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Sensitive and quantitative detection of MHC-I displayed neoepitopes using a semi-automated workflow and TOMAHAQ mass spectrometry

ABSTRACT: Advances in several key technologies, including MHC peptidomics, has helped fuel our understanding of basic immune regulatory mechanisms and identify T cell receptor targets for the development of immunotherapeutics. Isolating and accurately quantifying MHC-bound peptides from cells and tissues enables characterization of dynamic changes in the ligandome due to cellular perturbations. This multi-step analytical process remains challenging, and throughput and reproducibility are paramount for rapidly characterizing multiple conditions in parallel. Here, we describe a robust and quantitative method whereby peptides derived from MHC-I complexes from a variety of cell lines, including challenging adherent lines, can be enriched in a semi-automated fashion on reusable, dry-storage, customized antibody cartridges. TOMAHAQ, a targeted mass spectrometry technique that combines sample multiplexing and high sensitivity, was employed to characterize neoepitopes displayed on MHC-I by tumor cells and to quantitatively assess the influence of neoantigen expression and induced degradation on neoepitope presentation.

ORGANISM(S): Mus musculus

PROVIDER: GSE163326 | GEO | 2021/07/20

REPOSITORIES: GEO

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Sensitive and quantitative detection of MHC-I displayed neoepitopes using a semi-automated workflow and TOMAHAQ mass spectrometry

Project description:Advances in several key technologies, including MHC peptidomics, has helped fuel our understanding of basic immune regulatory mechanisms and identify T cell receptor targets for the development of immunotherapeutics. Isolating and accurately quantifying MHC-bound peptides from cells and tissues enables characterization of dynamic changes in the ligandome due to cellular perturbations. This multi-step analytical process remains challenging, and throughput and reproducibility are paramount for rapidly characterizing multiple conditions in parallel. Here, we describe a robust and quantitative method whereby peptides derived from MHC-I complexes from a variety of cell lines, including challenging adherent lines, can be enriched in a semi-automated fashion on reusable, dry-storage, customized antibody cartridges. TOMAHAQ, a targeted mass spectrometry technique that combines sample multiplexing and high sensitivity, was employed to characterize neoepitopes displayed on MHC-I by tumor cells and to quantitatively assess the influence of neoantigen expression and induced degradation on neoepitope presentation.

2020-12-11 | MSV000086582 | MassIVE

Sensitive and quantitative detection of MHC-I displayed neoepitopes using a semi-automated workflow and TOMAHAQ mass spectrometry

Project description:Sensitive and quantitative detection of MHC-I displayed neoepitopes using a semi-automated workflow and TOMAHAQ mass spectrometry

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Pharmacologic modulation of RNA splicing enhances anti-tumor immunity.

Project description:Although mutations in DNA are the best-studied source of neoantigens that determine response to immune checkpoint blockade, alterations in RNA splicing within cancer cells could similarly result in neoepitope production. However, the endogenous antigenicity and clinical potential of such splicing-derived epitopes have not been tested. Here, we demonstrate that pharmacologic modulation of splicing via specific drug classes generates bona fide neoantigens and elicits anti-tumor immunity, augmenting checkpoint immunotherapy. Splicing modulation inhibited tumor growth and enhanced checkpoint blockade in a manner dependent on host T cells and peptides presented on tumor MHC class I. Splicing modulation induced stereotyped splicing changes across tumor types, altering the MHC I-bound immunopeptidome to yield splicing-derived neoepitopes that trigger an anti-tumor T cell response in vivo. These data definitively identify splicing modulation as an untapped source of immunogenic peptides and provide a means to enhance response to checkpoint blockade that is readily translatable to the clinic.

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optiPRM: A targeted immunopeptidomics LC-MS workflow with ultra-high sensitivity for the detection of mutation-derived tumor neoepitopes from limited input material

Project description:Personalized cancer immunotherapies such as vaccines and T cell receptor (TCR)-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen (HLA) class I molecules to cytotoxic T cells. Such neoepitopes can for example arise from somatic mutations and their identification is crucial for the rational design of new therapeutic interventions. For their detection by liquid chromatography mass spectrometry (LC-MS), we have developed a parameter optimization workflow to tune targeted assays for maximum detection sensitivity on a per peptide basis, termed optiPRM. Optimization of collision energy using optiPRM allows for improved detection of low abundant peptides that are very hard to detect using standard parameters. Applying this for to immunopeptidomics, we detected a neoepitope in a patient-derived xenograft (PDX) from as little as 2.5×106 cells input. Application of the workflow on small patient tumor samples allowed for the detection of five mutation-derived neoepitopes in three patients. One neoepitope was confirmed to be recognized by patient T cells. In conclusion, we here present optiPRM, a targeted MS workflow reaching ultra-high sensitivity by per peptide parameter optimization, which allowed for the identification of actionable neoepitopes from sample sizes usually available in the clinic.

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Improved prediction of endogenous HLA-associated epitopes based on mono-allelic mass spectrometry profiling

Project description:LC-MS/MS-based identification of HLA-peptides is poised to provide a deep understanding of the rules underlying antigen presentation. However, a key obstacle limiting the utility of MS data is the ambiguity arising from the co-expression of multiple HLA alleles. Here, we introduce a strategy for profiling the HLA ligandome one allele at a time. By using cell lines expressing a single HLA allele, optimizing immunopurifications, and developing a novel spectral search algorithm, we identified thousands of peptides bound to 16 different HLA class I alleles. These data enabled the discovery of novel binding motifs, and an integrative analysis quantifying the contribution of factors critical to epitope presentation, such as protein cleavage and gene expression. We trained neural network prediction algorithms with our large dataset (>24,000 peptides) and outperformed algorithms trained on datasets of peptides with measured affinities. We thus demonstrate a scalable strategy for systematically learning the rules of endogenous antigen presentation.

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Features of TAP independently presented MHC ligands revealed by quantitative mass spectrometry.

Project description:The TAP transporter is responsible for transferring cytosolic peptides into the ER where they can be loaded onto MHC molecules. Deletion of TAP results in a drastic reduction of MHC surface expression and alters the presented peptide pattern. Using the TAP deficient cell line LCL721.174 and its TAP expressing progenitor cell line LCL721.45, we have identified and quantified more than 160 HLA ligands, 50 out of which were presented TAP independently. Peptides which were predominantly presented on the TAP deficient LCL721.174 cell line had a decreased MHC binding affinity according to their SYFPEITHI and BIMAS score. About half of the identified TAP independently presented peptides were not derived from signal sequences and may partly be generated by the proteasome. Furthermore, we have excluded that different HLA presentation ratios were due to varying expression of the respective protein or due to changes in the antigen loading complex. Features of TAP-independently presented peptides as well as proteasomal contribution to their generation provides an insight into basic immunological mechanisms. Keywords: differential mass spectrometry, TAP independent, antigen presentation

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Low avidity T cells drive endogenous tumor immunity in mice and humans

Project description:CD8 T cells which recognize neoepitopes are central to immune control of cancers. T cells, through T cell receptors, recognize neoepitope peptide-MHC I on cancer cells. The strength (or avidity) of the T cell receptor- peptide-MHCI interaction is a critical variable in immune control of cancers in vivo. Here, analyzing neoepitope-specific CD8 cells of distinct avidities to validated neoepitopes of a mouse tumor, low avidity T cells are observed to be the sole mediators of cancer control in vivo. Low avidity cells are also observed to be solely responsive to checkpoint blockade in mice and in humans. High avidity T cells are not only ineffective but suppress immune response. The mechanistic basis of the differences in the anti-tumor activity of cells of low and high avidities, lies in the higher exhaustion status of high avidity cells. High avidity T cells have a distinct transcriptomic profile which creates an Avidity Score, used here to identify in silico, the low and high avidity T cell populations in mice and humans. Surprisingly, CD8 T cells with identical TCRs exhibit a wide variation in avidities, suggesting a novel level of regulation of T cell activity. These observations, and the mechanisms that underlie them, shed new light on the endogenous T cell response to cancer and suggest new avenues in cancer immunotherapy.

2024-12-25 | GSE282069 | GEO

Reversion analysis reveals the immunogenicity in vivo of a poorly MHC I-binding cancer neoepitope

Project description:A mutation that results in tumor rejection activity in a neoepitope (which is a poor binder of Kd) influences the immunogenicity of the tumor as a whole. Our results demonstrate the activity in vivo of a poorly-MHC I-binding cancer neoepitope.

2021-05-31 | GSE171100 | GEO

Discovery of prevalent, clinically actionable tumor neoepitopes via integrated biochemical and cell-based platforms

Project description:Strategies for maximizing the potency and specificity of cancer immunotherapies have sparked efforts to identify recurrent epitopes presented in the context of defined tumor-associated neoantigens. Discovering these neoepitopes can be difficult owing to the limited number of peptides that arise from a single point mutation, a low number of copies presented on the cell surface, and variable binding specificity of the human leukocyte antigen (HLA) class I complex. Due to these limitations, many discovery efforts focus on identifying neoepitopes from a small number of cancer neoantigens in the context of few HLA alleles. Here we describe a systematic workflow to characterize binding and presentation of neoepitopes derived from 47 shared cancer neoantigens in the context of 15 HLA alleles. Through the development of a high-throughput neoepitope-HLA binding assay, we surveyed 24,149 candidate neoepitope-HLA combinations resulting in 587 stable complexes. These data were supplemented by computational prediction that identified an additional 257 neoepitope-HLA pairs, resulting in a total of 844 unique combinations. We used these results to build sensitive targeted mass spectrometry assays to validate neoepitope presentation on a panel of HLA-I monoallelic cell lines engineered to express neoantigens of interest as a single polypeptide. Altogether, our analyses detected 84 unique neoepitope-HLA pairs derived from 37 shared cancer neoantigens and presented across 12 HLA alleles. We subsequently identified multiple TCRs which specifically recognized two of these neoantigen-HLA combinations. Finally, these novel TCRs were utilized to elicit a T cell response suggesting that these neoepitopes are likely to be immunogenic. Together these data represent a validated, extensive resource of therapeutically relevant neoepitopes and the HLA context in which they can be targeted.

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MHC-IP MS of EpiScan A02 SARS-CoV-2 library

Project description:Identification of CD8+ T-cell epitopes is critical for the development of immunotherapeutics. Existing methods for MHC-I ligand discovery are time-intensive, specialized and unable to interrogate specific proteins on a large scale. Here we present EpiScan, which uses surface MHC-I levels as a readout for whether a genetically encoded peptide is an MHC-I ligand. Oligonucleotide synthesis permits facile screening for MHC-I ligands amongst predetermined starting pools comprising >100,000 peptides. We exploit this programmability of EpiScan to uncover an unappreciated role for cysteine that increases the number of predicted ligands by 12-21%, reveal affinity hierarchies by analysis of biased-anchor peptide libraries, and screen viral proteomes for MHC-I ligands. Using these data, we generate and iteratively refine peptide binding prediction predictions to create EpiScan Predictor, or ESP. ESP performed comparably to other state-of-the-art MHC-I peptide binding prediction algorithms while not suffering from underrepresentation of cysteine-containing peptides. Thus, targeted immunopeptidomics using EpiScan will accelerate CD8+ T-cell epitope discovery towards the goal of patient-specific immunotherapeutics.

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