Publications by authors named "Jennifer G Abelin"

The aminopeptidase, endoplasmic reticulum aminopeptidase 1 (ERAP1), trims peptides for loading into major histocompatibility complex class I (MHC class I), and loss of this activity has broad effects on the MHC class I peptidome. Here, we investigated the impact of targeting ERAP1 in immune checkpoint blockade (ICB), as MHC class I interactions mediate both activating and inhibitory functions in antitumor immunity. Loss of ERAP sensitized mouse tumor models to ICB, and this sensitivity depended on CD8 T cells and natural killer (NK) cells.

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Article Synopsis
  • Researchers aim to better understand the protein-coding genome due to its importance in human health, while questioning what previous genomic studies may have overlooked regarding non-canonical open reading frames (ncORFs).
  • Over the last ten years, ncORFs have shown potential relevance in human cell types and diseases, but their impact on the human proteome was previously unclear, prompting a collaborative effort to analyze their protein-level evidence.
  • The study found that 25% of analyzed ncORFs contribute to translated proteins, resulting in over 3,000 new peptides from extensive mass spectrometry data, and established an annotation framework and public tools to support ongoing research in this area.
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Over the past 30 years, immunopeptidomics has grown alongside improvements in mass spectrometry technology, genomics, transcriptomics, T cell receptor sequencing, and immunological assays to identify and characterize the targets of activated T cells. Together, multiple research groups with expertise in immunology, biochemistry, chemistry, and peptide mass spectrometry have come together to enable the isolation and sequence identification of endogenous major histocompatibility complex (MHC)-bound peptides. The idea to apply highly sensitive mass spectrometry techniques to study the landscape of peptide antigens presented by cell surface MHCs was innovative and continues to be successfully used and improved upon to deepen our understanding of how peptide antigens are processed and presented to T cells.

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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.

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Unveiling the complete proteome of viruses is crucial to our understanding of the viral life cycle and interaction with the host. We developed Massively Parallel Ribosome Profiling (MPRP) to experimentally determine open reading frames (ORFs) in 20,170 designed oligonucleotides across 679 human-associated viral genomes. We identified 5,381 ORFs, including 4,208 non-canonical ORFs, and show successful detection of both annotated coding sequences (CDSs) and reported non-canonical ORFs.

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Article Synopsis
  • Ribosome profiling (Ribo-Seq) has revealed thousands of noncanonical open reading frames (ORFs) that might expand the number of human protein-coding sequences (CDSs) by up to 30%, increasing the count from approximately 19,500 to over 26,000.
  • * However, there are significant uncertainties about how many of these noncanonical ORFs actually produce functional proteins, with estimates varying widely from a few thousand to several hundred thousand.
  • * This research gap has left the genomics and proteomics communities excited but also in need of guidance on how to evaluate the coding potential of these noncanonical ORFs.*
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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.

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CD4+ T cell responses are exquisitely antigen specific and directed toward peptide epitopes displayed by human leukocyte antigen class II (HLA-II) on antigen-presenting cells. Underrepresentation of diverse alleles in ligand databases and an incomplete understanding of factors affecting antigen presentation in vivo have limited progress in defining principles of peptide immunogenicity. Here, we employed monoallelic immunopeptidomics to identify 358,024 HLA-II binders, with a particular focus on HLA-DQ and HLA-DP.

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Article Synopsis
  • - Ribosome profiling (Ribo-seq) has revealed that there may be at least 7,000 non-canonical open reading frames (ORFs) in the human genome that could expand the number of recognized protein-coding sequences by 30% from around 19,500 to over 26,000.
  • - Despite the exciting possibilities for new coding regions, the scientific community faces challenges in verifying how many of these ORFs actually produce proteins, as estimates of their quantity range widely from a few thousand to several hundred thousand.
  • - The article discusses ongoing research on non-canonical ORFs, the use of ribosome profiling and immunopeptidomics to study them, and the need to understand the evidence required to classify
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Comprehensive and in-depth identification of the human leukocyte antigen class I (HLA-I) and class II (HLA-II) tumor immunopeptidome can inform the development of cancer immunotherapies. Mass spectrometry (MS) is a powerful technology for direct identification of HLA peptides from patient-derived tumor samples or cell lines. However, achieving sufficient coverage to detect rare and clinically relevant antigens requires highly sensitive MS-based acquisition methods and large amounts of sample.

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Serial multi-omic analysis of proteome, phosphoproteome, and acetylome provides insights into changes in protein expression, cell signaling, cross-talk and epigenetic pathways involved in disease pathology and treatment. However, ubiquitylome and HLA peptidome data collection used to understand protein degradation and antigen presentation have not together been serialized, and instead require separate samples for parallel processing using distinct protocols. Here we present MONTE, a highly sensitive multi-omic native tissue enrichment workflow, that enables serial, deep-scale analysis of HLA-I and HLA-II immunopeptidome, ubiquitylome, proteome, phosphoproteome, and acetylome from the same tissue sample.

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Immunopeptidome profiling of infected cells is a powerful technique for detecting viral peptides that are naturally processed and loaded onto class I human leukocyte antigens (HLAs-I). Here, we provide a protocol for preparing samples for immunopeptidome profiling that can inactivate enveloped viruses while still preserving the integrity of the HLA-I complex. We detail steps for lysate preparation of infected cells followed by HLA-I immunoprecipitation and virus inactivation.

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Oncogenic mutations in KRAS can be recognized by T cells on specific class I human leukocyte antigen (HLA-I) molecules, leading to tumor control. To date, the discovery of T cell targets from KRAS mutations has relied on occasional T cell responses in patient samples or the use of transgenic mice. To overcome these limitations, we have developed a systematic target discovery and validation pipeline.

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  • There is a significant need for new immunotherapy targets for colorectal cancer (CRC), particularly focusing on tumor-infiltrating lymphocytes (TILs) which act as a critical indicator of prognosis.
  • Recent research identifies 120 HLA-I phosphopeptides from CRC tumors and metastases, showing that these tumor-specific antigens are linked to abnormal protein phosphorylation due to dysregulated signaling in cancer.
  • The study reveals that these phosphopeptides not only play a pivotal role in TIL activity within tumors but also provoke stronger immune responses in CRC patients compared to healthy individuals, suggesting their potential utility in targeted therapies.
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MS is the most effective method to directly identify peptides presented on human leukocyte antigen (HLA) molecules. However, current standard approaches often use 500 million or more cells as input to achieve high coverage of the immunopeptidome, and therefore, these methods are not compatible with the often limited amounts of tissue available from clinical tumor samples. Here, we evaluated microscaled basic reversed-phase fractionation to separate HLA peptide samples offline followed by ion mobility coupled to LC-MS/MS for analysis.

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T cell-mediated immunity plays an important role in controlling SARS-CoV-2 infection, but the repertoire of naturally processed and presented viral epitopes on class I human leukocyte antigen (HLA-I) remains uncharacterized. Here, we report the first HLA-I immunopeptidome of SARS-CoV-2 in two cell lines at different times post infection using mass spectrometry. We found HLA-I peptides derived not only from canonical open reading frames (ORFs) but also from internal out-of-frame ORFs in spike and nucleocapsid not captured by current vaccines.

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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.

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Increasing evidence indicates CD4 T cells can recognize cancer-specific antigens and control tumor growth. However, it remains difficult to predict the antigens that will be presented by human leukocyte antigen class II molecules (HLA-II), hindering efforts to optimally target them therapeutically. Obstacles include inaccurate peptide-binding prediction and unsolved complexities of the HLA-II pathway.

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Identifying immunodominant T cell epitopes remains a significant challenge in the context of infectious disease, autoimmunity, and immuno-oncology. To address the challenge of antigen discovery, we developed a quantitative proteomic approach that enabled unbiased identification of major histocompatibility complex class II (MHCII)-associated peptide epitopes and biochemical features of antigenicity. On the basis of these data, we trained a deep neural network model for genome-scale predictions of immunodominant MHCII-restricted epitopes.

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Although the value of proteomics has been demonstrated, cost and scale are typically prohibitive, and gene expression profiling remains dominant for characterizing cellular responses to perturbations. However, high-throughput sentinel assays provide an opportunity for proteomics to contribute at a meaningful scale. We present a systematic library resource (90 drugs × 6 cell lines) of proteomic signatures that measure changes in the reduced-representation phosphoproteome (P100) and changes in epigenetic marks on histones (GCP).

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  • Mass spectrometry with data-independent acquisition (DIA) aims to enhance the analysis of proteins by measuring all peptide precursors in a sample, but it struggles with peptides that have similar sequences.
  • The analytical difficulties in distinguishing these peptides have restricted its use in important areas like identifying single-nucleotide polymorphisms (SNPs) and phosphoproteomics.
  • The authors present Specter, an open-source software tool that applies linear algebra to deconvolute DIA spectra by comparing them to a spectral library, showing improved performance especially for challenging cases involving similar peptides.
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  • Developing personalized cancer immunotherapies involves predicting cancer-specific antigens, with predictive algorithms currently used to select potential epitope targets based on HLA-peptide binding.
  • A major limitation of these algorithms is that they rely on datasets that may not fully represent how peptides are processed and presented in the body.
  • Recent advancements in mass spectrometry (MS) technology allow for improved identification of HLA-ligands from various cell types and tumors, providing a valuable method for creating comprehensive datasets to enhance epitope prediction strategies.
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Identification of human leukocyte antigen (HLA)-bound peptides by liquid chromatography-tandem mass spectrometry (LC-MS/MS) is poised to provide a deep understanding of rules underlying antigen presentation. However, a key obstacle is the ambiguity that arises from the co-expression of multiple HLA alleles. Here, we have implemented a scalable mono-allelic strategy for profiling the HLA peptidome.

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