions. In addition, to decrease the risk of tumor immune escape and immune tolerance that may exist with a single tumor vaccine, combination therapy of tumor vaccines with radiotherapy, chemotherapy, immune checkpoint inhibitors, cytokines, CAR-T therapy, or photoimmunotherapy is an effective strategy. Given the critical role of tumor vaccines in immunotherapy, here, we look back to the history of tumor vaccines, and we discuss the antigens, adjuvants, formulations, delivery systems, mechanisms, combination therapy, and future directions of tumor vaccines.

Microproteins encoded by noncanonical ORFs are a major source of tumor-specific antigens in a liver cancer patient meta-cohort

The expression of tumor-specific antigens during cancer progression can trigger an immune response against the tumor. Here, we investigate if microproteins encoded by noncanonical open reading frames (ncORFs) are a relevant source of tumor-specific antigens. We analyze RNA sequencing data from 117 hepatocellular carcinoma (HCC) tumors and matched healthy tissue together with ribosome profiling and immunopeptidomics data. Combining human leukocyte antigen-epitope binding predictions and experimental validation experiments, we conclude that around 40% of the tumor-specific antigens in HCC are likely to be derived from ncORFs, including two peptides that can trigger an immune response in humanized mice. We identify a subset of 33 tumor-specific long noncoding RNAs expressing novel cancer antigens shared by more than 10% of the HCC samples analyzed, which, when combined, cover a large proportion of the patients. The results of the study open avenues for extending the range of anticancer vaccines.

Cellular control of protein levels: A systems biology perspective

How cells regulate protein levels is a central question of biology. Over the past decades, molecular biology research has provided profound insights into the mechanisms and the molecular machinery governing each step of the gene expression process, from transcription to protein degradation. Recent advances in transcriptomics and proteomics have complemented our understanding of these fundamental cellular processes with a quantitative, systems-level perspective. Multi-omic studies revealed significant quantitative, kinetic and functional differences between the genome, transcriptome and proteome. While protein levels often correlate with mRNA levels, quantitative investigations have demonstrated a substantial impact of translation and protein degradation on protein expression control. In addition, protein-level regulation appears to play a crucial role in buffering protein abundances against undesirable mRNA expression variation. These findings have practical implications for many fields, including gene function prediction and precision medicine.

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.

Noncanonical microprotein regulation of immunity

The immune system is highly regulated but, when dysregulated, suboptimal protective or overly robust immune responses can lead to immune-mediated disorders. The genetic and molecular mechanisms of immune regulation are incompletely understood, impeding the development of more precise diagnostics and therapeutics for immune-mediated disorders. Recently, thousands of previously unrecognized noncanonical microprotein genes encoded by small open reading frames have been identified. Many of these microproteins perform critical functions, often in a cell- and context-specific manner. Several microproteins are now known to regulate immunity; however, the vast majority are uncharacterized. Therefore, illuminating what is often referred to as the "dark proteome," may present opportunities to tune immune responses more precisely. Here, we review noncanonical microprotein biology, highlight recently discovered examples regulating immunity, and discuss the potential and challenges of modulating dysregulated immune responses by targeting microproteins.

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.

SOCS1 expression in cancer cells: potential roles in promoting antitumor immunity

Suppressor of cytokine signaling 1 (SOCS1) is a potent regulator immune cell responses and a proven tumor suppressor. Inhibition of SOCS1 in T cells can boost antitumor immunity, whereas its loss in tumor cells increases tumor aggressivity. Investigations into the tumor suppression mechanisms so far focused on tumor cell-intrinsic functions of SOCS1. However, it is possible that SOCS1 expression in tumor cells also regulate antitumor immune responses in a cell-extrinsic manner via direct and indirect mechanisms. Here, we discuss the evidence supporting the latter, and its implications for antitumor immunity.

Towards targeting transposable elements for cancer therapy

Transposable elements (TEs) represent almost half of the human genome. Historically deemed 'junk DNA', recent technological advancements have stimulated a wave of research into the functional impact of TEs on gene-regulatory networks in evolution and development, as well as in diseases including cancer. The genetic and epigenetic evolution of cancer involves the exploitation of TEs, whereby TEs contribute directly to cancer-specific gene activities. This Review provides a perspective on the role of TEs in cancer as being a 'double-edged sword', both promoting cancer evolution and representing a vulnerability that could be exploited in cancer therapy. We discuss how TEs affect transcriptome regulation and other cellular processes in cancer. We highlight the potential of TEs as therapeutic targets for cancer. We also summarize technical hurdles in the characterization of TEs with genomic assays. Last, we outline open questions and exciting future research avenues.

MARS an improved de novo peptide candidate selection method for non-canonical antigen target discovery in cancer

Understanding the nature and extent of non-canonical human leukocyte antigen (HLA) presentation in tumour cells is a priority for target antigen discovery for the development of next generation immunotherapies in cancer. We here employ a de novo mass spectrometric sequencing approach with a refined, MHC-centric analysis strategy to detect non-canonical MHC-associated peptides specific to cancer without any prior knowledge of the target sequence from genomic or RNA sequencing data. Our strategy integrates MHC binding rank, Average local confidence scores, and peptide Retention time prediction for improved de novo candidate Selection; culminating in the machine learning model MARS. We benchmark our model on a large synthetic peptide library dataset and reanalysis of a published dataset of high-quality non-canonical MHC-associated peptide identifications in human cancer. We achieve almost 2-fold improvement for high quality spectral assignments in comparison to de novo sequencing alone with an estimated accuracy of above 85.7% when integrated with a stepwise peptide sequence mapping strategy. Finally, we utilize MARS to detect and validate lncRNA-derived peptides in human cervical tumour resections, demonstrating its suitability to discover novel, immunogenic, non-canonical peptide sequences in primary tumour tissue.

Non-canonical antigens are the largest fraction of peptides presented by MHC class I in mismatch repair deficient murine colorectal cancer

BACKGROUND

Immunotherapy based on checkpoint inhibitors is highly effective in mismatch repair deficient (MMRd) colorectal cancer (CRC). These tumors carry a high number of mutations, which are predicted to translate into a wide array of neoepitopes; however, a systematic classification of the neoantigen repertoire in MMRd CRC is lacking. Mass spectrometry peptidomics has demonstrated the existence of MHC class I associated peptides (MAPs) originating from non-coding DNA regions. Based on these premises we investigated DNA genomic regions responsible for generating MMRd-induced peptides.

METHODS

We exploited mouse CRC models in which the MMR gene Mlh1 was genetically inactivated. Isogenic cell lines CT26 Mlh1+/+ and Mlh1-/- were inoculated in immunocompromised and immunocompetent mice. Whole genome and RNA sequencing data were generated from samples obtained before and after injection in murine hosts. First, peptide databases were built from transcriptomes of isogenic cell lines. We then compiled a database of peptides lost after tumor cells injection in immunocompetent mice, likely due to immune editing. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) and matched next-generation sequencing databases were employed to identify the DNA regions from which the immune-targeted MAPs originated. Finally, we adopted in vitro T cell assays to verify whether MAP-specific T cells were part of the in vivo immune response against Mlh1-/- cells.

RESULTS

Whole genome sequencing analyses revealed an unbalanced distribution of immune edited alterations across the genome in Mlh1-/- cells grown in immunocompetent mice. Specifically, untranslated (UTR) and coding regions exhibited the largest fraction of mutations leading to highly immunogenic peptides. Moreover, the integrated computational and LC-MS/MS analyses revealed that MAPs originate mainly from atypical translational events in both Mlh1+/+ and Mlh1-/- tumor cells. In addition, mutated MAPs-derived from UTRs and out-of-frame translation of coding regions-were highly enriched in Mlh1-/- cells. The MAPs trigger T-cell activation in mice primed with Mlh1-/- cells.

CONCLUSIONS

Our results suggest that-in comparison to MMR proficient CRC-MMRd tumors generate a significantly higher number of non-canonical mutated peptides able to elicit T cell responses. These results reveal the importance of evaluating the diversity of neoepitope repertoire in MMRd tumors.

Tumour circular RNAs elicit anti-tumour immunity by encoding cryptic peptides

Emerging data have shown that previously defined noncoding genomes might encode peptides that bind human leukocyte antigen (HLA) as cryptic antigens to stimulate adaptive immunity1,2. However, the significance and mechanisms of action of cryptic antigens in anti-tumour immunity remain unclear. Here mass spectrometry of the HLA class I (HLA-I) peptidome coupled with ribosome sequencing of human breast cancer samples identified HLA-I-binding cryptic antigenic peptides that were noncanonically translated by a tumour-specific circular RNA (circRNA): circFAM53B. The cryptic peptides efficiently primed naive CD4+ and CD8+ T cells in an antigen-specific manner and induced anti-tumour immunity. Clinically, the expression of circFAM53B and its encoded peptides was associated with substantial infiltration of antigen-specific CD8+ T cells and better survival in patients with breast cancer and patients with melanoma. Mechanistically, circFAM53B-encoded peptides had strong binding affinity to both HLA-I and HLA-II molecules. In vivo, administration of vaccines consisting of tumour-specific circRNA or its encoded peptides in mice bearing breast cancer tumours or melanoma induced enhanced infiltration of tumour-antigen-specific cytotoxic T cells, which led to effective tumour control. Overall, our findings reveal that noncanonical translation of circRNAs can drive efficient anti-tumour immunity, which suggests that vaccination exploiting tumour-specific circRNAs may serve as an immunotherapeutic strategy against malignant tumours.

Non-mutational neoantigens in disease

The ability of mammals to mount adaptive immune responses culminating with the establishment of immunological memory is predicated on the ability of the mature T cell repertoire to recognize antigenic peptides presented by syngeneic MHC class I and II molecules. Although it is widely believed that mature T cells are highly skewed towards the recognition of antigenic peptides originating from genetically diverse (for example, foreign or mutated) protein-coding regions, preclinical and clinical data rather demonstrate that novel antigenic determinants efficiently recognized by mature T cells can emerge from a variety of non-mutational mechanisms. In this Review, we describe various mechanisms that underlie the formation of bona fide non-mutational neoantigens, such as epitope mimicry, upregulation of cryptic epitopes, usage of non-canonical initiation codons, alternative RNA splicing, and defective ribosomal RNA processing, as well as both enzymatic and non-enzymatic post-translational protein modifications. Moreover, we discuss the implications of the immune recognition of non-mutational neoantigens for human disease.

Using long-read CAGE sequencing to profile cryptic-promoter-derived transcripts and their contribution to the immunopeptidome

Recent studies have shown that the noncoding genome can produce unannotated proteins as antigens that induce immune response. One major source of this activity is the aberrant epigenetic reactivation of transposable elements (TEs). In tumors, TEs often provide cryptic or alternate promoters, which can generate transcripts that encode tumor-specific unannotated proteins. Thus, TE-derived transcripts (TE transcripts) have the potential to produce tumor-specific, but recurrent, antigens shared among many tumors. Identification of TE-derived tumor antigens holds the promise to improve cancer immunotherapy approaches; however, current genomics and computational tools are not optimized for their detection. Here we combined CAGE technology with full-length long-read transcriptome sequencing (long-read CAGE, or LRCAGE) and developed a suite of computational tools to significantly improve immunopeptidome detection by incorporating TE and other tumor transcripts into the proteome database. By applying our methods to human lung cancer cell line H1299 data, we show that long-read technology significantly improves mapping of promoters with low mappability scores and that LRCAGE guarantees accurate construction of uncharacterized 5' transcript structure. Augmenting a reference proteome database with newly characterized transcripts enabled us to detect noncanonical antigens from HLA-pulldown LC-MS/MS data. Lastly, we show that epigenetic treatment increased the number of noncanonical antigens, particularly those encoded by TE transcripts, which might expand the pool of targetable antigens for cancers with low mutational burden.

Protein-coding potential of non-canonical open reading frames in human transcriptome

In recent years, proteogenomics and ribosome profiling studies have identified a large number of proteins encoded by noncoding regions in the human genome. They are encoded by small open reading frames (sORFs) in the untranslated regions (UTRs) of mRNAs and long non-coding RNAs (lncRNAs). These sORF encoded proteins (SEPs) are often <150AA and show poor evolutionary conservation. A subset of them have been functionally characterized and shown to play an important role in fundamental biological processes including cardiac and muscle function, DNA repair, embryonic development and various human diseases. How many novel protein-coding regions exist in the human genome and what fraction of them are functionally important remains a mystery. In this review, we discuss current progress in unraveling SEPs, approaches used for their identification, their limitations and reliability of these identifications. We also discuss functionally characterized SEPs and their involvement in various biological processes and diseases. Lastly, we provide insights into their distinctive features compared to canonical proteins and challenges associated with annotating these in protein reference databases.

One-step shotgun approach for antigenic specific pMHCs capture stimulated CD8+ T cell activation and proliferation

Antigenic peptides play a central role in immune surveillance in cancer, infectious disease, autoimmunity, and allergy. The identification and isolation of antigenic peptides for T cell immune response are crucial for successful personalized adoptive immune cell therapy. The mainly methods includes gene sequencing and bioinformatic analysis. The antigenic peptides which identified by analysis and artificially synthesized still need antigen presenting cell (APC) to deliver to T cells. However, high costs and lengthy process times have limited its application in clinical practice. In order to overcome it, this study attempted to directly capture antigenic peptide-major histocompatibility complex (MHC) class I (pMHCs) from cell lysates using streptavidin Dynabeads and biotin-labeled antibodies, then the pMHCs was co-cultured with tumor infiltrating lymphocytes (TILs) of the same tissue origin. The results indicated that the captured pMHCs were able to enrich the tumor antigen-specific CD8+ T cells, and also effectively induce proliferation and cytotoxic responses of CD8+ T cells. This study provided a novel approach for obtaining tumor antigenic pMHCs, which could enrich antigen-specific CD8+ T cells, and could also function as artificial APCs (aAPCs) to stimulate proliferation and activation of T cells. Notably, these pMHCs can stimulate the proliferation of stem-like memory T cells. In conclusion, this study describes a time-saving and low-cost method to isolate tumour antigen peptide MHC complexs, helping tumor antigen-specific T cell enrichment, activation, and proliferation.

Current perspectives on mass spectrometry-based immunopeptidomics: the computational angle to tumor antigen discovery

Identification of tumor antigens presented by the human leucocyte antigen (HLA) molecules is essential for the design of effective and safe cancer immunotherapies that rely on T cell recognition and killing of tumor cells. Mass spectrometry (MS)-based immunopeptidomics enables high-throughput, direct identification of HLA-bound peptides from a variety of cell lines, tumor tissues, and healthy tissues. It involves immunoaffinity purification of HLA complexes followed by MS profiling of the extracted peptides using data-dependent acquisition, data-independent acquisition, or targeted approaches. By incorporating DNA, RNA, and ribosome sequencing data into immunopeptidomics data analysis, the proteogenomic approach provides a powerful means for identifying tumor antigens encoded within the canonical open reading frames of annotated coding genes and non-canonical tumor antigens derived from presumably non-coding regions of our genome. We discuss emerging computational challenges in immunopeptidomics data analysis and tumor antigen identification, highlighting key considerations in the proteogenomics-based approach, including accurate DNA, RNA and ribosomal sequencing data analysis, careful incorporation of predicted novel protein sequences into reference protein database, special quality control in MS data analysis due to the expanded and heterogeneous search space, cancer-specificity determination, and immunogenicity prediction. The advancements in technology and computation is continually enabling us to identify tumor antigens with higher sensitivity and accuracy, paving the way toward the development of more effective cancer immunotherapies.

Precision medicine in the era of multi-omics: can the data tsunami guide rational treatment decision?

Precision medicine for cancer is rapidly moving to an approach that integrates multiple dimensions of the biology in order to model mechanisms of cancer progression in each patient. The discovery of multiple drivers per tumor challenges medical decision that faces several treatment options. Drug sensitivity depends on the actionability of the target, its clonal or subclonal origin and coexisting genomic alterations. Sequencing has revealed a large diversity of drivers emerging at treatment failure, which are potential targets for clinical trials or drug repurposing. To effectively prioritize therapies, it is essential to rank genomic alterations based on their proven actionability. Moving beyond primary drivers, the future of precision medicine necessitates acknowledging the intricate spatial and temporal heterogeneity inherent in cancer. The advent of abundant complex biological data will make artificial intelligence algorithms indispensable for thorough analysis. Here, we will discuss the advancements brought by the use of high-throughput genomics, the advantages and limitations of precision medicine studies and future perspectives in this field.

Advances in vaccine development for cancer prevention and treatment in Lynch Syndrome

Lynch Syndrome (LS) is one of the most common hereditary cancer syndromes, and is caused by mutations in one of the four DNA mismatch repair (MMR) genes, namely MLH1, MSH2, MSH6 and PMS2. Tumors developed by LS carriers display high levels of microsatellite instability, which leads to the accumulation of large numbers of mutations, among which frameshift insertion/deletions (indels) within microsatellite (MS) loci are the most common. As a result, MMR-deficient (MMRd) cells generate increased rates of tumor-specific neoantigens (neoAgs) that can be recognized by the immune system to activate cancer cell killing. In this context, LS is an ideal disease to leverage immune-interception strategies. Therefore, the identification of these neoAgs is an ongoing effort for the development of LS cancer preventive vaccines. In this review, we summarize the computational methods used for in silico neoAg prediction, including their challenges, and the experimental techniques used for in vitro validation of their immunogenicity. In addition, we outline results from past and on-going vaccine clinical trials and highlight avenues for improvement and future directions.

What Can Ribo-Seq, Immunopeptidomics, and Proteomics Tell Us About the Noncanonical Proteome?

Ribosome profiling (Ribo-Seq) has proven transformative for our understanding of the human genome and proteome by illuminating thousands of noncanonical sites of ribosome translation outside the currently annotated coding sequences (CDSs). A conservative estimate suggests that at least 7000 noncanonical ORFs are translated, which, at first glance, has the potential to expand the number of human protein CDSs by 30%, from ∼19,500 annotated CDSs to over 26,000 annotated CDSs. Yet, additional scrutiny of these ORFs has raised numerous questions about what fraction of them truly produce a protein product and what fraction of those can be understood as proteins according to conventional understanding of the term. Adding further complication is the fact that published estimates of noncanonical ORFs vary widely by around 30-fold, from several thousand to several hundred thousand. The summation of this research has left the genomics and proteomics communities both excited by the prospect of new coding regions in the human genome but searching for guidance on how to proceed. Here, we discuss the current state of noncanonical ORF research, databases, and interpretation, focusing on how to assess whether a given ORF can be said to be "protein coding."

BamQuery: a proteogenomic tool to explore the immunopeptidome and prioritize actionable tumor antigens

MHC-I-associated peptides deriving from non-coding genomic regions and mutations can generate tumor-specific antigens, including neoantigens. Quantifying tumor-specific antigens' RNA expression in malignant and benign tissues is critical for discriminating actionable targets. We present BamQuery, a tool attributing an exhaustive RNA expression to MHC-I-associated peptides of any origin from bulk and single-cell RNA-sequencing data. We show that many cryptic and mutated tumor-specific antigens can derive from multiple discrete genomic regions, abundantly expressed in normal tissues. BamQuery can also be used to predict MHC-I-associated peptides immunogenicity and identify actionable tumor-specific antigens de novo.

Translational fidelity screens in mammalian cells reveal eIF3 and eIF4G2 as regulators of start codon selectivity

The translation initiation machinery and the ribosome orchestrate a highly dynamic scanning process to distinguish proper start codons from surrounding nucleotide sequences. Here, we performed genome-wide CRISPRi screens in human K562 cells to systematically identify modulators of the frequency of translation initiation at near-cognate start codons. We observed that depletion of any eIF3 core subunit promoted near-cognate start codon usage, though sensitivity thresholds of each subunit to sgRNA-mediated depletion varied considerably. Double sgRNA depletion experiments suggested that enhanced near-cognate usage in eIF3D depleted cells required canonical eIF4E cap-binding and was not driven by eIF2A or eIF2D-dependent leucine tRNA initiation. We further characterized the effects of eIF3D depletion and found that the N-terminus of eIF3D was strictly required for accurate start codon selection, whereas disruption of the cap-binding properties of eIF3D had no effect. Lastly, depletion of eIF3D activated TNFα signaling via NF-κB and the interferon gamma response. Similar transcriptional profiles were observed upon knockdown of eIF1A and eIF4G2, which also promoted near-cognate start codon usage, suggesting that enhanced near-cognate usage could potentially contribute to NF-κB activation. Our study thus provides new avenues to study the mechanisms and consequences of alternative start codon usage.

Antigen-specific and cross-reactive T cells in protection and disease

Human T cells have a diverse T-cell receptor (TCR) repertoire that endows them with the ability to identify and defend against a broad spectrum of antigens. The universe of possible antigens that T cells may encounter, however, is even larger. To effectively surveil such a vast universe, the T-cell repertoire must adopt a high degree of cross-reactivity. Likewise, antigen-specific and cross-reactive T-cell responses play pivotal roles in both protective and pathological immune responses in numerous diseases. In this review, we explore the implications of these antigen-driven T-cell responses, with a particular focus on CD8+ T cells, using infection, neurodegeneration, and cancer as examples. We also summarize recent technological advances that facilitate high-throughput profiling of antigen-specific and cross-reactive T-cell responses experimentally, as well as computational biology approaches that predict these interactions.

Unlocking the potential of microfluidics in mass spectrometry-based immunopeptidomics for tumor antigen discovery

The identification of tumor-specific antigens (TSAs) is critical for developing effective cancer immunotherapies. Mass spectrometry (MS)-based immunopeptidomics has emerged as a powerful tool for identifying TSAs as physical molecules. However, current immunopeptidomics platforms face challenges in measuring low-abundance TSAs in a precise, sensitive, and reproducible manner from small needle-tissue biopsies (<1 mg). Inspired by recent advances in single-cell proteomics, microfluidics technology offers a promising solution to these limitations by providing improved isolation of human leukocyte antigen (HLA)-associated peptides with higher sensitivity. In this context, we highlight the challenges in sample preparation and the rationale for developing microfluidics technology in immunopeptidomics. Additionally, we provide an overview of promising microfluidic methods, including microchip pillar arrays, valved-based systems, droplet microfluidics, and digital microfluidics, and discuss the latest research on their application in MS-based immunopeptidomics and single-cell proteomics.

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.

The Immunopeptidome from a Genomic Perspective: Establishing the Noncanonical Landscape of MHC Class I-Associated Peptides

Tumor antigens can emerge through multiple mechanisms, including translation of noncoding genomic regions. This noncanonical category of tumor antigens has recently gained attention; however, our understanding of how they recur within and between cancer types is still in its infancy. Therefore, we developed a proteogenomic pipeline based on deep learning de novo mass spectrometry (MS) to enable the discovery of noncanonical MHC class I-associated peptides (ncMAP) from noncoding regions. Considering that the emergence of tumor antigens can also involve posttranslational modifications (PTM), we included an open search component in our pipeline. Leveraging the wealth of MS-based immunopeptidomics, we analyzed data from 26 MHC class I immunopeptidomic studies across 11 different cancer types. We validated the de novo identified ncMAPs, along with the most abundant PTMs, using spectral matching and controlled their FDR to 1%. The noncanonical presentation appeared to be 5 times enriched for the A03 HLA supertype, with a projected population coverage of 55%. The data reveal an atlas of 8,601 ncMAPs with varying levels of cancer selectivity and suggest 17 cancer-selective ncMAPs as attractive therapeutic targets according to a stringent cutoff. In summary, the combination of the open-source pipeline and the atlas of ncMAPs reported herein could facilitate the identification and screening of ncMAPs as targets for T-cell therapies or vaccine development.

CrypticProteinDB: an integrated database of proteome and immunopeptidome derived non-canonical cancer proteins

Translated non-canonical proteins derived from noncoding regions or alternative open reading frames (ORFs) can contribute to critical and diverse cellular processes. In the context of cancer, they also represent an under-appreciated source of targets for cancer immunotherapy through their tumor-enriched expression or by harboring somatic mutations that produce neoantigens. Here, we introduce the largest integration and proteogenomic analysis of novel peptides to assess the prevalence of non-canonical ORFs (ncORFs) in more than 900 patient proteomes and 26 immunopeptidome datasets across 14 cancer types. The integrative proteogenomic analysis of whole-cell proteomes and immunopeptidomes revealed peptide support for a nonredundant set of 9760 upstream, downstream, and out-of-frame ncORFs in protein coding genes and 12811 in noncoding RNAs. Notably, 6486 ncORFs were derived from differentially expressed genes and 340 were ubiquitously translated across eight or more cancers. The analysis also led to the discovery of thirty-four epitopes and eight neoantigens from non-canonical proteins in two cohorts as novel cancer immunotargets. Collectively, our analysis integrated both bottom-up proteogenomic and targeted peptide validation to illustrate the prevalence of translated non-canonical proteins in cancer and to provide a resource for the prioritization of novel proteins supported by proteomic, immunopeptidomic, genomic and transcriptomic data, available at https://www.maherlab.com/crypticproteindb.

IRIS: Discovery of cancer immunotherapy targets arising from pre-mRNA alternative splicing

Alternative splicing (AS) is prevalent in cancer, generating an extensive but largely unexplored repertoire of novel immunotherapy targets. We describe Isoform peptides from RNA splicing for Immunotherapy target Screening (IRIS), a computational platform capable of discovering AS-derived tumor antigens (TAs) for T cell receptor (TCR) and chimeric antigen receptor T cell (CAR-T) therapies. IRIS leverages large-scale tumor and normal transcriptome data and incorporates multiple screening approaches to discover AS-derived TAs with tumor-associated or tumor-specific expression. In a proof-of-concept analysis integrating transcriptomics and immunopeptidomics data, we showed that hundreds of IRIS-predicted TCR targets are presented by human leukocyte antigen (HLA) molecules. We applied IRIS to RNA-seq data of neuroendocrine prostate cancer (NEPC). From 2,939 NEPC-associated AS events, IRIS predicted 1,651 epitopes from 808 events as potential TCR targets for two common HLA types (A*02:01 and A*03:01). A more stringent screening test prioritized 48 epitopes from 20 events with "neoantigen-like" NEPC-specific expression. Predicted epitopes are often encoded by microexons of ≤30 nucleotides. To validate the immunogenicity and T cell recognition of IRIS-predicted TCR epitopes, we performed in vitro T cell priming in combination with single-cell TCR sequencing. Seven TCRs transduced into human peripheral blood mononuclear cells (PBMCs) showed high activity against individual IRIS-predicted epitopes, providing strong evidence of isolated TCRs reactive to AS-derived peptides. One selected TCR showed efficient cytotoxicity against target cells expressing the target peptide. Our study illustrates the contribution of AS to the TA repertoire of cancer cells and demonstrates the utility of IRIS for discovering AS-derived TAs and expanding cancer immunotherapies.

What can Ribo-seq and proteomics tell us about the non-canonical proteome?

Ribosome profiling (Ribo-seq) has proven transformative for our understanding of the human genome and proteome by illuminating thousands of non-canonical sites of ribosome translation outside of the currently annotated coding sequences (CDSs). A conservative estimate suggests that at least 7,000 non-canonical open reading frames (ORFs) are translated, which, at first glance, has the potential to expand the number of human protein-coding sequences by 30%, from ∼19,500 annotated CDSs to over 26,000. Yet, additional scrutiny of these ORFs has raised numerous questions about what fraction of them truly produce a protein product and what fraction of those can be understood as proteins according to conventional understanding of the term. Adding further complication is the fact that published estimates of non-canonical ORFs vary widely by around 30-fold, from several thousand to several hundred thousand. The summation of this research has left the genomics and proteomics communities both excited by the prospect of new coding regions in the human genome, but searching for guidance on how to proceed. Here, we discuss the current state of non-canonical ORF research, databases, and interpretation, focusing on how to assess whether a given ORF can be said to be "protein-coding".

In brief

The human genome encodes thousands of non-canonical open reading frames (ORFs) in addition to protein-coding genes. As a nascent field, many questions remain regarding non-canonical ORFs. How many exist? Do they encode proteins? What level of evidence is needed for their verification? Central to these debates has been the advent of ribosome profiling (Ribo-seq) as a method to discern genome-wide ribosome occupancy, and immunopeptidomics as a method to detect peptides that are processed and presented by MHC molecules and not observed in traditional proteomics experiments. This article provides a synthesis of the current state of non-canonical ORF research and proposes standards for their future investigation and reporting.

Highlights

Combined use of Ribo-seq and proteomics-based methods enables optimal confidence in detecting non-canonical ORFs and their protein products.Ribo-seq can provide more sensitive detection of non-canonical ORFs, but data quality and analytical pipelines will impact results.Non-canonical ORF catalogs are diverse and span both high-stringency and low-stringency ORF nominations.A framework for standardized non-canonical ORF evidence will advance the research field.

A vast evolutionarily transient translatome contributes to phenotype and fitness

Translation is the process by which ribosomes synthesize proteins. Ribosome profiling recently revealed that many short sequences previously thought to be noncoding are pervasively translated. To identify protein-coding genes in this noncanonical translatome, we combine an integrative framework for extremely sensitive ribosome profiling analysis, iRibo, with high-powered selection inferences tailored for short sequences. We construct a reference translatome for Saccharomyces cerevisiae comprising 5,400 canonical and almost 19,000 noncanonical translated elements. Only 14 noncanonical elements were evolving under detectable purifying selection. A representative subset of translated elements lacking signatures of selection demonstrated involvement in processes including DNA repair, stress response, and post-transcriptional regulation. Our results suggest that most translated elements are not conserved protein-coding genes and contribute to genotype-phenotype relationships through fast-evolving molecular mechanisms.

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.

PABPN1 prevents the nuclear export of an unspliced RNA with a constitutive transport element and controls human gene expression via intron retention

Intron retention is a type of alternative splicing where one or more introns remain unspliced in a polyadenylated transcript. Although many viral systems are known to translate proteins from mRNAs with retained introns, restriction mechanisms generally prevent export and translation of incompletely spliced mRNAs. Here, we provide evidence that the human nuclear poly(A)-binding protein, PABPN1, functions in such restrictions. Using a reporter construct in which nuclear export of an incompletely spliced mRNA is enhanced by a viral constitutive transport element (CTE), we show that PABPN1 depletion results in a significant increase in export and translation from the unspliced CTE-containing transcript. Unexpectedly, we find that inactivation of poly(A)-tail exosome targeting by depletion of PAXT components had no effect on export and translation of the unspliced reporter mRNA, suggesting a mechanism largely independent of nuclear RNA decay. Interestingly, a PABPN1 mutant selectively defective in stimulating poly(A) polymerase elongation strongly enhanced the expression of the unspliced, but not of intronless, reporter transcripts. Analysis of RNA-seq data also revealed that PABPN1 controls the expression of many human genes via intron retention. Notably, PABPN1-dependent intron retention events mostly affected 3'-terminal introns and were insensitive to PAXT and NEXT deficiencies. Our findings thus disclose a role for PABPN1 in restricting nuclear export of intron-retained transcripts and reinforce the interdependence between terminal intron splicing, 3' end processing, and polyadenylation.

The Immunological Conundrum of Endogenous Retroelements

Our defenses against infection rely on the ability of the immune system to distinguish invading pathogens from self. This task is exceptionally challenging, if not seemingly impossible, in the case of retroviruses that have integrated almost seamlessly into the host. This review examines the limits of innate and adaptive immune responses elicited by endogenous retroviruses and other retroelements, the targets of immune recognition, and the consequences for host health and disease. Contrary to theoretical expectation, endogenous retroelements retain substantial immunogenicity, which manifests most profoundly when their epigenetic repression is compromised, contributing to autoinflammatory and autoimmune disease and age-related inflammation. Nevertheless, recent evidence suggests that regulated immune reactivity to endogenous retroelements is integral to immune system development and function, underpinning cancer immunosurveillance, resistance to infection, and responses to the microbiota. Elucidation of the interaction points with endogenous retroelements will therefore deepen our understanding of immune system function and contribution to disease.

Variant biomarker discovery using mass spectrometry-based proteogenomics

Genomic diversity plays critical roles in risk of disease pathogenesis and diagnosis. While genomic variants-including single nucleotide variants, frameshift variants, and mis-splicing isoforms-are commonly detected at the DNA or RNA level, their translated variant protein or polypeptide products are ultimately the functional units of the associated disease. These products are often released in biofluids and could be leveraged for clinical diagnosis and patient stratification. Recent emergence of integrated analysis of genomics with mass spectrometry-based proteomics for biomarker discovery, also known as proteogenomics, have significantly advanced the understanding disease risk variants, precise medicine, and biomarker discovery. In this review, we discuss variant proteins in the context of cancers and neurodegenerative diseases, outline current and emerging proteogenomic approaches for biomarker discovery, and provide a comprehensive proteogenomic strategy for detection of putative biomarker candidates in human biospecimens. This strategy can be implemented for proteogenomic studies in any field of enquiry. Our review timely addresses the need of biomarkers for aging related diseases.

NLRC5-CIITA Fusion Protein as an Effective Inducer of MHC-I Expression and Antitumor Immunity

Aggressive tumors evade cytotoxic T lymphocytes by suppressing MHC class-I (MHC-I) expression that also compromises tumor responsiveness to immunotherapy. MHC-I defects strongly correlate to defective expression of NLRC5, the transcriptional activator of MHC-I and antigen processing genes. In poorly immunogenic B16 melanoma cells, restoring NLRC5 expression induces MHC-I and elicits antitumor immunity, raising the possibility of using NLRC5 for tumor immunotherapy. As the clinical application of NLRC5 is constrained by its large size, we examined whether a smaller NLRC5-CIITA fusion protein, dubbed NLRC5-superactivator (NLRC5-SA) as it retains the ability to induce MHC-I, could be used for tumor growth control. We show that stable NLRC5-SA expression in mouse and human cancer cells upregulates MHC-I expression. B16 melanoma and EL4 lymphoma tumors expressing NLRC5-SA are controlled as efficiently as those expressing full-length NLRC5 (NLRC5-FL). Comparison of MHC-I-associated peptides (MAPs) eluted from EL4 cells expressing NLRC5-FL or NLRC5-SA and analyzed by mass spectrometry revealed that both NLRC5 constructs expanded the MAP repertoire, which showed considerable overlap but also included a substantial proportion of distinct peptides. Thus, we propose that NLRC5-SA, with its ability to increase tumor immunogenicity and promote tumor growth control, could overcome the limitations of NLRC5-FL for translational immunotherapy applications.

Precision Neoantigen Discovery Using Large-Scale Immunopeptidomes and Composite Modeling of MHC Peptide Presentation

Major histocompatibility complex (MHC)-bound peptides that originate from tumor-specific genetic alterations, known as neoantigens, are an important class of anticancer therapeutic targets. Accurately predicting peptide presentation by MHC complexes is a key aspect of discovering therapeutically relevant neoantigens. Technological improvements in mass spectrometry-based immunopeptidomics and advanced modeling techniques have vastly improved MHC presentation prediction over the past 2 decades. However, improvement in the accuracy of prediction algorithms is needed for clinical applications like the development of personalized cancer vaccines, the discovery of biomarkers for response to immunotherapies, and the quantification of autoimmune risk in gene therapies. Toward this end, we generated allele-specific immunopeptidomics data using 25 monoallelic cell lines and created Systematic Human Leukocyte Antigen (HLA) Epitope Ranking Pan Algorithm (SHERPA), a pan-allelic MHC-peptide algorithm for predicting MHC-peptide binding and presentation. In contrast to previously published large-scale monoallelic data, we used an HLA-null K562 parental cell line and a stable transfection of HLA allele to better emulate native presentation. Our dataset includes five previously unprofiled alleles that expand MHC diversity in the training data and extend allelic coverage in underprofiled populations. To improve generalizability, SHERPA systematically integrates 128 monoallelic and 384 multiallelic samples with publicly available immunoproteomics data and binding assay data. Using this dataset, we developed two features that empirically estimate the propensities of genes and specific regions within gene bodies to engender immunopeptides to represent antigen processing. Using a composite model constructed with gradient boosting decision trees, multiallelic deconvolution, and 2.15 million peptides encompassing 167 alleles, we achieved a 1.44-fold improvement of positive predictive value compared with existing tools when evaluated on independent monoallelic datasets and a 1.17-fold improvement when evaluating on tumor samples. With a high degree of accuracy, SHERPA has the potential to enable precision neoantigen discovery for future clinical applications.

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.

PGNneo: A Proteogenomics-Based Neoantigen Prediction Pipeline in Noncoding Regions

The development of a neoantigen-based personalized vaccine has promise in the hunt for cancer immunotherapy. The challenge in neoantigen vaccine design is the need to rapidly and accurately identify, in patients, those neoantigens with vaccine potential. Evidence shows that neoantigens can be derived from noncoding sequences, but there are few specific tools for identifying neoantigens in noncoding regions. In this work, we describe a proteogenomics-based pipeline, namely PGNneo, for use in discovering neoantigens derived from the noncoding region of the human genome with reliability. In PGNneo, four modules are included: (1) noncoding somatic variant calling and HLA typing; (2) peptide extraction and customized database construction; (3) variant peptide identification; (4) neoantigen prediction and selection. We have demonstrated the effectiveness of PGNneo and applied and validated our methodology in two real-world hepatocellular carcinoma (HCC) cohorts. TP53, WWP1, ATM, KMT2C, and NFE2L2, which are frequently mutating genes associated with HCC, were identified in two cohorts and corresponded to 107 neoantigens from non-coding regions. In addition, we applied PGNneo to a colorectal cancer (CRC) cohort, demonstrating that the tool can be extended and verified in other tumor types. In summary, PGNneo can specifically detect neoantigens generated by noncoding regions in tumors, providing additional immune targets for cancer types with a low tumor mutational burden (TMB) in coding regions. PGNneo, together with our previous tool, can identify coding and noncoding region-derived neoantigens and, thus, will contribute to a complete understanding of the tumor immune target landscape. PGNneo source code and documentation are available at Github. To facilitate the installation and use of PGNneo, we provide a Docker container and a GUI.

Contemplating immunopeptidomes to better predict them

The identification of T-cell epitopes is key for a complete molecular understanding of immune recognition mechanisms in infectious diseases, autoimmunity and cancer. T-cell epitopes further provide targets for personalized vaccines and T-cell therapy, with several therapeutic applications in cancer immunotherapy and elsewhere. T-cell epitopes consist of short peptides displayed on Major Histocompatibility Complex (MHC) molecules. The recent advances in mass spectrometry (MS) based technologies to profile the ensemble of peptides displayed on MHC molecules - the so-called immunopeptidome - had a major impact on our understanding of antigen presentation and MHC ligands. On the one hand, these techniques enabled researchers to directly identify hundreds of thousands of peptides presented on MHC molecules, including some that elicited T-cell recognition. On the other hand, the data collected in these experiments revealed fundamental properties of antigen presentation pathways and significantly improved our ability to predict naturally presented MHC ligands and T-cell epitopes across the wide spectrum of MHC alleles found in human and other organisms. Here we review recent computational developments to analyze experimentally determined immunopeptidomes and harness these data to improve our understanding of antigen presentation and MHC binding specificities, as well as our ability to predict MHC ligands. We further discuss the strengths and limitations of the latest approaches to move beyond predictions of antigen presentation and tackle the challenges of predicting TCR recognition and immunogenicity.

TCR-engineered T cell therapy in solid tumors: State of the art and perspectives

T cell engineering has changed the landscape of cancer immunotherapy. Chimeric antigen receptor T cells have demonstrated a remarkable efficacy in the treatment of B cell malignancies in hematology. However, their clinical impact on solid tumors has been modest so far. T cells expressing an engineered T cell receptor (TCR-T cells) represent a promising therapeutic alternative. The target repertoire is not limited to membrane proteins, and intrinsic features of TCRs such as high antigen sensitivity and near-to-physiological signaling may improve tumor cell detection and killing while improving T cell persistence. In this review, we present the clinical results obtained with TCR-T cells targeting different tumor antigen families. We detail the different methods that have been developed to identify and optimize a TCR candidate. We also discuss the challenges of TCR-T cell therapies, including toxicity assessment and resistance mechanisms. Last, we share some perspectives and highlight future directions in the field.

Major histocompatibility class I antigenic peptides derived from translation of pre-mRNAs generate immune tolerance

Antigenic peptides derived from introns are presented on major histocompatibility (MHC) class I molecules, but how these peptides are produced is poorly understood. Here, we show that an MHC class I epitope (SL8) sequence inserted in the second intron of the β-globin gene in a C57BL/6 mouse (HBB) generates immune tolerance. Introduction of SL8-specific CD8⁺ T cells derived from OT-1 transgenic mice resulted in a threefold increase in OT-1 T cell proliferation in HBB animals, as compared to wild-type animals. The growth of MCA sarcoma cells expressing the intron-derived SL8 epitope was suppressed in wild-type animals compared to HBB mice. The β-globin pre-mRNA was detected in the light polysomal fraction, and introducing stop codons identified a non-AUG initiation site between +228 and +255 nts upstream of the SL8. Isolation of ribosome footprints confirmed translation initiation within this 27 nt sequence. Furthermore, treatment with splicing inhibitor shifts the translation of the pre-mRNA to monosomal fractions and results in an increase of intron-derived peptide substrate as shown by polysome profiling and cell imaging. These results show that non-AUG-initiated translation of pre-mRNAs generates peptides for MHC class I immune tolerance and helps explain why alternative tissue-specific splicing is tolerated by the immune system.

Noncanonical splicing junctions between exons and transposable elements represent a source of immunogenic recurrent neo-antigens in patients with lung cancer

Although most characterized tumor antigens are encoded by canonical transcripts (such as differentiation or tumor-testis antigens) or mutations (both driver and passenger mutations), recent results have shown that noncanonical transcripts including long noncoding RNAs and transposable elements (TEs) can also encode tumor-specific neo-antigens. Here, we investigate the presentation and immunogenicity of tumor antigens derived from noncanonical mRNA splicing events between coding exons and TEs. Comparing human non-small cell lung cancer (NSCLC) and diverse healthy tissues, we identified a subset of splicing junctions that is both tumor specific and shared across patients. We used HLA-I peptidomics to identify peptides encoded by tumor-specific junctions in primary NSCLC samples and lung tumor cell lines. Recurrent junction-encoded peptides were immunogenic in vitro, and CD8+ T cells specific for junction-encoded epitopes were present in tumors and tumor-draining lymph nodes from patients with NSCLC. We conclude that noncanonical splicing junctions between exons and TEs represent a source of recurrent, immunogenic tumor-specific antigens in patients with NSCLC.

Translation Rescue by Targeting Ppp1r15a through Its Upstream Open Reading Frame in Sepsis-Induced Acute Kidney Injury in a Murine Model

BACKGROUND

Translation shutdown is a hallmark of late-phase, sepsis-induced kidney injury. Methods for controlling protein synthesis in the kidney are limited. Reversing translation shutdown requires dephosphorylation of the eukaryotic initiation factor 2 (eIF2) subunit eIF2 α ; this is mediated by a key regulatory molecule, protein phosphatase 1 regulatory subunit 15A (Ppp1r15a), also known as GADD34.

METHODS

To study protein synthesis in the kidney in a murine endotoxemia model and investigate the feasibility of translation control in vivo by boosting the protein expression of Ppp1r15a, we combined multiple tools, including ribosome profiling (Ribo-seq), proteomics, polyribosome profiling, and antisense oligonucleotides, and a newly generated Ppp1r15a knock-in mouse model and multiple mutant cell lines.

RESULTS

We report that translation shutdown in established sepsis-induced kidney injury is brought about by excessive eIF2 α phosphorylation and sustained by blunted expression of the counter-regulatory phosphatase Ppp1r15a. We determined the blunted Ppp1r15a expression persists because of the presence of an upstream open reading frame (uORF). Overcoming this barrier with genetic and antisense oligonucleotide approaches enabled the overexpression of Ppp1r15a, which salvaged translation and improved kidney function in an endotoxemia model. Loss of this uORF also had broad effects on the composition and phosphorylation status of the immunopeptidome-peptides associated with the MHC-that extended beyond the eIF2 α axis.

CONCLUSIONS

We found Ppp1r15a is translationally repressed during late-phase sepsis because of the existence of an uORF, which is a prime therapeutic candidate for this strategic rescue of translation in late-phase sepsis. The ability to accurately control translation dynamics during sepsis may offer new paths for the development of therapies at codon-level precision.

PODCAST

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Post-translational modifications reshape the antigenic landscape of the MHC I immunopeptidome in tumors

Post-translational modification (PTM) of antigens provides an additional source of specificities targeted by immune responses to tumors or pathogens, but identifying antigen PTMs and assessing their role in shaping the immunopeptidome is challenging. Here we describe the Protein Modification Integrated Search Engine (PROMISE), an antigen discovery pipeline that enables the analysis of 29 different PTM combinations from multiple clinical cohorts and cell lines. We expanded the antigen landscape, uncovering human leukocyte antigen class I binding motifs defined by specific PTMs with haplotype-specific binding preferences and revealing disease-specific modified targets, including thousands of new cancer-specific antigens that can be shared between patients and across cancer types. Furthermore, we uncovered a subset of modified peptides that are specific to cancer tissue and driven by post-translational changes that occurred in the tumor proteome. Our findings highlight principles of PTM-driven antigenicity, which may have broad implications for T cell-mediated therapies in cancer and beyond.

Challenges in neoantigen-directed therapeutics

A fundamental prerequisite for the efficacy of cancer immunotherapy is the presence of functional, antigen-specific T cells within the tumor. Neoantigen-directed therapy is a promising strategy that aims at targeting the host's immune response against tumor-specific antigens, thereby eradicating cancer cells. Initial forays have been made in clinical environments utilizing vaccines and adoptive cell therapy; however, many challenges lie ahead. We provide an in-depth overview of the current state of the field with an emphasis on in silico neoantigen discovery and the clinical aspects that need to be addressed to unlock the full potential of this therapy.

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.

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).

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.