Immunopeptidomic Profiling of HLA-A2-Positive Triple Negative Breast Cancer Identifies Potential Immunotherapy Target Antigens

SILAC-based quantification reveals modulation of the immunopeptidome in BRAF and MEK inhibitor sensitive and resistant melanoma cells

Background

The immunopeptidome is constantly monitored by T cells to detect foreign or aberrant HLA peptides. It is highly dynamic and reflects the current cellular state, enabling the immune system to recognize abnormal cellular conditions, such as those present in cancer cells. To precisely determine how changes in cellular processes, such as those induced by drug treatment, affect the immunopeptidome, quantitative immunopeptidomics approaches are essential.

Methods

To meet this need, we developed a pulsed SILAC-based method for quantitative immunopeptidomics. Metabolic labeling with lysine, arginine, and leucine enabled isotopic labeling of nearly all HLA peptides across all allotypes (> 90% on average). We established a data analysis workflow that integrates the de novo sequencing-based tool Peptide-PRISM for comprehensive HLA peptide identification with MaxQuant for accurate quantification.

Results

We employed this strategy to explore the modulation of the immunopeptidome upon MAPK pathway inhibition (MAPKi) and to investigate alterations associated with early cellular responses to inhibitor treatment and acquired resistance to MAPKi. Our analyses demonstrated significant changes in the immunopeptidome early during MAPKi treatment and in the resistant state. Moreover, we identified putative tumor-specific cryptic HLA peptides linked to these processes that might represent exploitable targets for cancer immunotherapy.

Conclusions

We have developed a new mass spectrometric approach that allowed us to investigate the effects of common MAPK inhibitors on the immunopeptidome of melanoma cells. This finally led to the discovery of new potential targets for cancer immunotherapy.

Update on current and new potential immunotherapies in breast cancer, from bench to bedside

Impressive advances have been seen in cancer immunotherapy during the last years. Although breast cancer (BC) has been long considered as non-immunogenic, immunotherapy for the treatment of BC is now emerging as a new promising therapeutic approach with considerable potential. This is supported by a plethora of completed and ongoing preclinical and clinical studies in various types of immunotherapies. However, a significant gap between clinical oncology and basic cancer research impairs the understanding of cancer immunology and immunotherapy, hampering cancer therapy research and development. To exploit the accumulating available data in an optimal way, both fundamental mechanisms at play in BC immunotherapy and its clinical pitfalls must be integrated. Then, clinical trials must be critically designed with appropriate combinations of conventional and immunotherapeutic strategies. While there is room for major improvement, this updated review details the immunotherapeutic tools available to date, from bench to bedside, in the hope that this will lead to rethinking and optimizing standards of care for BC patients.

The SysteMHC Atlas v2.0, an updated resource for mass spectrometry-based immunopeptidomics

The SysteMHC Atlas v1.0 was the first public repository dedicated to mass spectrometry-based immunopeptidomics. Here we introduce a newly released version of the SysteMHC Atlas v2.0 (https://systemhc.sjtu.edu.cn), a comprehensive collection of 7190 MS files from 303 allotypes. We extended and optimized a computational pipeline that allows the identification of MHC-bound peptides carrying on unexpected post-translational modifications (PTMs), thereby resulting in 471K modified peptides identified over 60 distinct PTM types. In total, we identified approximately 1.0 million and 1.1 million unique peptides for MHC class I and class II immunopeptidomes, respectively, indicating a 6.8-fold increase and a 28-fold increase to those in v1.0. The SysteMHC Atlas v2.0 introduces several new features, including the inclusion of non-UniProt peptides, and the incorporation of several novel computational tools for FDR estimation, binding affinity prediction and motif deconvolution. Additionally, we enhanced the user interface, upgraded website framework, and provided external links to other resources related. Finally, we built and provided various spectral libraries as community resources for data mining and future immunopeptidomic and proteomic analysis. We believe that the SysteMHC Atlas v2.0 is a unique resource to provide key insights to the immunology and proteomics community and will accelerate the development of vaccines and immunotherapies.

Breast cancer immunopeptidomes contain numerous shared tumor antigens

Hormone receptor-positive breast cancer (HR+) is immunologically cold and has not benefited from advances in immunotherapy. In contrast, subsets of triple-negative breast cancer (TNBC) display high leukocytic infiltration and respond to checkpoint blockade. CD8+ T cells, the main effectors of anticancer responses, recognize MHC I-associated peptides (MAPs). Our work aimed to characterize the repertoire of MAPs presented by HR+ and TNBC tumors. Using mass spectrometry, we identified 57,094 unique MAPs in 26 primary breast cancer samples. MAP source genes highly overlapped between both subtypes. We identified 25 tumor-specific antigens (TSAs) mainly deriving from aberrantly expressed regions. TSAs were most frequently identified in TNBC samples and were more shared among The Cancer Genome Atlas (TCGA) database TNBC than HR+ samples. In the TNBC cohort, the predicted number of TSAs positively correlated with leukocytic infiltration and overall survival, supporting their immunogenicity in vivo. We detected 49 tumor-associated antigens (TAAs), some of which derived from cancer-associated fibroblasts. Functional expansion of specific T cell assays confirmed the in vitro immunogenicity of several TSAs and TAAs. Our study identified attractive targets for cancer immunotherapy in both breast cancer subtypes. The higher prevalence of TSAs in TNBC tumors provides a rationale for their responsiveness to checkpoint blockade.

Multiomics insights on the onset, progression, and metastatic evolution of breast cancer

Breast cancer is the most common malignant neoplasm in women. Despite progress to date, 700,000 women worldwide died of this disease in 2020. Apparently, the prognostic markers currently used in the clinic are not sufficient to determine the most appropriate treatment. For this reason, great efforts have been made in recent years to identify new molecular biomarkers that will allow more precise and personalized therapeutic decisions in both primary and recurrent breast cancers. These molecular biomarkers include genetic and post-transcriptional alterations, changes in protein expression, as well as metabolic, immunological or microbial changes identified by multiple omics technologies (e.g., genomics, epigenomics, transcriptomics, proteomics, glycomics, metabolomics, lipidomics, immunomics and microbiomics). This review summarizes studies based on omics analysis that have identified new biomarkers for diagnosis, patient stratification, differentiation between stages of tumor development (initiation, progression, and metastasis/recurrence), and their relevance for treatment selection. Furthermore, this review highlights the importance of clinical trials based on multiomics studies and the need to advance in this direction in order to establish personalized therapies and prolong disease-free survival of these patients in the future.

Journey of CAR T‑cells: Emphasising the concepts and advancements in breast cancer (Review)

Cancer is the primary and one of the most prominent causes of the rising global mortality rate, accounting for nearly 10 million deaths annually. Specific methods have been devised to cure cancerous tumours. Effective therapeutic approaches must be developed, both at the cellular and genetic level. Immunotherapy offers promising results by providing sustained remission to patients with refractory malignancies. Genetically modified T‑lymphocytic cells have emerged as a novel therapeutic approach for the treatment of solid tumours, haematological malignancies, and relapsed/refractory B‑lymphocyte malignancies as a result of recent clinical trial findings; the treatment is referred to as chimeric antigen receptor T‑cell therapy (CAR T‑cell therapy). Leukapheresis is used to remove T‑lymphocytes from the leukocytes, and CARs are created through genetic engineering. Without the aid of a major histocompatibility complex, these genetically modified receptors lyse malignant tissues by interacting directly with the carcinogen. Additionally, the outcomes of preclinical and clinical studies reveal that CAR T‑cell therapy has proven to be a potential therapeutic contender against metastatic breast cancer (BCa), triple‑negative, and HER 2+ve BCa. Nevertheless, unique toxicities, including (cytokine release syndrome, on/off‑target tumour recognition, neurotoxicities, anaphylaxis, antigen escape in BCa, and the immunosuppressive tumour microenvironment in solid tumours, negatively impact the mechanism of action of these receptors. In this review, the potential of CAR T‑cell immunotherapy and its method of destroying tumour cells is explored using data from preclinical and clinical trials, as well as providing an update on the approaches used to reduce toxicities, which may improve or broaden the effectiveness of the therapies used in BCa.

Single-cell RNA-seq and bulk RNA-seq explore the prognostic value of exhausted T cells in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains a worldwide health problem. Mounting evidence indicates that exhausted T cells play a critical role in the progress and treatment of HCC. Therefore, a detailed characterisation of exhausted T cells and their clinical significance warrants further investigation in HCC. Based on the GSE146115, we presented a comprehensive single-cell Atlas in HCC. Pseudo-time analysis revealed that tumour heterogeneity progressively increased, and the exhausted T cells gradually appeared during tumour progression. Functional enrichment analysis revealed that the evolutionary process of exhausted T cells mainly contained the pathway of cadherin binding, proteasome, cell cycle, and T cell receptor regulation of apoptosis. In the International Cancer Genome Consortium database, we divided patients into three clusters with the T cell evolution-associated genes. We found that the exhausted T cells are significantly related to poor outcomes through immunity and survival analysis. In The Cancer Genome Atlas database, the authors enrolled weighted gene co-expression network analysis, univariate Cox analysis, and Lasso Cox analysis, then screened the 19 core genes in T cells evolution and built a robust prognostic model. This study offers a fresh view on evaluating the patients' outcomes from an exhausted T cells perspective and might help clinicians develop therapeutic systems.

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.

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.

Biological Role and Aberrant Overexpression of Syntenin-1 in Cancer: Potential Role as a Biomarker and Therapeutic Target

Syntenin-1 is a 298 amino acid protein codified by the melanoma differentiation-associated gene-9 (MDA-9). Structurally, it is composed of four domains: N-terminal, PDZ1, PDZ2, and C-terminal. The PDZ domains of syntenin-1 are involved in the stability and interaction with other molecules such as proteins, glycoproteins, and lipids. Domains are also associated with several biological functions such as the activation of signaling pathways related to cell-to-cell adhesion, signaling translation, and the traffic of intracellular lipids, among others. The overexpression of syntenin-1 has been reported in glioblastoma, colorectal, melanoma, lung, prostate, and breast cancer, which promotes tumorigenesis by regulating cell migration, invasion, proliferation, angiogenesis, apoptosis, and immune response evasion, and metastasis. The overexpression of syntenin-1 in samples has been associated with worst prognostic and recurrence, whereas the use of inhibitors such as shRNA, siRNA, and PDZli showed a diminution of the tumor size and reduction in metastasis and invasion. Syntenin-1 has been suggested as a potential biomarker and therapeutic target in cancer for developing more effective diagnostic/prognostic tests or passive/active immunotherapies.

RPN2 in cancer: An overview

Oncogenes together with tumor suppresser genes are confirmed to regulate tumor phenotype in human cancers. RPN2, widely verified as an oncogene, encodes a protein that is part of an N-oligosaccharyl transferase, and is observed to be aberrantly expressed in human malignancies. Accumulating evidence unveils the vital functions of RPN2, contributing to tumorigenicity, metastasis, progression, and multi-drug resistance. Furthermore, previous studies partly indicated that RPN2 was involved in tumor progression via contributing to N-glycosylation and regulating multiple signaling pathways. In addition, RPN2 was also confirmed as a downstream target involved in tumor progression. Moreover, with demonstrated prognosis value and therapeutic target, RPN2 was also determined as a promising biomarker for forecasting patients' prognostic and therapy efficacy. In the present review, we aimed to summarize the present studies of RPN2 in cancer, and enhance the understanding of RPN2's extensive functions and clinical significances.

Mining the Immunopeptidome for Antigenic Peptides in Cancer

Although harnessing the immune system for cancer therapy has shown success, response to immunotherapy has been limited. The immunopeptidome of cancer cells presents an opportunity to discover novel antigens for immunotherapy applications. These neoantigens bind to MHC class I and class II molecules. Remarkably, the immunopeptidome encompasses protein post-translation modifications (PTMs) that may not be evident from genome or transcriptome profiling. A case in point is citrullination, which has been demonstrated to induce a strong immune response. In this review, we cover how the immunopeptidome, with a special focus on PTMs, can be utilized to identify cancer-specific antigens for immunotherapeutic applications.

A TCR mimic CAR T cell specific for NDC80 is broadly reactive with solid tumors and hematologic malignancies

Target identification for chimeric antigen receptor (CAR) T-cell therapies remains challenging due to the limited repertoire of tumor-specific surface proteins. Intracellular proteins presented in the context of cell surface HLA provide a wide pool of potential antigens targetable through T-cell receptor mimic antibodies. Mass spectrometry (MS) of HLA ligands from 8 hematologic and nonhematologic cancer cell lines identified a shared, non-immunogenic, HLA-A*02-restricted ligand (ALNEQIARL) derived from the kinetochore-associated NDC80 gene. CAR T cells directed against the ALNEQIARL:HLA-A*02 complex exhibited high sensitivity and specificity for recognition and killing of multiple cancer types, especially those of hematologic origin, and were efficacious in mouse models against a human leukemia and a solid tumor. In contrast, no toxicities toward resting or activated healthy leukocytes as well as hematopoietic stem cells were observed. This shows how MS can inform the design of broadly reactive therapeutic T-cell receptor mimic CAR T-cell therapies that can target multiple cancer types currently not druggable by small molecules, conventional CAR T cells, T cells, or antibodies.

Recent progress in antibody-based therapeutics for triple-negative breast cancer

INTRODUCTION

Triple-negative breast cancer (TNBC) is a subtype of severely aggressive breast cancer that lacks the expression of oestrogen receptor (ER), progesterone receptor and human epidermal growth factor receptor 2 (HER2) and is highly metastatic and related to a poor prognosis. Current standard treatments are still limited to systemic chemotherapy, radiotherapy, and surgical resection. More effective treatments are urgently needed.

AREAS COVERED

The immunogenicity of TNBC has provided opportunities for the development of targeted immunotherapy. In this review, we focus on the recent development in antibody-based drug modalities, including angiogenesis inhibitors, immune checkpoint inhibitors, antibody-drug conjugates, immunoconjugates, T cell-redirecting bispecific antibodies and CAR-T cells, and their mechanisms of action in TNBC.

EXPERT OPINION

At present, the treatment of TNBC is still a major challenge that needs to be addressed. Novel immunotherapies are promising opportunities for improving the management of this aggressive disease.

A Paradoxical Effect of Interleukin-32 Isoforms on Cancer

IL-32 plays a contradictory role such as tumor proliferation or suppressor in cancer development depending on the cancer type. In most cancers, it was found that the high expression of IL-32 was associated with more proliferative and progression of cancer. However, studying the isoforms of IL-32 cytokine has placed its paradoxical role into a wide range of functions based on its dominant isoform and surrounding environment. IL-32β, for example, was found mostly in different types of cancer and associated with cancer expansion. This observation is legitimate since cancer exhibits some hypoxic environment and IL-32β was known to be induced under hypoxic conditions. However, IL-32θ interacts directly with protein kinase C-δ reducing NF-κB and STAT3 levels to inhibit epithelial-mesenchymal transition (EMT). This effect could explain the different functions of IL-32 isoforms in cancer. However, pro- or antitumor activity which is dependant on obesity, gender, and age as it relates to IL-32 has yet to be studied. Obesity-related IL-32 regulation indicated the role of IL-32 in cancer metabolism and inflammation. IL-32-specific direction in cancer therapy is difficult to conclude. In this review, we address that the paradoxical effect of IL-32 on cancer is attributed to the dominant isoform, cancer type, tumor microenvironment, and genetic background. IL-32 seems to have a contradictory role in cancer. However, investigating multiple IL-32 isoforms could explain this doubt and bring us closer to using them in therapy.

Application of Proteomics in the Discovery of Radiosensitive Cancer Biomarkers

Radiation therapy remains an important component of cancer treatment. Gene-encoded proteins were the actual executors of cellular functions. Proteomic was a novel technology that can systematically analysis protein composition and measure their levels of change, this was a high throughput method, and were the import tools in the post genomic era. In recent years, rapid progress of proteomic have been made in the study of cancer mechanism, diagnosis, and treatment. This article elaborates current advances and future directions of proteomics in the discovery of radiosensitive cancer biomarkers.

Know thy immune self and non-self: Proteomics informs on the expanse of self and non-self, and how and where they arise

T cells play an important role in the adaptive immune response to a variety of infections and cancers. Initiation of a T cell mediated immune response requires antigen recognition in a process termed MHC (major histocompatibility complex) restri ction. A T cell antigen is a composite structure made up of a peptide fragment bound within the antigen-binding groove of an MHC-encoded class I or class II molecule. Insight into the precise composition and biology of self and non-self immunopeptidomes is essential to harness T cell mediated immunity to prevent, treat, or cure infectious diseases and cancers. T cell antigen discovery is an arduous task! The pioneering work in the early 1990s has made large-scale T cell antigen discovery possible. Thus, advancements in mass spectrometry coupled with proteomics and genomics technologies make possible T cell antigen discovery with ease, accuracy, and sensitivity. Yet we have only begun to understand the breadth and the depth of self and non-self immunopeptidomes because the molecular biology of the cell continues to surprise us with new secrets directly related to the source, and the processing and presentation of MHC ligands. Focused on MHC class I molecules, this review, therefore, provides a brief historic account of T cell antigen discovery and, against a backdrop of key advances in molecular cell biologic processes, elaborates on how proteogenomics approaches have revolutionised the field.

Immuno-transcriptomic profiling of extracranial pediatric solid malignancies

We perform an immunogenomics analysis utilizing whole-transcriptome sequencing of 657 pediatric extracranial solid cancer samples representing 14 diagnoses, and additionally utilize transcriptomes of 131 pediatric cancer cell lines and 147 normal tissue samples for comparison. We describe patterns of infiltrating immune cells, T cell receptor (TCR) clonal expansion, and translationally relevant immune checkpoints. We find that tumor-infiltrating lymphocytes and TCR counts vary widely across cancer types and within each diagnosis, and notably are significantly predictive of survival in osteosarcoma patients. We identify potential cancer-specific immunotherapeutic targets for adoptive cell therapies including cell-surface proteins, tumor germline antigens, and lineage-specific transcription factors. Using an orthogonal immunopeptidomics approach, we find several potential immunotherapeutic targets in osteosarcoma and Ewing sarcoma and validated PRAME as a bona fide multi-pediatric cancer target. Importantly, this work provides a critical framework for immune targeting of extracranial solid tumors using parallel immuno-transcriptomic and -peptidomic approaches.

caAtlas: An immunopeptidome atlas of human cancer

Comprehensive characterization of tumor antigens is essential for the design of cancer immunotherapies, and mass spectrometry (MS)-based immunopeptidomics enables high-throughput identification of major histocompatibility complex (MHC)-bound peptide antigens in vivo. Here we construct an immunopeptidome atlas of human cancer through an extensive collection of 43 published immunopeptidomic datasets and standardized analysis of 81.6 million MS/MS spectra using an open search engine. Our analysis greatly expands the current knowledge of MHC-bound antigens, including an unprecedented characterization of post-translationally modified antigens and their cancer-association. We also perform systematic analysis of cancer-testis antigens, cancer-associated antigens, and neoantigens. We make all these data together with annotated MS/MS spectra supporting identification of each antigen in an easily browsable web portal named cancer antigen atlas (caAtlas). caAtlas provides a central resource for the selection and prioritization of MHC-bound peptides for in vitro HLA binding assay and immunogenicity testing, which will pave the way to eventual development of cancer immunotherapies.

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Extensive collection of 43 immunopeptidomic datasets with 1018 samples

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Standardized and rigorous identification of HLA-bound peptides, including PTM peptides

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Comprehensive annotation of CT antigens and cancer-associated antigens

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User-friendly data dissemination through the caAtlas web portal

Identification of tumor antigens with immunopeptidomics

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

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

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

Immunopeptidomics-Guided Warehouse Design for Peptide-Based Immunotherapy in Chronic Lymphocytic Leukemia

Antigen-specific immunotherapies, in particular peptide vaccines, depend on the recognition of naturally presented antigens derived from mutated and unmutated gene products on human leukocyte antigens, and represent a promising low-side-effect concept for cancer treatment. So far, the broad application of peptide vaccines in cancer patients is hampered by challenges of time- and cost-intensive personalized vaccine design, and the lack of neoepitopes from tumor-specific mutations, especially in low-mutational burden malignancies. In this study, we developed an immunopeptidome-guided workflow for the design of tumor-associated off-the-shelf peptide warehouses for broadly applicable personalized therapeutics. Comparative mass spectrometry-based immunopeptidome analyses of primary chronic lymphocytic leukemia (CLL) samples, as representative example of low-mutational burden tumor entities, and a dataset of benign tissue samples enabled the identification of high-frequent non-mutated CLL-associated antigens. These antigens were further shown to be recognized by pre-existing and de novo induced T cells in CLL patients and healthy volunteers, and were evaluated as pre-manufactured warehouse for the construction of personalized multi-peptide vaccines in a first clinical trial for CLL (NCT04688385). This workflow for the design of peptide warehouses is easily transferable to other tumor entities and can provide the foundation for the development of broad personalized T cell-based immunotherapy approaches.

Therapeutic Cancer Vaccination with Immunopeptidomics-Discovered Antigens Confers Protective Antitumor Efficacy

Knowledge of clinically targetable tumor antigens is becoming vital for broader design and utility of therapeutic cancer vaccines. This information is obtained reliably by directly interrogating the MHC-I presented peptide ligands, the immunopeptidome, with state-of-the-art mass spectrometry. Our manuscript describes direct identification of novel tumor antigens for an aggressive triple-negative breast cancer model. Immunopeptidome profiling revealed 2481 unique antigens, among them a novel ERV antigen originating from an endogenous retrovirus element. The clinical benefit and tumor control potential of the identified tumor antigens and ERV antigen were studied in a preclinical model using two vaccine platforms and therapeutic settings. Prominent control of established tumors was achieved using an oncolytic adenovirus platform designed for flexible and specific tumor targeting, namely PeptiCRAd. Our study presents a pipeline integrating immunopeptidome analysis-driven antigen discovery with a therapeutic cancer vaccine platform for improved personalized oncolytic immunotherapy.

HLA-B and cysteinylated ligands distinguish the antigen presentation landscape of extracellular vesicles

Extracellular vesicles can modulate diverse processes ranging from proliferation and tissue repair, to chemo-resistance and cellular differentiation. With the advent of tissue and immunological targeting, extracellular vesicles are also increasingly viewed as promising vectors to deliver peptide-based cancer antigens to the human immune system. Despite the clinical relevance and therapeutic potential of such 'cell-free' approaches, the natural antigen presentation landscape exported in extracellular vesicles is still largely uncharted, due to the challenging nature of such preparations and analyses. In the context of therapeutic vesicle production, a critical evaluation of the similarity in vesicular antigen presentation is also urgently needed. In this work, we compared the HLA-I peptide ligandomes of extracellular vesicles against that of whole-cells of the same cell line. We found that extracellular vesicles not only over-represent HLA-B complexes and peptide ligands, but also cysteinylated peptides that may modulate immune responses. Collectively, these findings describe the pre-existing provision of vesicular HLA complexes that may be utilized to carry peptide vaccines, as well as the propensity for different peptide and post-translationally modified ligands to be presented, and will outline critical considerations in devising novel EV vaccination strategies.

Pharmacological inhibition of MDA-9/Syntenin blocks breast cancer metastasis through suppression of IL-1β

Melanoma differentiation associated gene-9 (MDA-9), Syntenin-1, or syndecan binding protein is a differentially regulated prometastatic gene with elevated expression in advanced stages of melanoma. MDA-9/Syntenin expression positively associates with advanced disease stage in multiple histologically distinct cancers and negatively correlates with patient survival and response to chemotherapy. MDA-9/Syntenin is a highly conserved PDZ-domain scaffold protein, robustly expressed in a spectrum of diverse cancer cell lines and clinical samples. PDZ domains interact with a number of proteins, many of which are critical regulators of signaling cascades in cancer. Knockdown of MDA-9/Syntenin decreases cancer cell metastasis, sensitizing these cells to radiation. Genetic silencing of MDA-9/Syntenin or treatment with a pharmacological inhibitor of the PDZ1 domain, PDZ1i, also activates the immune system to kill cancer cells. Additionally, suppression of MDA-9/Syntenin deregulates myeloid-derived suppressor cell differentiation via the STAT3/interleukin (IL)-1β pathway, which concomitantly promotes activation of cytotoxic T lymphocytes. Biologically, PDZ1i treatment decreases metastatic nodule formation in the lungs, resulting in significantly fewer invasive cancer cells. In summary, our observations indicate that MDA-9/Syntenin provides a direct therapeutic target for mitigating aggressive breast cancer and a small-molecule inhibitor, PDZ1i, provides a promising reagent for inhibiting advanced breast cancer pathogenesis.

IFNγ Modulates the Immunopeptidome of Triple Negative Breast Cancer Cells by Enhancing and Diversifying Antigen Processing and Presentation

Peptide vaccination remains a viable approach to induce T-cell mediated killing of tumors. To identify potential T-cell targets for Triple-Negative Breast Cancer (TNBC) vaccination, we examined the effect of the pro-inflammatory cytokine interferon-γ (IFNγ) on the transcriptome, proteome, and immunopeptidome of the TNBC cell line MDA-MB-231. Using high resolution mass spectrometry, we identified a total of 84,131 peptides from 9,647 source proteins presented by human leukocyte antigen (HLA)-I and HLA-II alleles. Treatment with IFNγ resulted in a remarkable remolding of the immunopeptidome, with only a 34% overlap between untreated and treated cells across the HLA-I immunopeptidome, and expression of HLA-II only detected on treated cells. IFNγ increased the overall number, diversity, and abundance of peptides contained within the immunopeptidome, as well increasing the coverage of individual source antigens. The suite of peptides displayed under conditions of IFNγ treatment included many known tumor associated antigens, with the HLA-II repertoire sampling 17 breast cancer associated antigens absent from those sampled by HLA-I molecules. Quantitative analysis of the transcriptome (10,248 transcripts) and proteome (6,783 proteins) of these cells revealed 229 common proteins and transcripts that were differentially expressed. Most of these represented downstream targets of IFNγ signaling including components of the antigen processing machinery such as tapasin and HLA molecules. However, these changes in protein expression did not explain the dramatic modulation of the immunopeptidome following IFNγ treatment. These results demonstrate the high degree of plasticity in the immunopeptidome of TNBC cells following cytokine stimulation and provide evidence that under pro-inflammatory conditions a greater variety of potential HLA-I and HLA-II vaccine targets are unveiled to the immune system. This has important implications for the development of personalized cancer vaccination strategies.

Mass Spectrometry-Based Omics for the Characterization of Triple-Negative Breast Cancer Bio-Signature

Triple-negative breast cancer (TNBC) represents an unmet medical need due to a high rate of metastatic occurrence and poor overall survival, pathology aggressiveness, heterogeneous clinical behavior and limited cytotoxic chemotherapy options available because of the absence of targetable receptors. The current standard of care in TNBC is represented by chemotherapy and surgery associated with low overall survival and high relapse rates. Hopes of overcoming current limited and unspecific approaches of TNBC therapy lie in studying the metabolic rewiring of these types of breast cancer, thus understanding the mechanisms involved in the occurrence and progression of the disease. Due to its heterogeneity, a clinically relevant sub-classification of this type of breast cancer based on biomarker panels is greatly needed in order to guide treatment decisions. Mass spectrometry-based omics may provide very useful tools to address the current needs of targetable biomarker discovery and validation. The present review aims to provide a comprehensive view of the current clinical diagnosis and therapy of TNBC highlighting the need for a new approach. Therefore, this paper offers a detailed mass spectrometry-based snapshot of TNBC metabolic adjustment, emphasizing a complex network of variables governing the diverse and aggressive clinical behavior of TNBC.

Identification of the Cryptic HLA-I Immunopeptidome

The success of cancer immunotherapy relies on the ability of cytotoxic T cells to specifically recognize and eliminate tumor cells based on peptides presented by HLA-I. Although the peptide epitopes that elicit the corresponding immune response often remain unidentified, it is generally assumed that neoantigens, due to tumor-specific mutations, are the most common targets. Here, we used a mass spectrometric approach to show an underappreciated class of epitopes that accounts for up to 15% of HLA-I peptides for certain HLA alleles in various tumors and patients. These peptides are translated from cryptic open reading frames in supposedly noncoding regions in the genome and are mostly unidentifiable with conventional computational analyses of mass spectrometry (MS) data. Our approach, Peptide-PRISM, identified thousands of such cryptic peptides in tumor immunopeptidomes. About 20% of these HLA-I peptides represented the C-terminus of the corresponding translation product, suggesting frequent proteasome-independent processing. Our data also revealed HLA-I allele-dependent presentation of cryptic peptides, with HLA-A*03 and HLA-A*11 presenting the highest percentage of cryptic peptides. Our analyses refute the reported frequent presentation of HLA peptides generated by proteasome-catalyzed peptide splicing. Thus, Peptide-PRISM represents an important step toward comprehensive identification of HLA-I immunopeptidomes and reveals cryptic peptides as an abundant class of epitopes with potential relevance for novel immunotherapeutic approaches.

Interleukin-32: Frenemy in cancer?

Interleukin-32 (IL-32) was originally identified in natural killer (NK) cells activated by IL-2 in 1992. Thus, it was named NK cell transcript 4 (NK4) because of its unknown function at that time. The function of IL-32 has been elucidated over the last decade. IL-32 is primarily considered to be a booster of inflammatory reactions because it is induced by pro-inflammatory cytokines and stimulates the production of those cytokines and vice versa. Therefore, many studies have been devoted to studying the roles of IL-32 in inflammation-associated cancers, including gastric, colon cancer, and hepatocellular carcinoma. At the same time, roles of IL-32 have also been discovered in other cancers. Collectively, IL-32 fosters the tumor progression by nuclear factor-κB (NF-κB)-mediated cytokines and metalloproteinase production, as well as stimulation of differentiation into immunosuppressive cell types in some cancer types. However, it is also able to induce tumor cell apoptosis and enhance NK and cytotoxic T cell sensitivity in other cancer types. In this review, we will address the function of each IL-32 isoform in different cancer types studied to date, and suggest further strategies to comprehensively elucidate the roles of IL-32 in a context-dependent manner.

The Evolving Landscape of Autoantigen Discovery and Characterization in Type 1 Diabetes

Type 1 diabetes (T1D) is an autoimmune disease that is caused, in part, by T cell-mediated destruction of insulin-producing β-cells. High risk for disease, in those with genetic susceptibility, is predicted by the presence of two or more autoantibodies against insulin, the 65-kDa form of glutamic acid decarboxylase (GAD65), insulinoma-associated protein 2 (IA-2), and zinc transporter 8 (ZnT8). Despite this knowledge, we still do not know what leads to the breakdown of tolerance to these autoantigens, and we have an incomplete understanding of T1D etiology and pathophysiology. Several new autoantibodies have recently been discovered using innovative technologies, but neither their potential utility in monitoring disease development and treatment nor their role in the pathophysiology and etiology of T1D has been explored. Moreover, neoantigen generation (through posttranslational modification, the formation of hybrid peptides containing two distinct regions of an antigen or antigens, alternative open reading frame usage, and translation of RNA splicing variants) has been reported, and autoreactive T cells that target these neoantigens have been identified. Collectively, these new studies provide a conceptual framework to understand the breakdown of self-tolerance, if such modifications occur in a tissue- or disease-specific context. A recent workshop sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases brought together investigators who are using new methods and technologies to identify autoantigens and characterize immune responses toward these proteins. Researchers with diverse expertise shared ideas and identified resources to accelerate antigen discovery and the detection of autoimmune responses in T1D. The application of this knowledge will direct strategies for the identification of improved biomarkers for disease progression and treatment response monitoring and, ultimately, will form the foundation for novel antigen-specific therapeutics. This Perspective highlights the key issues that were addressed at the workshop and identifies areas for future investigation.

Serum amyloid A predisposes inflammatory tumor microenvironment in triple negative breast cancer

Acute-phase proteins (APPs) are associated with a variety of disorders such as infection, inflammatory diseases, and cancers. The signature profile of APPs in breast cancer (BC) is poorly understood. Here, we identified serum amyloid A (SAA) for proinflammatory predisposition in BC through the signature profiles of APPs, interleukin (IL) and tumor necrosis factor (TNF) superfamily using publicly available datasets of tumor samples and cell lines. Triple-negative breast cancer (TNBC) subtype highly expressed SAA1/2 compared to HER2, luminal A (LA) and luminal B (LB) subtypes. IL1A, IL1B, IL8/CXCL8, IL32 and IL27RA in IL superfamily and CD70, TNFSF9 and TNFRSF21 in TNF superfamily were highly expressed in TNBC compared to other subtypes. SAA is restrictedly regulated by nuclear factor (NF)-κB and IL-1β, an NF-κB activator highly expressed in TNBC, increased the promoter activity of SAA1 in human TNBC MDA-MB231 cells. Interestingly, two κB-sites contained in SAA1 promoter were involved, and the proximal region (-96/-87) was more critical than the distal site (-288/-279) in regulating IL-1β-induced SAA1. Among the SAA receptors, TLR1 and TLR2 were highly expressed in TNBC. Cu-CPT22, TLR1/2 antagonist, abrogated IL-1β-induced SAA1 promoter activity. In addition, SAA1 induced IL8/CXCL8 promoter activity, which was partially reduced by Cu-CPT22. Notably, SAA1/2, TLR2 and IL8/CXCL8 were associated with a poor overall survival in mesenchymal-like TNBC. Taken together, IL-1-induced SAA via NF-κB-mediated signaling could potentiate an inflammatory burden, leading to cancer progression and high mortality in TNBC patients.

Immunopeptidomic Profiling of HLA-A2-Positive Triple Negative Breast Cancer Identifies Potential Immunotherapy Target Antigens

The recent development in immune checkpoint inhibitors and chimeric antigen receptor (CAR) T-cells in the treatment of cancer has not only demonstrated the potency of utilizing T-cell reactivity for cancer therapy, but has also highlighted the need for developing new approaches to discover targets suitable for such novel therapeutics. Here we analyzed the immunopeptidomes of six HLA-A2-positive triple negative breast cancer (TNBC) samples by nano-ultra performance liquid chromatography tandem mass spectrometry (nUPLC-MS2 ). Immunopeptidomic profiling identified a total of 19 675 peptides from tumor and adjacent normal tissue and 130 of the peptides were found to have higher abundance in tumor than in normal tissues. To determine potential therapeutic target proteins, we calculated the average tumor-associated cohort coverage (aTaCC) that represents the percentage coverage of each protein in this cohort by peptides that had higher tumoral abundance. Cofilin-1 (CFL-1), interleukin-32 (IL-32), proliferating cell nuclear antigen (PCNA), syntenin-1 (SDCBP), and ribophorin-2 (RPN-2) were found to have the highest aTaCC scores. We propose that these antigens could be evaluated further for their potential as targets in breast cancer immunotherapy and the small cohort immunopeptidomics analysis technique could be used in a wide spectrum of target discovery. Data are available via ProteomeXchange with identifier PXD009738.