CIITA-Transduced Glioblastoma Cells Uncover a Rich Repertoire of Clinically Relevant Tumor-Associated HLA-II Antigens

Deleterious KOs in the HLA Class I Antigen Processing and Presentation Machinery Induce Distinct Changes in the Immunopeptidome

The human leukocyte antigen (HLA) processing and presentation machinery (APPM) is altered in various diseases and in response to drug treatments. Defects in the machinery may change presentation levels or alter the repertoire of presented peptides, globally or in an HLA allele-restricted manner, with direct implications for adaptive immunity. In this study, we investigated the immunopeptidome landscape across a panel of isogenic HAP1 cell line clones, each with a KO of a single gene encoding a key protein in the APPM, including B2M, TAP1, TAP2, TAPBP, IRF2, PDIA3, ERAP1, GANAB, SPPL3, CANX, and CALR. We applied immunopeptidomics and proteomics to assess the successful gene KOs on the protein level, understand how these proteins participate in antigen presentation, and contextualize protein expression and antigen presentation. We validated the absence of the KO proteins in the respective samples and found that knocking-out an APPM component leads to the loss of peptide subsets that are normally presented on the control wildtype cells. We assessed the immunopeptidomes qualitatively and quantitatively, considering factors like peptide diversity, peptide length distribution, and binding affinity to the endogenously expressed HLA alleles in HAP1 cells. We demonstrated prominent HLA allele-restricted alterations in several KO conditions. The absence of CALR, CANX, and TAP1 led to significant changes in HLA allele-specific presentation levels. Overall, this work represents the first systematic analysis of how the absence of individual APPM components, knocked out in a single cell line under controlled conditions, affects the immunopeptidome. This approach could facilitate the creation of predictive tools capable of prioritizing HLA-bound peptides likely to be presented when presentation defects occur, such as in cancer and viral infections.

HLAPepBinder: An Ensemble Model for The Prediction Of HLA-Peptide Binding

Background

Human leukocyte antigens (HLAs) play a pivotal role in orchestrating the host's immune response, offering a promising avenue with reduced adverse effects compared to conventional treatments. Cancer immunotherapies use HLA class I molecules for T cells to recognize tumor antigens, emphasizing the importance of identifying peptides that bind effectively to HLAs. Computer modeling of HLA-peptide binding speeds up the search for immunogenic epitopes, which enhances the prospect of personalized medicine and targeted therapies. The Immune Epitope Database (IEDB) is a vital repository, housing curated immune epitope data and prediction tools for HLA-peptide binding. It can be challenging for immunologists to choose the best tool from the IEDB for predicting HLA-peptide binding. This has led to the creation of consensus-based methods that combine the results of several predictors. One of the major challenges in these methods is how to effectively integrate the results from multiple predictors.

Objectives

Previous consensus-based methods integrate at most three tools by relying on simple strategies, such as selecting prediction methods based on their proximity to HLA in training data. In this study, we introduce HLAPepBinder, a novel consensus approach using ensemble machine learning methods to predict HLA-peptide binding, addressing the challenges biologists face in model selection.

Materials and Methods

The key contribution is the development of an automatic pipeline named HLAPepBinder that integrates the predictions of multiple models using a random forest approach. Unlike previous approaches, HLAPepBinder seamlessly integrates results from all nine predictors, providing a comprehensive and accurate predictive framework. By combining the strengths of these models, HLAPepBinder eliminates the need for manual model selection, providing a streamlined and reliable solution for biologists.

Results

HLAPepBinder offers a practical and high-performing alternative for HLA-peptide binding predictions, outperforming both traditional methods and complex deep learning models. Compared to the recently introduced transformer-based model, TranspHLA, which requires substantial computational resources, HLAPepBinder demonstrates superior performance in both prediction accuracy and resource efficiency. Notably, it operates effectively in limited computational environments, making it accessible to researchers with minimal resources. The codes are available online at https://github.com/CBRC-lab/HLAPepBinder.

Conclusion

Our study introduces a novel ensemble-learning model designed to enhance the accuracy and efficiency of HLA-peptide binding predictions. Due to the lack of reliable negative data and the typical assumption of unknown interactions being negative, we focus on analyzing the unknown HLA-peptide bindings in the test set that our model predicts with 100% certainty as positive bindings. Using HLAPepBinder, we identify 26 HLA-peptide pairs with absolute prediction confidence. These predictions are validated through a multi-step pipeline involving literature review, BLAST sequence similarity analysis, and molecular docking studies. This comprehensive validation process highlights HLAPepBinder's ability to make accurate and reliable predictions, contributing significantly to advancements in immunotherapy and vaccine development.

Long-range alternative splicing contributes to neoantigen specificity in glioblastoma

Recent advances in neoantigen research have accelerated the development of immunotherapies for cancers, such as glioblastoma (GBM). Neoantigens resulting from genomic mutations and dysregulated alternative splicing have been studied in GBM. However, these studies have primarily focused on annotated alternatively-spliced transcripts, leaving non-annotated transcripts largely unexplored. Circular ribonucleic acids (circRNAs), abnormally regulated in tumors, are correlated with the presence of non-annotated linear transcripts with exon skipping events. But the extent to which these linear transcripts truly exist and their functions in cancer immunotherapies remain unknown. Here, we found the ubiquitous co-occurrence of circRNA biogenesis and alternative splicing across various tumor types, resulting in large amounts of long-range alternatively-spliced transcripts (LRs). By comparing tumor and healthy tissues, we identified tumor-specific LRs more abundant in GBM than in normal tissues and other tumor types. This may be attributable to the upregulation of the protein quaking in GBM, which is reported to promote circRNA biogenesis. In total, we identified 1057 specific and recurrent LRs in GBM. Through in silico translation prediction and MS-based immunopeptidome analysis, 16 major histocompatibility complex class I-associated peptides were identified as potential immunotherapy targets in GBM. This study revealed long-range alternatively-spliced transcripts specifically upregulated in GBM may serve as recurrent, immunogenic tumor-specific antigens.

Neoantigen-specific T cell help outperforms non-specific help in multi-antigen DNA vaccination against cancer

CD4+ T helper antigens are essential components of cancer vaccines, but the relevance of the source of these MHC class II-restricted antigens remains underexplored. To compare the effectiveness of tumor-specific versus tumor-unrelated helper antigens, we designed three DNA vaccines for the murine MC-38 colon carcinoma, encoding CD8+ T cell neoantigens alone (noHELP) or in combination with either "universal" helper antigens (uniHELP) or helper neoantigens (neoHELP). Both types of helped vaccines increased the frequency of vaccine-induced CD8+ T cells, and particularly uniHELP increased the fraction of KLRG1+ and PD-1low effector cells. However, when mice were subsequently injected with MC-38 cells, only neoHELP vaccination resulted in significantly better tumor control than noHELP. In contrast to uniHELP, neoHELP-induced tumor control was dependent on the presence of CD4+ T cells, while both vaccines relied on CD8+ T cells. In line with this, neoHELP variants containing wild-type counterparts of the CD4+ or CD8+ T cell neoantigens displayed reduced tumor control. These data indicate that optimal personalized cancer vaccines should include MHC class II-restricted neoantigens to elicit tumor-specific CD4+ T cell help.

Novel vaccination strategies based on optimal stimulation of CD4+ T helper cells for the treatment of oral squamous cell carcinoma

Oral Squamous Cell Carcinoma (OSCC) is the most common malignant tumor of the oral cavity. Despite recent advances in the field of oral cancer therapy, including the introduction of immunotherapeutic approaches, the 5-year survival rate remains steadily assessed around 50%. Thus, there is an urgent need for new therapeutic strategies. After the characterization of the immune phenotype of three human OSCC cell lines (CAL-27, SCC-25, and SCC-4) and one mouse OSCC cell line (MOC2) showing their similarities to resected patient tumors, we explored for the first time an experimental preclinical model of therapeutic vaccination with mouse OSCC MOC2 cell line stably expressing MHC class II antigens after CIITA gene transfection (MOC2-CIITA). Mice injected with MOC2-CIITA reject or strongly retard tumor growth; more importantly, vaccinated animals that fully reject MOC2-CIITA tumors display anti-tumor immunological memory protective against challenge with parental MOC2 tumor cells. Further experiments of adoptive cell transfer or in vivo cell depletion show that both CD4+ and CD8+ T lymphocytes prove fundamental in tumor rejection. This unprecedented approach for oral cancer opens the way for possible future translation of novel immunotherapeutic strategies to the human setting for the treatment of this tumor.

The 2023 Report on the Proteome from the HUPO Human Proteome Project

Since 2010, the Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify the protein parts list and (2) to make proteomics an integral part of multiomics studies of human health and disease. The HPP relies on international collaboration, data sharing, standardized reanalysis of MS data sets by PeptideAtlas and MassIVE-KB using HPP Guidelines for quality assurance, integration and curation of MS and non-MS protein data by neXtProt, plus extensive use of antibody profiling carried out by the Human Protein Atlas. According to the neXtProt release 2023-04-18, protein expression has now been credibly detected (PE1) for 18,397 of the 19,778 neXtProt predicted proteins coded in the human genome (93%). Of these PE1 proteins, 17,453 were detected with mass spectrometry (MS) in accordance with HPP Guidelines and 944 by a variety of non-MS methods. The number of neXtProt PE2, PE3, and PE4 missing proteins now stands at 1381. Achieving the unambiguous identification of 93% of predicted proteins encoded from across all chromosomes represents remarkable experimental progress on the Human Proteome parts list. Meanwhile, there are several categories of predicted proteins that have proved resistant to detection regardless of protein-based methods used. Additionally there are some PE1-4 proteins that probably should be reclassified to PE5, specifically 21 LINC entries and ∼30 HERV entries; these are being addressed in the present year. Applying proteomics in a wide array of biological and clinical studies ensures integration with other omics platforms as reported by the Biology and Disease-driven HPP teams and the antibody and pathology resource pillars. Current progress has positioned the HPP to transition to its Grand Challenge Project focused on determining the primary function(s) of every protein itself and in networks and pathways within the context of human health and disease.

The HLA-II immunopeptidome of SARS-CoV-2

Targeted synthetic vaccines have the potential to transform our response to viral outbreaks, yet the design of these vaccines requires a comprehensive knowledge of viral immunogens. Here, we report severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) peptides that are naturally processed and loaded onto human leukocyte antigen-II (HLA-II) complexes in infected cells. We identify over 500 unique viral peptides from canonical proteins as well as from overlapping internal open reading frames. Most HLA-II peptides colocalize with known CD4+ T cell epitopes in coronavirus disease 2019 patients, including 2 reported immunodominant regions in the SARS-CoV-2 membrane protein. Overall, our analyses show that HLA-I and HLA-II pathways target distinct viral proteins, with the structural proteins accounting for most of the HLA-II peptidome and nonstructural and noncanonical proteins accounting for the majority of the HLA-I peptidome. These findings highlight the need for a vaccine design that incorporates multiple viral elements harboring CD4+ and CD8+ T cell epitopes to maximize vaccine effectiveness.

Limited Effects of Class II Transactivator-Based Immunotherapy in Murine and Human Glioblastoma

BACKGROUND

The major histocompatibility complex type II is downregulated in glioblastoma (GB) due to the silencing of the major transcriptional regulator class II transactivator (CIITA). We investigated the pro-immunogenic potential of CIITA overexpression in mouse and human GB.

METHODS

The intracerebral growth of wildtype GL261-WT cells was assessed following contralateral injection of GL261-CIITA cells or flank injections with GL261-WT or GL261-CIITA cells. Splenocytes obtained from mice implanted intracerebrally with GL261-WT, GL261-CIITA cells or phosphate buffered saline (PBS) were transferred to other mice and subsequently implanted intracerebrally with GL261-WT. Human GB cells and (syngeneic) GB-infiltrating immune cells were isolated from surgical samples and co-cultured with GB cells expressing CIITA or not, followed by RT-qPCR assessment of the expression of key immune regulators.

RESULTS

Intracerebral vaccination of GL261-CIITA significantly reduced the subsequent growth of GL261-WT cells implanted contralaterally. Vaccination with GL261-WT or -CIITA subcutaneously, however, equivalently retarded the intracerebral growth of GL261 cells. Adoptive cell transfer experiments showed a similar antitumor potential of lymphocytes harvested from mice implanted intracerebrally with GL261-WT or -CIITA. Human GB-infiltrating myeloid cells and lymphocytes were not activated when cultured with CIITA-expressing GB cells. Tumor-infiltrating NK cells remained mostly inactivated when in co-culture with GB cells, regardless of CIITA.

CONCLUSION

these results question the therapeutic potential of CIITA-mediated immunotherapy in glioblastoma.

Carboxylated graphene quantum dots-mediated photothermal therapy enhances drug-membrane permeability, ROS production, and the immune system recruitment on 3D glioblastoma models

Graphene quantum dots (GQDs) are biocompatible nanoparticles employed in biomedical field, thanks to their size and photophysical properties. GQDs have shown the capability to cross biological barriers, including the blood–brain barrier, which makes them promising agents for brain diseases therapy. It has been shown that surface-functionalized GQDs enhance membrane fluidity and intracellular uptake, exerting a synergistic effect with antitumor drugs at subtherapeutic doses. Here, we tested GQDs effects in combination with chemotherapeutic agents doxorubicin and temozolomide, on a complex 3D spheroid model of glioblastoma. We observed that the capability of GQDs to absorb and convert near-infrared light into heat is a key factor in membrane permeability enhancement on 3D model. This non-invasive therapeutic strategy named photothermal therapy (PTT), combined to chemotherapy at subtherapeutic doses, significantly increased the effect of antitumor drugs by reducing tumor growth and viability. Furthermore, the increase in membrane permeability due to GQDs-mediated PTT enhanced the release of reactive oxygen species with strong migration of the immune system towards irradiated cancer spheroids. Our data indicate that the increase in membrane permeability can enhance the efficacy of antitumor drugs at subtherapeutic doses against glioblastoma, reducing side effects, and directing immune response, ultimately improving quality of life for patients.

Human dendritic cell subsets in the glioblastoma-associated microenvironment

Glioblastoma (GBM) is the most aggressive type of glioma (Grade IV). The presence of cytotoxic T lymphocyte (CTLs) has been associated with improved outcomes in patients with GBM, and it is believed that the activation of CTLs by dendritic cells may play a critical role in controlling the growth of GBM. DCs are professional antigen-presenting cells (APC) that orchestrate innate and adaptive anti-GBM immunity. DCs can subsequently differentiate into plasmacytoid DCs (pDC), conventional DC1 (cDC1), conventional (cDC2), and monocyte-derived DCs (moDC) depending on environmental exposure. The different subsets of DCs exhibit varying functional capabilities in antigen presentation and T cell activation in producing an antitumor response. In this review, we focus on recent studies describing the phenotypic and functional characteristics of DC subsets in humans and their respective antitumor immunity and immunotolerance roles in the GBM-associated microenvironment. The critical components of crosstalk between DC subsets that contribute significantly to GBM-specific immune responses are also highlighted in this review with reference to the latest literature. Since DCs could be prime targets for therapeutic intervention, it is worth summarizing the relevance of DC subsets with respect to GBM-associated immunologic tolerance and their therapeutic potential.

The NLR member CIITA: Master controller of adaptive and intrinsic immunity and unexpected tool in cancer immunotherapy

Human nucleotide-binding oligomerization domain (NOD)-like receptors (NLR) include a large family of proteins that have important functions in basic physio-pathological processes like inflammation, cell death and regulation of transcription of key molecules for the homeostasis of the immune system. They are all characterized by a common backbone structure (the STAND ATPase module consisting in a nucleotide-binding domain (NBD), an helical domain 1 (HD1) and a winged helix domain (WHD), used by both prokaryotes and eukaryotes as defense mechanism. In this review, we will focus on the MHC class II transactivator (CIITA), the master regulator of MHC class II (MHC-II) gene expression and the founding member of NLR. Although a consistent part of the described NLR family components is often recalled as innate or intrinsic immune sensors, CIITA in fact occupies a special place as a unique example of regulator of both intrinsic and adaptive immunity. The description of the discovery of CIITA and the genetic and molecular characterization of its expression will be followed by the most recent studies that have unveiled this dual role of CIITA, key molecule in intrinsic immunity as restriction factor for human retroviruses and precious tool to induce the expression of MHC-II molecules in cancer cells, rendering them potent surrogate antigen presenting cells (APC) for their own tumor antigens.

Immunopeptidome profiling of human coronavirus OC43-infected cells identifies CD4 T-cell epitopes specific to seasonal coronaviruses or cross-reactive with SARS-CoV-2

Seasonal "common-cold" human coronaviruses are widely spread throughout the world and are mainly associated with mild upper respiratory tract infections. The emergence of highly pathogenic coronaviruses MERS-CoV, SARS-CoV, and most recently SARS-CoV-2 has prompted increased attention to coronavirus biology and immunopathology, but the T-cell response to seasonal coronaviruses remains largely uncharacterized. Here we report the repertoire of viral peptides that are naturally processed and presented upon infection of a model cell line with seasonal coronavirus OC43. We identified MHC-bound peptides derived from each of the viral structural proteins (spike, nucleoprotein, hemagglutinin-esterase, membrane, and envelope) as well as non-structural proteins nsp3, nsp5, nsp6, and nsp12. Eighty MHC-II bound peptides corresponding to 14 distinct OC43-derived epitopes were identified, including many at very high abundance within the overall MHC-II peptidome. Fewer and less abundant MHC-I bound OC43-derived peptides were observed, possibly due to MHC-I downregulation induced by OC43 infection. The MHC-II peptides elicited low-abundance recall T-cell responses in most donors tested. In vitro assays confirmed that the peptides were recognized by CD4+ T cells and identified the presenting HLA alleles. T-cell responses cross-reactive between OC43, SARS-CoV-2, and the other seasonal coronaviruses were confirmed in samples of peripheral blood and peptide-expanded T-cell lines. Among the validated epitopes, spike protein S903-917 presented by DPA1*01:03/DPB1*04:01 and S1085-1099 presented by DRB1*15:01 shared substantial homology to other human coronaviruses, including SARS-CoV-2, and were targeted by cross-reactive CD4 T cells. Nucleoprotein N54-68 and hemagglutinin-esterase HE128-142 presented by DRB1*15:01 and HE259-273 presented by DPA1*01:03/DPB1*04:01 are immunodominant epitopes with low coronavirus homology that are not cross-reactive with SARS-CoV-2. Overall, the set of naturally processed and presented OC43 epitopes comprise both OC43-specific and human coronavirus cross-reactive epitopes, which can be used to follow CD4 T-cell cross-reactivity after infection or vaccination, and to guide selection of epitopes for inclusion in pan-coronavirus vaccines.

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.

Unraveling the glycosylated immunopeptidome with HLA-Glyco

Recent interest in targeted therapies has been sparked by the study of MHC-associated peptides (MAPs) that undergo post-translational modifications (PTMs), particularly glycosylation. In this study, we introduce a fast computational workflow that merges the MSFragger-Glyco search algorithm with a false discovery rate control for glycopeptide analysis from mass spectrometry-based immunopeptidome data. By analyzing eight large-scale publicly available studies, we find that glycosylated MAPs are predominantly presented by MHC class II. Here, we present HLA-Glyco, a comprehensive resource containing over 3,400 human leukocyte antigen (HLA) class II N-glycopeptides from 1,049 distinct protein glycosylation sites. This resource provides valuable insights, including high levels of truncated glycans, conserved HLA-binding cores, and differences in glycosylation positional specificity between HLA allele groups. We integrate the workflow within the FragPipe computational platform and provide HLA-Glyco as a free web resource. Overall, our work provides a valuable tool and resource to aid the nascent field of glyco-immunopeptidomics.

The HLA-II immunopeptidome of SARS-CoV-2

Targeted synthetic vaccines have the potential to transform our response to viral outbreaks; yet the design of these vaccines requires a comprehensive knowledge of viral immunogens, including T-cell epitopes. Having previously mapped the SARS-CoV-2 HLA-I landscape, here we report viral peptides that are naturally processed and loaded onto HLA-II complexes in infected cells. We identified over 500 unique viral peptides from canonical proteins, as well as from overlapping internal open reading frames (ORFs), revealing, for the first time, the contribution of internal ORFs to the HLA-II peptide repertoire. Most HLA-II peptides co-localized with the known CD4+ T cell epitopes in COVID-19 patients. We also observed that two reported immunodominant regions in the SARS-CoV-2 membrane protein are formed at the level of HLA-II presentation. Overall, our analyses show that HLA-I and HLA-II pathways target distinct viral proteins, with the structural proteins accounting for most of the HLA-II peptidome and non-structural and non-canonical proteins accounting for the majority of the HLA-I peptidome. These findings highlight the need for a vaccine design that incorporates multiple viral elements harboring CD4+ and CD8+ T cell epitopes to maximize the vaccine effectiveness.

Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes

CD4⁺ T cells orchestrate the adaptive immune response against pathogens and cancer by recognizing epitopes presented on class II major histocompatibility complex (MHC-II) molecules. The high polymorphism of MHC-II genes represents an important hurdle toward accurate prediction and identification of CD4⁺ T cell epitopes. Here we collected and curated a dataset of 627,013 unique MHC-II ligands identified by mass spectrometry. This enabled us to precisely determine the binding motifs of 88 MHC-II alleles across humans, mice, cattle, and chickens. Analysis of these binding specificities combined with X-ray crystallography refined our understanding of the molecular determinants of MHC-II motifs and revealed a widespread reverse-binding mode in HLA-DP ligands. We then developed a machine-learning framework to accurately predict binding specificities and ligands of any MHC-II allele. This tool improves and expands predictions of CD4⁺ T cell epitopes and enables us to discover viral and bacterial epitopes following the aforementioned reverse-binding mode.

Protective anti-tumor vaccination against glioblastoma expressing the MHC class II transactivator CIITA

Glioblastoma is the most malignant tumor of the central nervous system. Current treatments based on surgery, chemotherapy, and radiotherapy, and more recently on selected immunological approaches, unfortunately produce dismal outcomes, and less than 2% of patients survive after 5 years. Thus, there is an urgent need for new therapeutic strategies. Here, we report unprecedented positive results in terms of protection from glioblastoma growth in an animal experimental system after vaccination with glioblastoma GL261 cells stably expressing the MHC class II transactivator CIITA. Mice injected with GL261-CIITA express de novo MHC class II molecules and reject or strongly retard tumor growth as a consequence of rapid infiltration with CD4+ and CD8+ T cells. Importantly, mice vaccinated with GL261-CIITA cells by injection in the right brain hemisphere strongly reject parental GL261 tumors injected in the opposite brain hemisphere, indicating not only the acquisition of anti-tumor immune memory but also the capacity of immune T cells to migrate within the brain, overcoming the blood–brain barrier. GL261-CIITA cells are a potent anti-glioblastoma vaccine, stimulating a protective adaptive anti-tumor immune response in vivo as a consequence of CIITA-driven MHC class II expression and consequent acquisition of surrogate antigen-presenting function toward tumor-specific CD4+ Th cells. This unprecedented approach for glioblastoma demonstrates the feasibility of novel immunotherapeutic strategies for potential application in the clinical setting.

Single-cell RNA-seq-based proteogenomics identifies glioblastoma-specific transposable elements encoding HLA-I-presented peptides

We analyze transposable elements (TEs) in glioblastoma (GBM) patients using a proteogenomic pipeline that combines single-cell transcriptomics, bulk RNA sequencing (RNA-seq) samples from tumors and healthy-tissue cohorts, and immunopeptidomic samples. We thus identify 370 human leukocyte antigen (HLA)-I-bound peptides encoded by TEs differentially expressed in GBM. Some of the peptides are encoded by repeat sequences from intact open reading frames (ORFs) present in up to several hundred TEs from recent long interspersed nuclear element (LINE)-1, long terminal repeat (LTR), and SVA subfamilies. Other HLA-I-bound peptides are encoded by single copies of TEs from old subfamilies that are expressed recurrently in GBM tumors and not expressed, or very infrequently and at low levels, in healthy tissues (including brain). These peptide-coding, GBM-specific, highly recurrent TEs represent potential tumor-specific targets for cancer immunotherapies.

Tryptophan depletion results in tryptophan-to-phenylalanine substitutants

Activated T cells secrete interferon-γ, which triggers intracellular tryptophan shortage by upregulating the indoleamine 2,3-dioxygenase 1 (IDO1) enzyme^1-4. Here we show that despite tryptophan depletion, in-frame protein synthesis continues across tryptophan codons. We identified tryptophan-to-phenylalanine codon reassignment (W>F) as the major event facilitating this process, and pinpointed tryptophanyl-tRNA synthetase (WARS1) as its source. We call these W>F peptides 'substitutants' to distinguish them from genetically encoded mutants. Using large-scale proteomics analyses, we demonstrate W>F substitutants to be highly abundant in multiple cancer types. W>F substitutants were enriched in tumours relative to matching adjacent normal tissues, and were associated with increased IDO1 expression, oncogenic signalling and the tumour-immune microenvironment. Functionally, W>F substitutants can impair protein activity, but also expand the landscape of antigens presented at the cell surface to activate T cell responses. Thus, substitutants are generated by an alternative decoding mechanism with potential effects on gene function and tumour immunoreactivity.

HLA Allele-Specific Quantitative Profiling of Type 1 Diabetic B Lymphocyte Immunopeptidome

Peptide ligands presented by human leukocyte antigen (HLA) molecules on the cell surface represent the immunopeptidome that could be utilized for identification of antigenic peptides for immunotherapy and prevention of autoimmune diseases. Although T-cells are well-known key players in the destruction of pancreatic beta-cells in type 1 diabetes (T1D), increasing evidence points toward a role for B-cells in disease pathogenesis. However, as antigen presenting cells, little is known about the comprehensive immunopeptidome of B cells and their changes in the context of T1D. We performed HLA allele-specific quantitative immunopeptidomics using B lymphocytes derived from T1D patients and healthy controls. Hundreds of HLA-I and HLA-II immunopeptides were identified as differentially regulated in T1D per HLA allele for B cells sharing identical HLA alleles. The results were further validated using additional T1D and healthy B cells with partially overlapped HLA alleles. Differentially expressed immunopeptides were confirmed with targeted proteomics and for reactivity using known T-cell assays in the immune epitope database. Considering samples with identical HLA alleles are difficult to obtain for T1D and other similar HLA-restricted diseases, our work represents a viable approach to better understand HLA allele-specific antigen presentation and may facilitate identification of immunopeptides for therapeutic applications in autoimmune diseases. Data are available via ProteomeXchange with identifier PXD026184.

Beneficial autoimmunity improves cancer prognosis

Many tumour antigens that do not arise from cancer cell-specific mutations are targets of humoral and cellular immunity despite their expression on non-malignant cells. Thus, in addition to the expected ability to detect mutations and stress-associated shifts in the immunoproteome and immunopeptidome (the sum of MHC class I-bound peptides) unique to malignant cells, the immune system also recognizes antigens expressed in non-malignant cells, which can result in autoimmune reactions against non-malignant cells from the tissue of origin. These autoimmune manifestations include, among others, vitiligo, thyroiditis and paraneoplastic syndromes, concurrent with melanoma, thyroid cancer and non-small-cell lung cancer, respectively. Importantly, despite the undesirable effects of these symptoms, such events can have prognostic value and correlate with favourable disease outcomes, suggesting 'beneficial autoimmunity'. Similarly, the occurrence of dermal and endocrine autoimmune adverse events in patients receiving immune-checkpoint inhibitors can have a positive predictive value for therapeutic outcomes. Neoplasias derived from stem cells deemed 'not essential' for survival (such as melanocytes, thyroid cells and most cells in sex-specific organs) have a particularly good prognosis, perhaps because the host can tolerate autoimmune reactions that destroy tumour cells at some cost to non-malignant tissues. In this Perspective, we discuss examples of spontaneous as well as therapy-induced autoimmunity that correlate with favourable disease outcomes and make a strong case in favour of this 'beneficial autoimmunity' being important not only in patients with advanced-stage disease but also in cancer immunosurveillance.

Distinct Molecular Mechanisms of Altered HLA Class II Expression in Malignant Melanoma

BACKGROUND

The human leukocyte antigen (HLA) class II molecules are constitutively expressed in some melanoma, but the underlying molecular mechanisms have not yet been characterized.

METHODS

The expression of HLA class II antigen processing machinery (APM) components was determined in melanoma samples by qPCR, Western blot, flow cytometry and immunohistochemistry. Immunohistochemical and TCGA datasets were used for correlation of HLA class II expression to tumor grading, T-cell infiltration and patients' survival.

RESULTS

The heterogeneous HLA class II expression in melanoma samples allowed us to characterize four distinct phenotypes. Phenotype I totally lacks constitutive HLA class II surface expression, which is inducible by interferon-gamma (IFN-γ); phenotype II expresses low basal surface HLA class II that is further upregulated by IFN-γ; phenotype III lacks constitutive and IFN-γ controlled HLA class II expression, but could be induced by epigenetic drugs; and in phenotype IV, lack of HLA class II expression is not recovered by any drug tested. High levels of HLA class II APM component expression were associated with an increased intra-tumoral CD4+ T-cell density and increased patients' survival.

CONCLUSIONS

The heterogeneous basal expression of HLA class II antigens and/or APM components in melanoma cells is caused by distinct molecular mechanisms and has clinical relevance.

MS-Based HLA-II Peptidomics Combined With Multiomics Will Aid the Development of Future Immunotherapies

Immunotherapies have emerged to treat diseases by selectively modulating a patient's immune response. Although the roles of T and B cells in adaptive immunity have been well studied, it remains difficult to select targets for immunotherapeutic strategies. Because human leukocyte antigen class II (HLA-II) peptides activate CD4+ T cells and regulate B cell activation, proliferation, and differentiation, these peptide antigens represent a class of potential immunotherapy targets and biomarkers. To better understand the molecular basis of how HLA-II antigen presentation is involved in disease progression and treatment, systematic HLA-II peptidomics combined with multiomic analyses of diverse cell types in healthy and diseased states is required. For this reason, MS-based innovations that facilitate investigations into the interplay between disease pathologies and the presentation of HLA-II peptides to CD4+ T cells will aid in the development of patient-focused immunotherapies.