1
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Wei F, Kouro T, Nakamura Y, Ueda H, Iiizumi S, Hasegawa K, Asahina Y, Kishida T, Morinaga S, Himuro H, Horaguchi S, Tsuji K, Mano Y, Nakamura N, Kawamura T, Sasada T. Enhancing Mass spectrometry-based tumor immunopeptide identification: machine learning filter leveraging HLA binding affinity, aliphatic index and retention time deviation. Comput Struct Biotechnol J 2024; 23:859-869. [PMID: 38356658 PMCID: PMC10864759 DOI: 10.1016/j.csbj.2024.01.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/31/2024] [Accepted: 01/31/2024] [Indexed: 02/16/2024] Open
Abstract
Accurately identifying neoantigens is crucial for developing effective cancer vaccines and improving tumor immunotherapy. Mass spectrometry-based immunopeptidomics has emerged as a promising approach to identifying human leukocyte antigen (HLA) peptides presented on the surface of cancer cells, but false-positive identifications remain a significant challenge. In this study, liquid chromatography-tandem mass spectrometry-based proteomics and next-generation sequencing were utilized to identify HLA-presenting neoantigenic peptides resulting from non-synonymous single nucleotide variations in tumor tissues from 18 patients with renal cell carcinoma or pancreatic cancer. Machine learning was utilized to evaluate Mascot identifications through the prediction of MS/MS spectral consistency, and four descriptors for each candidate sequence: the max Mascot ion score, predicted HLA binding affinity, aliphatic index and retention time deviation, were selected as important features in filtering out identifications with inadequate fragmentation consistency. This suggests that incorporating rescoring filters based on peptide physicochemical characteristics could enhance the identification rate of MS-based immunopeptidomics compared to the traditional Mascot approach predominantly used for proteomics, indicating the potential for optimizing neoantigen identification pipelines as well as clinical applications.
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Affiliation(s)
- Feifei Wei
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Cancer Vaccine and Immunotherapy Center, Kanagawa Cancer Center, Yokohama, Japan
| | - Taku Kouro
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Cancer Vaccine and Immunotherapy Center, Kanagawa Cancer Center, Yokohama, Japan
| | - Yuko Nakamura
- Isotope Science Center, The University of Tokyo, Tokyo, Japan
| | - Hiroki Ueda
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Susumu Iiizumi
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Research & Early Development Division, BrightPath Biotherapeutics Co., Ltd., Kawasaki, Japan
| | - Kyoko Hasegawa
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Research & Early Development Division, BrightPath Biotherapeutics Co., Ltd., Kawasaki, Japan
| | - Yuki Asahina
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
| | - Takeshi Kishida
- Department of Urology, Kanagawa Cancer Center, Yokohama, Japan
| | - Soichiro Morinaga
- Department of Hepato-Biliary and Pancreatic Surgery, Kanagawa Cancer Center, Yokohama, Japan
| | - Hidetomo Himuro
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Cancer Vaccine and Immunotherapy Center, Kanagawa Cancer Center, Yokohama, Japan
| | - Shun Horaguchi
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Cancer Vaccine and Immunotherapy Center, Kanagawa Cancer Center, Yokohama, Japan
- Department of Pediatric Surgery, Nihon University School of Medicine, Tokyo, Japan
| | - Kayoko Tsuji
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Cancer Vaccine and Immunotherapy Center, Kanagawa Cancer Center, Yokohama, Japan
| | - Yasunobu Mano
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Cancer Vaccine and Immunotherapy Center, Kanagawa Cancer Center, Yokohama, Japan
| | - Norihiro Nakamura
- Research & Early Development Division, BrightPath Biotherapeutics Co., Ltd., Kawasaki, Japan
| | | | - Tetsuro Sasada
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Cancer Vaccine and Immunotherapy Center, Kanagawa Cancer Center, Yokohama, Japan
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2
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Meng W, Takeuchi Y, Ward JP, Sultan H, Arthur CD, Mardis ER, Artyomov MN, Lichti CF, Schreiber RD. Improvement of Tumor Neoantigen Detection by High-Field Asymmetric Waveform Ion Mobility Mass Spectrometry. Cancer Immunol Res 2024; 12:988-1006. [PMID: 38768391 DOI: 10.1158/2326-6066.cir-23-0900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 03/05/2024] [Accepted: 05/17/2024] [Indexed: 05/22/2024]
Abstract
Cancer neoantigens have been shown to elicit cancer-specific T-cell responses and have garnered much attention for their roles in both spontaneous and therapeutically induced antitumor responses. Mass spectrometry (MS) profiling of tumor immunopeptidomes has been used, in part, to identify MHC-bound mutant neoantigen ligands. However, under standard conditions, MS-based detection of such rare but clinically relevant neoantigens is relatively insensitive, requiring 300 million cells or more. Here, to quantitatively define the minimum detectable amounts of therapeutically relevant MHC-I and MHC-II neoantigen peptides, we analyzed different dilutions of immunopeptidomes isolated from the well-characterized T3 mouse methylcholanthrene (MCA)-induced cell line by MS. Using either data-dependent acquisition or parallel reaction monitoring (PRM), we established the minimum amount of material required to detect the major T3 neoantigens in the presence or absence of high field asymmetric waveform ion mobility spectrometry (FAIMS). This analysis yielded a 14-fold enhancement of sensitivity in detecting the major T3 MHC-I neoantigen (mLama4) with FAIMS-PRM compared with PRM without FAIMS, allowing ex vivo detection of this neoantigen from an individual 100 mg T3 tumor. These findings were then extended to two other independent MCA-sarcoma lines (1956 and F244). This study demonstrates that FAIMS substantially increases the sensitivity of MS-based characterization of validated neoantigens from tumors.
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Affiliation(s)
- Wei Meng
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, Missouri
- The Andrew M. and Jane M. Bursky Center for Human Immunology and Immunotherapy Programs, Washington University School of Medicine, Saint Louis, Missouri
| | - Yoshiko Takeuchi
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, Missouri
- The Andrew M. and Jane M. Bursky Center for Human Immunology and Immunotherapy Programs, Washington University School of Medicine, Saint Louis, Missouri
| | - Jeffrey P Ward
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, Missouri
- The Andrew M. and Jane M. Bursky Center for Human Immunology and Immunotherapy Programs, Washington University School of Medicine, Saint Louis, Missouri
- Department of Medicine, Washington University School of Medicine, Saint Louis, Missouri
| | - Hussein Sultan
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, Missouri
- The Andrew M. and Jane M. Bursky Center for Human Immunology and Immunotherapy Programs, Washington University School of Medicine, Saint Louis, Missouri
| | - Cora D Arthur
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, Missouri
| | - Elaine R Mardis
- The Steve and Cindy Rasmussen Institute for Genomic Medicine at Nationwide Children's Hospital, Columbus, Ohio
| | - Maxim N Artyomov
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, Missouri
- The Andrew M. and Jane M. Bursky Center for Human Immunology and Immunotherapy Programs, Washington University School of Medicine, Saint Louis, Missouri
| | - Cheryl F Lichti
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, Missouri
- The Andrew M. and Jane M. Bursky Center for Human Immunology and Immunotherapy Programs, Washington University School of Medicine, Saint Louis, Missouri
| | - Robert D Schreiber
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, Missouri
- The Andrew M. and Jane M. Bursky Center for Human Immunology and Immunotherapy Programs, Washington University School of Medicine, Saint Louis, Missouri
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3
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Gurung HR, Heidersbach AJ, Darwish M, Chan PPF, Li J, Beresini M, Zill OA, Wallace A, Tong AJ, Hascall D, Torres E, Chang A, Lou K'HW, Abdolazimi Y, Hammer C, Xavier-Magalhães A, Marcu A, Vaidya S, Le DD, Akhmetzyanova I, Oh SA, Moore AJ, Uche UN, Laur MB, Notturno RJ, Ebert PJR, Blanchette C, Haley B, Rose CM. Systematic discovery of neoepitope-HLA pairs for neoantigens shared among patients and tumor types. Nat Biotechnol 2024; 42:1107-1117. [PMID: 37857725 PMCID: PMC11251992 DOI: 10.1038/s41587-023-01945-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 08/14/2023] [Indexed: 10/21/2023]
Abstract
The broad application of precision cancer immunotherapies is limited by the number of validated neoepitopes that are common among patients or tumor types. To expand the known repertoire of shared neoantigen-human leukocyte antigen (HLA) complexes, we developed a high-throughput platform that coupled an in vitro peptide-HLA binding assay with engineered cellular models expressing individual HLA alleles in combination with a concatenated transgene harboring 47 common cancer neoantigens. From more than 24,000 possible neoepitope-HLA combinations, biochemical and computational assessment yielded 844 unique candidates, of which 86 were verified after immunoprecipitation mass spectrometry analyses of engineered, monoallelic cell lines. To evaluate the potential for immunogenicity, we identified T cell receptors that recognized select neoepitope-HLA pairs and elicited a response after introduction into human T cells. These cellular systems and our data on therapeutically relevant neoepitopes in their HLA contexts will aid researchers studying antigen processing as well as neoepitope targeting therapies.
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Affiliation(s)
| | | | | | | | - Jenny Li
- Genentech, South San Francisco, CA, USA
| | | | | | | | | | | | | | | | | | | | | | | | - Ana Marcu
- Genentech, South San Francisco, CA, USA
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4
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Minegishi Y, Haga Y, Ueda K. Emerging potential of immunopeptidomics by mass spectrometry in cancer immunotherapy. Cancer Sci 2024; 115:1048-1059. [PMID: 38382459 PMCID: PMC11007014 DOI: 10.1111/cas.16118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 02/02/2024] [Accepted: 02/07/2024] [Indexed: 02/23/2024] Open
Abstract
With significant advances in analytical technologies, research in the field of cancer immunotherapy, such as adoptive T cell therapy, cancer vaccine, and immune checkpoint blockade (ICB), is currently gaining tremendous momentum. Since the efficacy of cancer immunotherapy is recognized only by a minority of patients, more potent tumor-specific antigens (TSAs, also known as neoantigens) and predictive markers for treatment response are of great interest. In cancer immunity, immunopeptides, presented by human leukocyte antigen (HLA) class I, play a role as initiating mediators of immunogenicity. The latest advancement in the interdisciplinary multiomics approach has rapidly enlightened us about the identity of the "dark matter" of cancer and the associated immunopeptides. In this field, mass spectrometry (MS) is a viable option to select because of the naturally processed and actually presented TSA candidates in order to grasp the whole picture of the immunopeptidome. In the past few years the search space has been enlarged by the multiomics approach, the sensitivity of mass spectrometers has been improved, and deep/machine-learning-supported peptide search algorithms have taken immunopeptidomics to the next level. In this review, along with the introduction of key technical advancements in immunopeptidomics, the potential and further directions of immunopeptidomics will be reviewed from the perspective of cancer immunotherapy.
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Affiliation(s)
- Yuriko Minegishi
- Cancer Proteomics Group, Cancer Precision Medicine CenterJapanese Foundation for Cancer ResearchTokyoJapan
| | - Yoshimi Haga
- Cancer Proteomics Group, Cancer Precision Medicine CenterJapanese Foundation for Cancer ResearchTokyoJapan
| | - Koji Ueda
- Cancer Proteomics Group, Cancer Precision Medicine CenterJapanese Foundation for Cancer ResearchTokyoJapan
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5
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Adams C, Laukens K, Bittremieux W, Boonen K. Machine learning-based peptide-spectrum match rescoring opens up the immunopeptidome. Proteomics 2024; 24:e2300336. [PMID: 38009585 DOI: 10.1002/pmic.202300336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 10/18/2023] [Accepted: 10/23/2023] [Indexed: 11/29/2023]
Abstract
Immunopeptidomics is a key technology in the discovery of targets for immunotherapy and vaccine development. However, identifying immunopeptides remains challenging due to their non-tryptic nature, which results in distinct spectral characteristics. Moreover, the absence of strict digestion rules leads to extensive search spaces, further amplified by the incorporation of somatic mutations, pathogen genomes, unannotated open reading frames, and post-translational modifications. This inflation in search space leads to an increase in random high-scoring matches, resulting in fewer identifications at a given false discovery rate. Peptide-spectrum match rescoring has emerged as a machine learning-based solution to address challenges in mass spectrometry-based immunopeptidomics data analysis. It involves post-processing unfiltered spectrum annotations to better distinguish between correct and incorrect peptide-spectrum matches. Recently, features based on predicted peptidoform properties, including fragment ion intensities, retention time, and collisional cross section, have been used to improve the accuracy and sensitivity of immunopeptide identification. In this review, we describe the diverse bioinformatics pipelines that are currently available for peptide-spectrum match rescoring and discuss how they can be used for the analysis of immunopeptidomics data. Finally, we provide insights into current and future machine learning solutions to boost immunopeptide identification.
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Affiliation(s)
- Charlotte Adams
- Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium
- Laboratory of Protein Science, Proteomics and Epigenetic Signaling (PPES), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Kris Laukens
- Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium
| | - Wout Bittremieux
- Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium
| | - Kurt Boonen
- Laboratory of Protein Science, Proteomics and Epigenetic Signaling (PPES), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- ImmuneSpec BV, Niel, Belgium
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6
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Kina E, Laverdure JP, Durette C, Lanoix J, Courcelles M, Zhao Q, Apavaloaei A, Larouche JD, Hardy MP, Vincent K, Gendron P, Hesnard L, Thériault C, Ruiz Cuevas MV, Ehx G, Thibault P, Perreault C. Breast cancer immunopeptidomes contain numerous shared tumor antigens. J Clin Invest 2024; 134:e166740. [PMID: 37906288 PMCID: PMC10760959 DOI: 10.1172/jci166740] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 10/23/2023] [Indexed: 11/02/2023] Open
Abstract
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.
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Affiliation(s)
- Eralda Kina
- Institute for Research in Immunology and Cancer (IRIC), and
- Department of Medicine, University of Montreal, Montreal, Quebec, Canada
| | | | | | - Joël Lanoix
- Institute for Research in Immunology and Cancer (IRIC), and
| | | | - Qingchuan Zhao
- Institute for Research in Immunology and Cancer (IRIC), and
- Department of Medicine, University of Montreal, Montreal, Quebec, Canada
| | - Anca Apavaloaei
- Institute for Research in Immunology and Cancer (IRIC), and
- Department of Medicine, University of Montreal, Montreal, Quebec, Canada
| | - Jean-David Larouche
- Institute for Research in Immunology and Cancer (IRIC), and
- Department of Medicine, University of Montreal, Montreal, Quebec, Canada
| | | | | | | | - Leslie Hesnard
- Institute for Research in Immunology and Cancer (IRIC), and
| | | | - Maria Virginia Ruiz Cuevas
- Institute for Research in Immunology and Cancer (IRIC), and
- Department of Medicine, University of Montreal, Montreal, Quebec, Canada
| | - Grégory Ehx
- Laboratory of Hematology, GIGA-I3, University of Liege and CHU of Liège, Liege, Belgium
| | - Pierre Thibault
- Institute for Research in Immunology and Cancer (IRIC), and
- Department of Chemistry, University of Montreal, Montreal, Quebec, Canada
| | - Claude Perreault
- Institute for Research in Immunology and Cancer (IRIC), and
- Department of Medicine, University of Montreal, Montreal, Quebec, Canada
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7
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Mayer RL, Mechtler K. Immunopeptidomics in the Era of Single-Cell Proteomics. BIOLOGY 2023; 12:1514. [PMID: 38132340 PMCID: PMC10740491 DOI: 10.3390/biology12121514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/04/2023] [Accepted: 12/06/2023] [Indexed: 12/23/2023]
Abstract
Immunopeptidomics, as the analysis of antigen peptides being presented to the immune system via major histocompatibility complexes (MHC), is being seen as an imperative tool for identifying epitopes for vaccine development to treat cancer and viral and bacterial infections as well as parasites. The field has made tremendous strides over the last 25 years but currently still faces challenges in sensitivity and throughput for widespread applications in personalized medicine and large vaccine development studies. Cutting-edge technological advancements in sample preparation, liquid chromatography as well as mass spectrometry, and data analysis, however, are currently transforming the field. This perspective showcases how the advent of single-cell proteomics has accelerated this transformation of immunopeptidomics in recent years and will pave the way for even more sensitive and higher-throughput immunopeptidomics analyses.
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Affiliation(s)
- Rupert L. Mayer
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter, 1030 Vienna, Austria
| | - Karl Mechtler
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter, 1030 Vienna, Austria
- Gregor Mendel Institute of Molecular Plant Biology (GMI), Austrian Academy of Sciences, Vienna BioCenter (VBC), 1030 Vienna, Austria
- Institute of Molecular Biotechnology (IMBA), Austrian Academy of Sciences, Vienna BioCenter (VBC), 1030 Vienna, Austria
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8
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Hoenisch Gravel N, Nelde A, Bauer J, Mühlenbruch L, Schroeder SM, Neidert MC, Scheid J, Lemke S, Dubbelaar ML, Wacker M, Dengler A, Klein R, Mauz PS, Löwenheim H, Hauri-Hohl M, Martin R, Hennenlotter J, Stenzl A, Heitmann JS, Salih HR, Rammensee HG, Walz JS. TOF IMS mass spectrometry-based immunopeptidomics refines tumor antigen identification. Nat Commun 2023; 14:7472. [PMID: 37978195 PMCID: PMC10656517 DOI: 10.1038/s41467-023-42692-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 10/18/2023] [Indexed: 11/19/2023] Open
Abstract
T cell recognition of human leukocyte antigen (HLA)-presented tumor-associated peptides is central for cancer immune surveillance. Mass spectrometry (MS)-based immunopeptidomics represents the only unbiased method for the direct identification and characterization of naturally presented tumor-associated peptides, a key prerequisite for the development of T cell-based immunotherapies. This study reports on the implementation of ion mobility separation-based time-of-flight (TOFIMS) MS for next-generation immunopeptidomics, enabling high-speed and sensitive detection of HLA-presented peptides. Applying TOFIMS-based immunopeptidomics, a novel extensive benignTOFIMS dataset was generated from 94 primary benign samples of solid tissue and hematological origin, which enabled the expansion of benign reference immunopeptidome databases with > 150,000 HLA-presented peptides, the refinement of previously described tumor antigens, as well as the identification of frequently presented self antigens and not yet described tumor antigens comprising low abundant mutation-derived neoepitopes that might serve as targets for future cancer immunotherapy development.
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Affiliation(s)
- Naomi Hoenisch Gravel
- Department of Peptide-based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Annika Nelde
- Department of Peptide-based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Jens Bauer
- Department of Peptide-based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Lena Mühlenbruch
- Department of Peptide-based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), partner site Tübingen, Tübingen, Germany
| | - Sarah M Schroeder
- Department of Peptide-based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Department of Otorhinolaryngology, Head and Neck Surgery, University of Tübingen, Tübingen, Germany
| | - Marian C Neidert
- Neuroscience Center Zürich (ZNZ), University of Zürich and ETH Zürich, Zürich, Switzerland
- Clinical Neuroscience Center and Department of Neurosurgery, University Hospital and University of Zurich, Zürich, Switzerland
- Department of Neurosurgery, Cantonal Hospital St. Gallen, Zürich, Switzerland
| | - Jonas Scheid
- Department of Peptide-based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
- Quantitative Biology Center (QBIC), University of Tübingen, Tübingen, Germany
| | - Steffen Lemke
- Department of Peptide-based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
- Quantitative Biology Center (QBIC), University of Tübingen, Tübingen, Germany
| | - Marissa L Dubbelaar
- Department of Peptide-based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
- Quantitative Biology Center (QBIC), University of Tübingen, Tübingen, Germany
| | - Marcel Wacker
- Department of Peptide-based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Anna Dengler
- Department of Peptide-based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Reinhild Klein
- Department of Hematology, Oncology, Clinical Immunology and Rheumatology, University Hospital Tübingen, Tübingen, Germany
| | - Paul-Stefan Mauz
- Department of Otorhinolaryngology, Head and Neck Surgery, University of Tübingen, Tübingen, Germany
| | - Hubert Löwenheim
- Department of Otorhinolaryngology, Head and Neck Surgery, University of Tübingen, Tübingen, Germany
| | - Mathias Hauri-Hohl
- Pediatric Stem Cell Transplantation, University Children's Hospital Zürich, Zürich, Switzerland
| | - Roland Martin
- Neuroimmunology and MS Research, Neurology Clinic, University and University Hospital Zürich, Zürich, Switzerland
| | - Jörg Hennenlotter
- Department of Urology, University Hospital Tübingen, Tübingen, Germany
| | - Arnulf Stenzl
- Department of Urology, University Hospital Tübingen, Tübingen, Germany
| | - Jonas S Heitmann
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany
| | - Helmut R Salih
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), partner site Tübingen, Tübingen, Germany
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany
| | - Hans-Georg Rammensee
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), partner site Tübingen, Tübingen, Germany
| | - Juliane S Walz
- Department of Peptide-based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany.
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany.
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany.
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany.
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9
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Meng W, Schreiber RD, Lichti CF. Recent advances in immunopeptidomic-based tumor neoantigen discovery. Adv Immunol 2023; 160:1-36. [PMID: 38042584 DOI: 10.1016/bs.ai.2023.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2023]
Abstract
The role of aberrantly expressed proteins in tumors in driving immune-mediated control of cancer has been well documented for more than five decades. Today, we know that both aberrantly expressed normal proteins as well as mutant proteins (neoantigens) can function as tumor antigens in both humans and mice. Next-generation sequencing (NGS) and high-resolution mass spectrometry (MS) technologies have made significant advances since the early 2010s, enabling detection of rare but clinically relevant neoantigens recognized by T cells. MS profiling of tumor-specific immunopeptidomes remains the most direct method to identify mutant peptides bound to cellular MHC. However, the need for use of large numbers of cells or significant amounts of tumor tissue to achieve neoantigen detection has historically limited the application of MS. Newer, more sensitive MS technologies have recently demonstrated the capacities to detect neoantigens from fewer cells. Here, we highlight recent advancements in immunopeptidomics-based characterization of tumor-specific neoantigens. Various tumor antigen categories and neoantigen identification approaches are also discussed. Furthermore, we summarize recent reports that achieved successful tumor neoantigen detection by MS using a variety of starting materials, MS acquisition modes, and novel ion mobility devices.
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Affiliation(s)
- Wei Meng
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, United States; The Andrew M. and Jane M. Bursky Center for Human Immunology and Immunotherapy Programs, Washington University School of Medicine, Saint Louis, MO, United States
| | - Robert D Schreiber
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, United States; The Andrew M. and Jane M. Bursky Center for Human Immunology and Immunotherapy Programs, Washington University School of Medicine, Saint Louis, MO, United States.
| | - Cheryl F Lichti
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, United States; The Andrew M. and Jane M. Bursky Center for Human Immunology and Immunotherapy Programs, Washington University School of Medicine, Saint Louis, MO, United States.
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10
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Zhang B, Bassani-Sternberg M. Current perspectives on mass spectrometry-based immunopeptidomics: the computational angle to tumor antigen discovery. J Immunother Cancer 2023; 11:e007073. [PMID: 37899131 PMCID: PMC10619091 DOI: 10.1136/jitc-2023-007073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/21/2023] [Indexed: 10/31/2023] Open
Abstract
Identification of tumor antigens presented by the human leucocyte antigen (HLA) molecules is essential for the design of effective and safe cancer immunotherapies that rely on T cell recognition and killing of tumor cells. Mass spectrometry (MS)-based immunopeptidomics enables high-throughput, direct identification of HLA-bound peptides from a variety of cell lines, tumor tissues, and healthy tissues. It involves immunoaffinity purification of HLA complexes followed by MS profiling of the extracted peptides using data-dependent acquisition, data-independent acquisition, or targeted approaches. By incorporating DNA, RNA, and ribosome sequencing data into immunopeptidomics data analysis, the proteogenomic approach provides a powerful means for identifying tumor antigens encoded within the canonical open reading frames of annotated coding genes and non-canonical tumor antigens derived from presumably non-coding regions of our genome. We discuss emerging computational challenges in immunopeptidomics data analysis and tumor antigen identification, highlighting key considerations in the proteogenomics-based approach, including accurate DNA, RNA and ribosomal sequencing data analysis, careful incorporation of predicted novel protein sequences into reference protein database, special quality control in MS data analysis due to the expanded and heterogeneous search space, cancer-specificity determination, and immunogenicity prediction. The advancements in technology and computation is continually enabling us to identify tumor antigens with higher sensitivity and accuracy, paving the way toward the development of more effective cancer immunotherapies.
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Affiliation(s)
- Bing Zhang
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
| | - Michal Bassani-Sternberg
- Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland
- Department of Oncology, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
- Agora Cancer Research Centre, Lausanne, Switzerland
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11
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Nicholas B, Skipp P. What do cancer-specific CD8+ T cells see? The contribution of immunopeptidomics. Essays Biochem 2023; 67:957-965. [PMID: 37503576 DOI: 10.1042/ebc20220246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 07/03/2023] [Accepted: 07/13/2023] [Indexed: 07/29/2023]
Abstract
Immunopeptidomics is the survey of all peptides displayed on a cell or tissue when bound to human leukocyte antigen (HLA) molecules using tandem mass spectrometry. When attempting to determine the targets of tumour-specific CD8+ T cells, a survey of the potential ligands in tumour tissues is invaluable, and, in comparison with in-silico predictions, provides greater certainty of the existence of individual epitopes, as immunopeptidomics-confirmed CD8+ T-cell epitopes are known to be immunogenic, and direct observation should avoid the risk of autoreactivity which could arise following immunisation with structural homologues. The canonical sources of CD8+ T-cell tumour specific epitopes, such as tumour associated antigens, may be well conserved between patients and tumour types, but are often only weakly immunogenic. Direct observation of tumour-specific neoantigens by immunopeptidomics is rare, although valuable. Thus, there has been increasing interest in the non-canonical origins of tumour-reactive CD8+ T-cell epitopes, such as those arising from proteasomal splicing events, translational/turnover defects and alternative open reading frame reads. Such epitopes can be identified in silico, although validation is more challenging. Non-self CD8+ T-cell epitopes such as viral epitopes may be useful in certain cancer types with known viral origins, however these have been relatively unexplored with immunopeptidomics to date, possibly due to the paucity of source viral proteins in tumour tissues. This review examines the latest evidence for canonical, non-canonical and non-human CD8+ T-cell epitopes identified by immunopeptidomics, and concludes that the relative contribution for each of these sources to anti-tumour CD8+ T-cell reactivity is currently uncertain.
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Affiliation(s)
- Ben Nicholas
- Centre for Proteomic Research, Biological Sciences and Institute for Life Sciences, Building 85, University of Southampton, SO17 1BJ, U.K
| | - Paul Skipp
- Centre for Proteomic Research, Biological Sciences and Institute for Life Sciences, Building 85, University of Southampton, SO17 1BJ, U.K
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12
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Stutzmann C, Peng J, Wu Z, Savoie C, Sirois I, Thibault P, Wheeler AR, Caron E. Unlocking the potential of microfluidics in mass spectrometry-based immunopeptidomics for tumor antigen discovery. CELL REPORTS METHODS 2023; 3:100511. [PMID: 37426761 PMCID: PMC10326451 DOI: 10.1016/j.crmeth.2023.100511] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
The identification of tumor-specific antigens (TSAs) is critical for developing effective cancer immunotherapies. Mass spectrometry (MS)-based immunopeptidomics has emerged as a powerful tool for identifying TSAs as physical molecules. However, current immunopeptidomics platforms face challenges in measuring low-abundance TSAs in a precise, sensitive, and reproducible manner from small needle-tissue biopsies (<1 mg). Inspired by recent advances in single-cell proteomics, microfluidics technology offers a promising solution to these limitations by providing improved isolation of human leukocyte antigen (HLA)-associated peptides with higher sensitivity. In this context, we highlight the challenges in sample preparation and the rationale for developing microfluidics technology in immunopeptidomics. Additionally, we provide an overview of promising microfluidic methods, including microchip pillar arrays, valved-based systems, droplet microfluidics, and digital microfluidics, and discuss the latest research on their application in MS-based immunopeptidomics and single-cell proteomics.
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Affiliation(s)
| | - Jiaxi Peng
- Department of Chemistry, University of Toronto, Toronto, ON, Canada
| | - Zhaoguan Wu
- CHU Sainte Justine Research Center, Montreal, QC, Canada
| | | | | | - Pierre Thibault
- Institute for Research in Immunology and Cancer, University of Montreal, Montreal, QC, Canada
- Department of Chemistry, University of Montreal, Montreal, QC, Canada
| | - Aaron R. Wheeler
- Department of Chemistry, University of Toronto, Toronto, ON, Canada
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada
| | - Etienne Caron
- CHU Sainte Justine Research Center, Montreal, QC, Canada
- Department of Pathology and Cellular Biology, University of Montreal, Montreal, QC, Canada
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13
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Lim Kam Sian TCC, Goncalves G, Steele JR, Shamekhi T, Bramberger L, Jin D, Shahbazy M, Purcell AW, Ramarathinam S, Stoychev S, Faridi P. SAPrIm, a semi-automated protocol for mid-throughput immunopeptidomics. Front Immunol 2023; 14:1107576. [PMID: 37334365 PMCID: PMC10272402 DOI: 10.3389/fimmu.2023.1107576] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 05/10/2023] [Indexed: 06/20/2023] Open
Abstract
Human leukocyte antigen (HLA) molecules play a crucial role in directing adaptive immune responses based on the nature of their peptide ligands, collectively coined the immunopeptidome. As such, the study of HLA molecules has been of major interest in the development of cancer immunotherapies such as vaccines and T-cell therapies. Hence, a comprehensive understanding and profiling of the immunopeptidome is required to foster the growth of these personalised solutions. We herein describe SAPrIm, an Immunopeptidomics tool for the Mid-Throughput era. This is a semi-automated workflow involving the KingFisher platform to isolate immunopeptidomes using anti-HLA antibodies coupled to a hyper-porous magnetic protein A microbead, a variable window data independent acquisition (DIA) method and the ability to run up to 12 samples in parallel. Using this workflow, we were able to concordantly identify and quantify ~400 - 13000 unique peptides from 5e5 - 5e7 cells, respectively. Overall, we propose that the application of this workflow will be crucial for the future of immunopeptidome profiling, especially for mid-size cohorts and comparative immunopeptidomics studies.
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Affiliation(s)
- Terry C. C. Lim Kam Sian
- Department of Medicine, School of Clinical Sciences, Faculty of Medicine, Nursing & Health Sciences, Monash University, Clayton, VIC, Australia
- Monash Proteomics and Metabolomics Platform, Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
| | - Gabriel Goncalves
- Department of Medicine, School of Clinical Sciences, Faculty of Medicine, Nursing & Health Sciences, Monash University, Clayton, VIC, Australia
- Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
| | - Joel R. Steele
- Monash Proteomics and Metabolomics Platform, Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
| | - Tima Shamekhi
- Department of Medicine, School of Clinical Sciences, Faculty of Medicine, Nursing & Health Sciences, Monash University, Clayton, VIC, Australia
| | - Liesl Bramberger
- Department of Medicine, School of Clinical Sciences, Faculty of Medicine, Nursing & Health Sciences, Monash University, Clayton, VIC, Australia
| | - Dongbin Jin
- Department of Medicine, School of Clinical Sciences, Faculty of Medicine, Nursing & Health Sciences, Monash University, Clayton, VIC, Australia
| | - Mohammad Shahbazy
- Department of Medicine, School of Clinical Sciences, Faculty of Medicine, Nursing & Health Sciences, Monash University, Clayton, VIC, Australia
- Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
| | - Anthony W. Purcell
- Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
| | - Sri Ramarathinam
- Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
| | | | - Pouya Faridi
- Department of Medicine, School of Clinical Sciences, Faculty of Medicine, Nursing & Health Sciences, Monash University, Clayton, VIC, Australia
- Monash Proteomics and Metabolomics Platform, Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
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14
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Oreper D, Klaeger S, Jhunjhunwala S, Delamarre L. The peptide woods are lovely, dark and deep: Hunting for novel cancer antigens. Semin Immunol 2023; 67:101758. [PMID: 37027981 DOI: 10.1016/j.smim.2023.101758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 03/22/2023] [Accepted: 03/22/2023] [Indexed: 04/08/2023]
Abstract
Harnessing the patient's immune system to control a tumor is a proven avenue for cancer therapy. T cell therapies as well as therapeutic vaccines, which target specific antigens of interest, are being explored as treatments in conjunction with immune checkpoint blockade. For these therapies, selecting the best suited antigens is crucial. Most of the focus has thus far been on neoantigens that arise from tumor-specific somatic mutations. Although there is clear evidence that T-cell responses against mutated neoantigens are protective, the large majority of these mutations are not immunogenic. In addition, most somatic mutations are unique to each individual patient and their targeting requires the development of individualized approaches. Therefore, novel antigen types are needed to broaden the scope of such treatments. We review high throughput approaches for discovering novel tumor antigens and some of the key challenges associated with their detection, and discuss considerations when selecting tumor antigens to target in the clinic.
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Affiliation(s)
- Daniel Oreper
- Genentech, 1 DNA way, South San Francisco, 94080 CA, USA.
| | - Susan Klaeger
- Genentech, 1 DNA way, South San Francisco, 94080 CA, USA.
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15
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Shapiro IE, Bassani-Sternberg M. The impact of immunopeptidomics: From basic research to clinical implementation. Semin Immunol 2023; 66:101727. [PMID: 36764021 DOI: 10.1016/j.smim.2023.101727] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 01/30/2023] [Accepted: 02/01/2023] [Indexed: 02/10/2023]
Abstract
The immunopeptidome is the set of peptides presented by the major histocompatibility complex (MHC) molecules, in humans also known as the human leukocyte antigen (HLA), on the surface of cells that mediate T-cell immunosurveillance. The immunopeptidome is a sampling of the cellular proteome and hence it contains information about the health state of cells. The peptide repertoire is influenced by intra- and extra-cellular perturbations - such as in the case of drug exposure, infection, or oncogenic transformation. Immunopeptidomics is the bioanalytical method by which the presented peptides are extracted from biological samples and analyzed by high-performance liquid chromatography coupled to tandem mass spectrometry (MS), resulting in a deep qualitative and quantitative snapshot of the immunopeptidome. In this review, we discuss published immunopeptidomics studies from recent years, grouped into three main domains: i) basic, ii) pre-clinical and iii) clinical research and applications. We review selected fundamental immunopeptidomics studies on the antigen processing and presentation machinery, on HLA restriction and studies that advanced our understanding of various diseases, and how exploration of the antigenic landscape allowed immune targeting at the pre-clinical stage, paving the way to pioneering exploratory clinical trials where immunopeptidomics is directly implemented in the conception of innovative treatments for cancer patients.
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Affiliation(s)
- Ilja E Shapiro
- Ludwig Institute for Cancer Research, University of Lausanne, 1005 Lausanne, Switzerland; Department of Oncology, Centre hospitalier universitaire vaudois (CHUV), 1005 Lausanne, Switzerland; Agora Cancer Research Centre, 1011 Lausanne, Switzerland
| | - Michal Bassani-Sternberg
- Ludwig Institute for Cancer Research, University of Lausanne, 1005 Lausanne, Switzerland; Department of Oncology, Centre hospitalier universitaire vaudois (CHUV), 1005 Lausanne, Switzerland; Agora Cancer Research Centre, 1011 Lausanne, Switzerland; Center of Experimental Therapeutics, Department of Oncology, Centre hospitalier universitaire vaudois (CHUV), 1005 Lausanne, Switzerland.
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16
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Ahn R, Cui Y, White FM. Antigen discovery for the development of cancer immunotherapy. Semin Immunol 2023; 66:101733. [PMID: 36841147 DOI: 10.1016/j.smim.2023.101733] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 02/15/2023] [Accepted: 02/16/2023] [Indexed: 02/25/2023]
Abstract
Central to successful cancer immunotherapy is effective T cell antitumor immunity. Multiple targeted immunotherapies engineered to invigorate T cell-driven antitumor immunity rely on identifying the repertoire of T cell antigens expressed on the tumor cell surface. Mass spectrometry-based survey of such antigens ("immunopeptidomics") combined with other omics platforms and computational algorithms has been instrumental in identifying and quantifying tumor-derived T cell antigens. In this review, we discuss the types of tumor antigens that have emerged for targeted cancer immunotherapy and the immunopeptidomics methods that are central in MHC peptide identification and quantification. We provide an overview of the strength and limitations of mass spectrometry-driven approaches and how they have been integrated with other technologies to discover targetable T cell antigens for cancer immunotherapy. We highlight some of the emerging cancer immunotherapies that successfully capitalized on immunopeptidomics, their challenges, and mass spectrometry-based strategies that can support their development.
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Affiliation(s)
- Ryuhjin Ahn
- David H. Koch Institute for Integrative Cancer Research, Cambridge, MA 02139, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Yufei Cui
- David H. Koch Institute for Integrative Cancer Research, Cambridge, MA 02139, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Forest M White
- David H. Koch Institute for Integrative Cancer Research, Cambridge, MA 02139, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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17
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Sun Z, Fu B, Wang G, Zhang L, Xu R, Zhang Y, Lu H. High-throughput site-specific N-glycoproteomics reveals glyco-signatures for liver disease diagnosis. Natl Sci Rev 2023; 10:nwac059. [PMID: 36879659 PMCID: PMC9985154 DOI: 10.1093/nsr/nwac059] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 03/15/2022] [Accepted: 03/15/2022] [Indexed: 11/13/2022] Open
Abstract
The glycoproteome has emerged as a prominent target for screening biomarkers, as altered glycosylation is a hallmark of cancer cells. In this work, we incorporated tandem mass tag labeling into quantitative glycoproteomics by developing a chemical labeling-assisted complementary dissociation method for the multiplexed analysis of intact N-glycopeptides. Benefiting from the complementary nature of two different mass spectrometry dissociation methods for identification and multiplex labeling for quantification of intact N-glycopeptides, we conducted the most comprehensive site-specific and subclass-specific N-glycosylation profiling of human serum immunoglobulin G (IgG) to date. By analysing the serum of 90 human patients with varying severities of liver diseases, as well as healthy controls, we identified that the combination of IgG1-H3N5F1 and IgG4-H4N3 can be used for distinguishing between different stages of liver diseases. Finally, we used targeted parallel reaction monitoring to successfully validate the expression changes of glycosylation in liver diseases in a different sample cohort that included 45 serum samples.
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Affiliation(s)
- Zhenyu Sun
- Shanghai Cancer Center and Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Bin Fu
- Department of Chemistry and NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai 200032, China
| | - Guoli Wang
- Shanghai Cancer Center and Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Lei Zhang
- Shanghai Cancer Center and Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Ruofan Xu
- Eleanor Roosevelt College, University of California San Diego, La Jolla, CA92093, USA
| | - Ying Zhang
- Shanghai Cancer Center and Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China.,Department of Chemistry and NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai 200032, China
| | - Haojie Lu
- Shanghai Cancer Center and Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China.,Department of Chemistry and NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai 200032, China
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18
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Immunopeptidomics-based design of mRNA vaccine formulations against Listeria monocytogenes. Nat Commun 2022; 13:6075. [PMID: 36241641 PMCID: PMC9562072 DOI: 10.1038/s41467-022-33721-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 09/29/2022] [Indexed: 12/24/2022] Open
Abstract
Listeria monocytogenes is a foodborne intracellular bacterial pathogen leading to human listeriosis. Despite a high mortality rate and increasing antibiotic resistance no clinically approved vaccine against Listeria is available. Attenuated Listeria strains offer protection and are tested as antitumor vaccine vectors, but would benefit from a better knowledge on immunodominant vector antigens. To identify novel antigens, we screen for Listeria peptides presented on the surface of infected human cell lines by mass spectrometry-based immunopeptidomics. In between more than 15,000 human self-peptides, we detect 68 Listeria immunopeptides from 42 different bacterial proteins, including several known antigens. Peptides presented on different cell lines are often derived from the same bacterial surface proteins, classifying these antigens as potential vaccine candidates. Encoding these highly presented antigens in lipid nanoparticle mRNA vaccine formulations results in specific CD8+ T-cell responses and induces protection in vaccination challenge experiments in mice. Our results can serve as a starting point for the development of a clinical mRNA vaccine against Listeria and aid to improve attenuated Listeria vaccines and vectors, demonstrating the power of immunopeptidomics for next-generation bacterial vaccine development.
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19
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Bernhardt M, Cruz-Garcia Y, Rech A, Meierjohann S, Erhard F, Schilling B, Schlosser A. Extending the Mass Spectrometry-Detectable Landscape of MHC Peptides by Use of Restricted Access Material. Anal Chem 2022; 94:14214-14222. [PMID: 36194871 DOI: 10.1021/acs.analchem.2c02198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Mass spectrometry-based immunopeptidomics enables the comprehensive identification of major histocompatibility complex (MHC) peptides from a cell culture as well as from tissue or tumor samples and is applied for the identification of tumor-specific and viral T-cell epitopes. Although mass spectrometry is generally considered an "unbiased" method for MHC peptide identification, the physicochemical properties of MHC peptides can greatly influence their detectability. Here, we demonstrate that highly hydrophobic peptides are lost during sample preparation when C18 solid-phase extraction (SPE) is used for separating MHC peptides from proteins. To overcome this limitation, we established an optimized protocol involving restricted access material (RAM). Compared to C18-SPE, RAM-SPE improved the overall MHC peptide recovery and extended the landscape of mass spectrometry-detectable MHC peptides toward more hydrophobic peptides.
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Affiliation(s)
- Melissa Bernhardt
- Rudolf Virchow Center, Center for Integrative and Translational Bioimaging, Julius Maximilians University Würzburg, 97080 Würzburg, Germany
| | - Yiliam Cruz-Garcia
- Department of Biochemistry and Molecular Biology, Julius Maximilians University Würzburg, 97080 Würzburg, Germany
| | - Anne Rech
- Department of Dermatology, Venereology, and Allergology, University Hospital Würzburg, 97080 Würzburg, Germany
| | - Svenja Meierjohann
- Institute of Pathology, Julius Maximilians University Würzburg, 97080 Würzburg, Germany
| | - Florian Erhard
- Institute for Virology and Immunobiology, Julius Maximilians University Würzburg, 97080 Würzburg, Germany
| | - Bastian Schilling
- Department of Dermatology, Venereology, and Allergology, University Hospital Würzburg, 97080 Würzburg, Germany
| | - Andreas Schlosser
- Rudolf Virchow Center, Center for Integrative and Translational Bioimaging, Julius Maximilians University Würzburg, 97080 Würzburg, Germany
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20
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Declercq A, Bouwmeester R, Hirschler A, Carapito C, Degroeve S, Martens L, Gabriels R. MS 2Rescore: Data-driven rescoring dramatically boosts immunopeptide identification rates. Mol Cell Proteomics 2022; 21:100266. [PMID: 35803561 PMCID: PMC9411678 DOI: 10.1016/j.mcpro.2022.100266] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 06/30/2022] [Accepted: 07/01/2022] [Indexed: 12/03/2022] Open
Abstract
Immunopeptidomics aims to identify major histocompatibility complex (MHC)-presented peptides on almost all cells that can be used in anti-cancer vaccine development. However, existing immunopeptidomics data analysis pipelines suffer from the nontryptic nature of immunopeptides, complicating their identification. Previously, peak intensity predictions by MS2PIP and retention time predictions by DeepLC have been shown to improve tryptic peptide identifications when rescoring peptide-spectrum matches with Percolator. However, as MS2PIP was tailored toward tryptic peptides, we have here retrained MS2PIP to include nontryptic peptides. Interestingly, the new models not only greatly improve predictions for immunopeptides but also yield further improvements for tryptic peptides. We show that the integration of new MS2PIP models, DeepLC, and Percolator in one software package, MS2Rescore, increases spectrum identification rate and unique identified peptides with 46% and 36% compared to standard Percolator rescoring at 1% FDR. Moreover, MS2Rescore also outperforms the current state-of-the-art in immunopeptide-specific identification approaches. Altogether, MS2Rescore thus allows substantially improved identification of novel epitopes from existing immunopeptidomics workflows. MS2Rescore significantly boosts immunopeptide identification rates Data-driven post-processing allows for a ten-fold increase in specificity MS2PIP and DeepLC predictors are integrated with Percolator post-processing MS2Rescore accepts identification results from MaxQuant, PEAKS, MS-GF+ and X!Tandem MS2Rescore shows great promise to extend current neo- and xeno-epitope landscapes
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Affiliation(s)
- Arthur Declercq
- VIB-UGent Center for Medical Biotechnology, VIB, Belgium; Department of Biomolecular Medicine, Ghent University, Belgium
| | - Robbin Bouwmeester
- VIB-UGent Center for Medical Biotechnology, VIB, Belgium; Department of Biomolecular Medicine, Ghent University, Belgium
| | - Aurélie Hirschler
- Laboratoire de Spectrométrie de Masse BioOrganique (LSMBO), Université de Strasbourg, CNRS
| | - Christine Carapito
- Laboratoire de Spectrométrie de Masse BioOrganique (LSMBO), Université de Strasbourg, CNRS
| | - Sven Degroeve
- VIB-UGent Center for Medical Biotechnology, VIB, Belgium; Department of Biomolecular Medicine, Ghent University, Belgium
| | - Lennart Martens
- VIB-UGent Center for Medical Biotechnology, VIB, Belgium; Department of Biomolecular Medicine, Ghent University, Belgium.
| | - Ralf Gabriels
- VIB-UGent Center for Medical Biotechnology, VIB, Belgium; Department of Biomolecular Medicine, Ghent University, Belgium
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21
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Yeung D, Anderson G, Spicer V, Krokhin OV. Chromatographic behaviour of peptides modified with amine-reacting tags for relative protein quantitation in proteomic applications. J Chromatogr A 2022; 1679:463391. [DOI: 10.1016/j.chroma.2022.463391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 07/27/2022] [Accepted: 07/29/2022] [Indexed: 10/16/2022]
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22
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Gabriel W, The M, Zolg DP, Bayer FP, Shouman O, Lautenbacher L, Schnatbaum K, Zerweck J, Knaute T, Delanghe B, Huhmer A, Wenschuh H, Reimer U, Médard G, Kuster B, Wilhelm M. Prosit-TMT: Deep Learning Boosts Identification of TMT-Labeled Peptides. Anal Chem 2022; 94:7181-7190. [PMID: 35549156 DOI: 10.1021/acs.analchem.1c05435] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The prediction of fragment ion intensities and retention time of peptides has gained significant attention over the past few years. However, the progress shown in the accurate prediction of such properties focused primarily on unlabeled peptides. Tandem mass tags (TMT) are chemical peptide labels that are coupled to free amine groups usually after protein digestion to enable the multiplexed analysis of multiple samples in bottom-up mass spectrometry. It is a standard workflow in proteomics ranging from single-cell to high-throughput proteomics. Particularly for TMT, increasing the number of confidently identified spectra is highly desirable as it provides identification and quantification information with every spectrum. Here, we report on the generation of an extensive resource of synthetic TMT-labeled peptides as part of the ProteomeTools project and present the extension of the deep learning model Prosit to accurately predict the retention time and fragment ion intensities of TMT-labeled peptides with high accuracy. Prosit-TMT supports CID and HCD fragmentation and ion trap and Orbitrap mass analyzers in a single model. Reanalysis of published TMT data sets show that this single model extracts substantial additional information. Applying Prosit-TMT, we discovered that the expression of many proteins in human breast milk follows a distinct daily cycle which may prime the newborn for nutritional or environmental cues.
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Affiliation(s)
- Wassim Gabriel
- Computational Mass Spectrometry, Technical University of Munich, 85354 Freising, Germany
| | - Matthew The
- Chair of Proteomics and Bioanalytics, Technical University of Munich, 85354 Freising, Germany
| | - Daniel P Zolg
- Chair of Proteomics and Bioanalytics, Technical University of Munich, 85354 Freising, Germany
| | - Florian P Bayer
- Chair of Proteomics and Bioanalytics, Technical University of Munich, 85354 Freising, Germany
| | - Omar Shouman
- Computational Mass Spectrometry, Technical University of Munich, 85354 Freising, Germany
| | - Ludwig Lautenbacher
- Computational Mass Spectrometry, Technical University of Munich, 85354 Freising, Germany
| | | | | | - Tobias Knaute
- JPT Peptide Technologies GmbH, 12489 Berlin, Germany
| | | | - Andreas Huhmer
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | | | - Ulf Reimer
- JPT Peptide Technologies GmbH, 12489 Berlin, Germany
| | - Guillaume Médard
- Chair of Proteomics and Bioanalytics, Technical University of Munich, 85354 Freising, Germany
| | - Bernhard Kuster
- Chair of Proteomics and Bioanalytics, Technical University of Munich, 85354 Freising, Germany.,Bavarian Center for Biomolecular Mass Spectrometry, 85354 Freising, Germany
| | - Mathias Wilhelm
- Computational Mass Spectrometry, Technical University of Munich, 85354 Freising, Germany
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23
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Cleyle J, Hardy MP, Minati R, Courcelles M, Durette C, Lanoix J, Laverdure JP, Vincent K, Perreault C, Thibault P. Immunopeptidomic analyses of colorectal cancers with and without microsatellite instability. Mol Cell Proteomics 2022; 21:100228. [PMID: 35367648 PMCID: PMC9134101 DOI: 10.1016/j.mcpro.2022.100228] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 03/17/2022] [Accepted: 03/18/2022] [Indexed: 02/07/2023] Open
Abstract
Colorectal cancer is the second leading cause of cancer death worldwide, and the incidence of this disease is expected to increase as global socioeconomic changes occur. Immune checkpoint inhibition therapy is effective in treating a minority of colorectal cancer tumors; however, microsatellite stable tumors do not respond well to this treatment. Emerging cancer immunotherapeutic strategies aim to activate a cytotoxic T cell response against tumor-specific antigens, presented exclusively at the cell surface of cancer cells. These antigens are rare and are most effectively identified with a mass spectrometry-based approach, which allows the direct sampling and sequencing of these peptides. Although the few tumor-specific antigens identified to date are derived from coding regions of the genome, recent findings indicate that a large proportion of tumor-specific antigens originate from allegedly noncoding regions. Here, we employed a novel proteogenomic approach to identify tumor antigens in a collection of colorectal cancer-derived cell lines and biopsy samples consisting of matched tumor and normal adjacent tissue. The generation of personalized cancer databases paired with mass spectrometry analyses permitted the identification of more than 30,000 unique MHC I-associated peptides. We identified 19 tumor-specific antigens in both microsatellite stable and unstable tumors, over two-thirds of which were derived from noncoding regions. Many of these peptides were derived from source genes known to be involved in colorectal cancer progression, suggesting that antigens from these genes could have therapeutic potential in a wide range of tumors. These findings could benefit the development of T cell-based vaccines, in which T cells are primed against these antigens to target and eradicate tumors. Such a vaccine could be used in tandem with existing immune checkpoint inhibition therapies, to bridge the gap in treatment efficacy across subtypes of colorectal cancer with varying prognoses. Data are available via ProteomeXchange with identifier PXD028309.
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Affiliation(s)
- Jenna Cleyle
- Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Quebec, Canada; Molecular Biology Program, Université de Montréal, Montreal, Quebec, Canada
| | - Marie-Pierre Hardy
- Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Quebec, Canada
| | - Robin Minati
- Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Quebec, Canada; Molecular Biology Program, Université de Montréal, Montreal, Quebec, Canada
| | - Mathieu Courcelles
- Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Quebec, Canada
| | - Chantal Durette
- Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Quebec, Canada
| | - Joel Lanoix
- Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Quebec, Canada
| | - Jean-Philippe Laverdure
- Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Quebec, Canada
| | - Krystel Vincent
- Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Quebec, Canada
| | - Claude Perreault
- Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Quebec, Canada; Department of Medicine, Université de Montréal, Montreal, Quebec, Canada.
| | - Pierre Thibault
- Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Quebec, Canada; Department of Chemistry, Université de Montréal, Montreal, Quebec, Canada.
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24
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Mizero B, Villacrés C, Spicer V, Viner R, Saba J, Patel B, Snovida S, Jensen P, Huhmer A, Krokhin OV. Retention Time Prediction for TMT-Labeled Peptides in Proteomic LC-MS Experiments. J Proteome Res 2022; 21:1218-1228. [PMID: 35363494 DOI: 10.1021/acs.jproteome.1c00833] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We present the first detailed study of chromatographic behavior of peptides labeled with tandem mass tags (TMT and TMTpro) in 2D LC for proteomic applications. Carefully designed experimental procedures have permitted generating data sets of over 100,000 nonlabeled and TMT-labeled peptide pairs for the low pH RP in the second separation dimension and data sets of over 10,000 peptide pairs for high-pH RP, HILIC (amide and silica), and SCX separations in the first separation dimension. The average increase in peptide RPLC (0.1% formic acid) retention upon TMT labeling was found to be 3.3% acetonitrile (linear water/acetonitrile gradients), spanning a range of -4 to 10.3%. In addition to the bulk peptide properties such as length, hydrophobicity, and the number of labeled residues, we found several sequence-dependent features mostly associated with differences in N-terminal chemistry. The behavior of TMTpro-labeled peptides was found to be very similar except for a slightly higher hydrophobicity: an average retention shift of 3.7% acetonitrile. The respective versions of the sequence-specific retention calculator (SSRCalc) model have been developed to accommodate both TMT chemistries, showing identical prediction accuracy (R2 ∼ 0.98) for labeled and nonlabeled peptides. Higher retention for TMT-labeled peptides was observed for high-pH RP and HILIC separations, while SCX selectivity remained virtually unchanged.
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Affiliation(s)
- Benilde Mizero
- Department of Chemistry, University of Manitoba, Winnipeg R3T 2N2, Canada
| | - Carina Villacrés
- Manitoba Centre for Proteomics and Systems Biology, Winnipeg R3E 3P4, Canada
| | - Victor Spicer
- Manitoba Centre for Proteomics and Systems Biology, Winnipeg R3E 3P4, Canada
| | - Rosa Viner
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | - Julian Saba
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | | | - Sergei Snovida
- Thermo Fisher Scientific, Rockford, Illinois 61101, United States
| | - Penny Jensen
- Thermo Fisher Scientific, Rockford, Illinois 61101, United States
| | - Andreas Huhmer
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | - Oleg V Krokhin
- Department of Chemistry, University of Manitoba, Winnipeg R3T 2N2, Canada.,Manitoba Centre for Proteomics and Systems Biology, Winnipeg R3E 3P4, Canada.,Department of Internal Medicine, University of Manitoba, Winnipeg R3E 3P4, Canada
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25
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Bollineni RC, Tran TT, Lund-Johansen F, Olweus J. Chasing neoantigens; invite naïve T cells to the party. Curr Opin Immunol 2022; 75:102172. [DOI: 10.1016/j.coi.2022.102172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Accepted: 02/17/2022] [Indexed: 11/03/2022]
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26
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Pfeiffer CT, Paulo JA, Gygi SP, Rockman HA. Proximity labeling for investigating protein-protein interactions. Methods Cell Biol 2022; 169:237-266. [PMID: 35623704 PMCID: PMC10782847 DOI: 10.1016/bs.mcb.2021.12.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The study of protein complexes and protein-protein interactions is of great importance due to their fundamental roles in cellular function. Proximity labeling, often coupled with mass spectrometry, has become a powerful and versatile tool for studying protein-protein interactions by enriching and identifying proteins in the vicinity of a specified protein-of-interest. Here, we describe and compare traditional approaches to investigate protein-protein interactions to current day state-of-the-art proximity labeling methods. We focus on the wide array of proximity labeling strategies and underscore studies using diverse model systems to address numerous biological questions. In addition, we highlight current advances in mass spectrometry-based technology that exhibit promise in improving the depth and breadth of the data acquired in proximity labeling experiments. In all, we show the diversity of proximity labeling strategies and emphasize the broad range of applications and biological inquiries that can be addressed using this technology.
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Affiliation(s)
- Conrad T Pfeiffer
- Department of Medicine, Duke University Medical Center, Durham, NC, United States
| | - Joao A Paulo
- Department of Cell Biology, Harvard Medical School, Boston, MA, United States
| | - Steven P Gygi
- Department of Cell Biology, Harvard Medical School, Boston, MA, United States
| | - Howard A Rockman
- Department of Medicine, Duke University Medical Center, Durham, NC, United States; Department of Cell Biology, Duke University Medical Center, Durham, NC, United States.
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27
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Omenn GS, Lane L, Overall CM, Paik YK, Cristea IM, Corrales FJ, Lindskog C, Weintraub S, Roehrl MHA, Liu S, Bandeira N, Srivastava S, Chen YJ, Aebersold R, Moritz RL, Deutsch EW. Progress Identifying and Analyzing the Human Proteome: 2021 Metrics from the HUPO Human Proteome Project. J Proteome Res 2021; 20:5227-5240. [PMID: 34670092 DOI: 10.1021/acs.jproteome.1c00590] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The 2021 Metrics of the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 357 (92.8%) of the 19 778 predicted proteins coded in the human genome, a gain of 483 since 2020 from reports throughout the world reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 478 to 1421. This represents remarkable progress on the proteome parts list. The utilization of proteomics in a broad array of biological and clinical studies likewise continues to expand with many important findings and effective integration with other omics platforms. We present highlights from the Immunopeptidomics, Glycoproteomics, Infectious Disease, Cardiovascular, Musculo-Skeletal, Liver, and Cancers B/D-HPP teams and from the Knowledgebase, Mass Spectrometry, Antibody Profiling, and Pathology resource pillars, as well as ethical considerations important to the clinical utilization of proteomics and protein biomarkers.
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Affiliation(s)
- Gilbert S Omenn
- University of Michigan, Ann Arbor, Michigan 48109, United States.,Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Lydie Lane
- CALIPHO Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | | | - Young-Ki Paik
- Yonsei Proteome Research Center and Yonsei University, Seoul 03722, Korea
| | - Ileana M Cristea
- Princeton University, Princeton, New Jersey 08544, United States
| | | | | | - Susan Weintraub
- University of Texas Health, San Antonio, San Antonio, Texas 78229-3900, United States
| | - Michael H A Roehrl
- Memorial Sloan Kettering Cancer Center, New York, New York 10065, United States
| | - Siqi Liu
- BGI Group, Shenzhen 518083, China
| | - Nuno Bandeira
- University of California, San Diego, La Jolla, California 92093, United States
| | | | - Yu-Ju Chen
- National Taiwan University, Academia Sinica, Nankang, Taipei 11529, Taiwan
| | - Ruedi Aebersold
- ETH-Zurich and University of Zurich, 8092 Zurich, Switzerland
| | - Robert L Moritz
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Eric W Deutsch
- Institute for Systems Biology, Seattle, Washington 98109, United States
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28
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Liu X, Fields R, Schweppe DK, Paulo JA. Strategies for mass spectrometry-based phosphoproteomics using isobaric tagging. Expert Rev Proteomics 2021; 18:795-807. [PMID: 34652972 DOI: 10.1080/14789450.2021.1994390] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
INTRODUCTION Protein phosphorylation is a primary mechanism of signal transduction in cellular systems. Isobaric tagging can be used to investigate alterations in phosphorylation events in sample multiplexing experiments where quantification extends across all conditions. As such, innovations in tandem mass tag methods can facilitate the expansion of the depth and breadth of phosphoproteomic analyses. AREAS COVERED This review discusses the current state of tandem mass tag-centric phosphoproteomics and highlights advances in reagent chemistry, instrumentation, data acquisition, and data analysis. We stress that approaches for phosphoproteomic investigations require high-specificity enrichment, sensitive detection, and accurate phosphorylation site localization. EXPERT OPINION Tandem mass tag-centric phosphoproteomics will continue to be an important conduit for our understanding of signal transduction in living organisms. We anticipate that progress in phosphopeptide enrichment methodologies, enhancements in instrumentation and data acquisition technologies, and further refinements in analytical strategies will be key to the discovery of biologically relevant findings from phosphoproteomics studies.
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Affiliation(s)
- Xinyue Liu
- Department of Cell Biology, Harvard Medical School, Boston, USA
| | - Rose Fields
- Department of Genome Sciences, University of Washington, Seattle, USA
| | - Devin K Schweppe
- Department of Genome Sciences, University of Washington, Seattle, USA
| | - Joao A Paulo
- Department of Cell Biology, Harvard Medical School, Boston, USA
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29
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Stopfer L, D'Souza A, White F. 1,2,3, MHC: a review of mass-spectrometry-based immunopeptidomics methods for relative and absolute quantification of pMHCs. IMMUNO-ONCOLOGY TECHNOLOGY 2021; 11:100042. [PMID: 35756972 PMCID: PMC9216433 DOI: 10.1016/j.iotech.2021.100042] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Quantitative mass-spectrometry-based methods to perform relative and absolute quantification of peptides in the immunopeptidome are growing in popularity as researchers aim to measure the dynamic nature of the peptide major histocompatibility complex repertoire and make copies-per-cell estimations of target antigens of interest. Multiple methods to carry out these experiments have been reported, each with unique advantages and limitations. This article describes existing methods and recent applications, offering guidance for improving quantitative accuracy and selecting an appropriate experimental set-up to maximize data quality and quantity.
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Affiliation(s)
- L.E. Stopfer
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, USA,Koch Institute for Integrative Cancer Research, Center for Precision Cancer Medicine, Massachusetts Institute of Technology, Cambridge, USA
| | - A.D. D'Souza
- Koch Institute for Integrative Cancer Research, Center for Precision Cancer Medicine, Massachusetts Institute of Technology, Cambridge, USA,Program in Health Sciences and Technology, Harvard Medical School and Massachusetts Institute of Technology, Boston, USA
| | - F.M. White
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, USA,Koch Institute for Integrative Cancer Research, Center for Precision Cancer Medicine, Massachusetts Institute of Technology, Cambridge, USA,Correspondence to: Prof. Forest M. White, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Tel: 617-258-8949
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30
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Identification of tumor antigens with immunopeptidomics. Nat Biotechnol 2021; 40:175-188. [PMID: 34635837 DOI: 10.1038/s41587-021-01038-8] [Citation(s) in RCA: 92] [Impact Index Per Article: 30.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 07/29/2021] [Indexed: 12/18/2022]
Abstract
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.
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31
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Zitvogel L, Perreault C, Finn OJ, Kroemer G. Beneficial autoimmunity improves cancer prognosis. Nat Rev Clin Oncol 2021; 18:591-602. [PMID: 33976418 DOI: 10.1038/s41571-021-00508-x] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/26/2021] [Indexed: 02/06/2023]
Abstract
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.
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Affiliation(s)
- Laurence Zitvogel
- Gustave Roussy Comprehensive Cancer Institute, Villejuif, France. .,Université Paris Saclay, Faculty of Medicine, Le Kremlin-Bicêtre, France. .,INSERM U1015, Gustave Roussy, Villejuif, France. .,Equipe labellisée par la Ligue contre le cancer, Villejuif, France. .,Center of Clinical Investigations in Biotherapies of Cancer (CICBT) BIOTHERIS, Villejuif, France. .,Suzhou Institute for Systems Medicine, Chinese Academy of Medical Sciences, Suzhou, China.
| | - Claude Perreault
- Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC, Canada
| | - Olivera J Finn
- Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Guido Kroemer
- Gustave Roussy Comprehensive Cancer Institute, Villejuif, France. .,Suzhou Institute for Systems Medicine, Chinese Academy of Medical Sciences, Suzhou, China. .,Equipe labellisée par la Ligue contre le cancer, Université de Paris, Sorbonne Université, INSERM U1138, Centre de Recherche des Cordeliers, Institut Universitaire de France, Paris, France. .,Metabolomics and Cell Biology Platforms, Institut Gustave Roussy, Villejuif, France. .,Pôle de Biologie, Hôpital Européen Georges Pompidou, AP-HP, Paris, France. .,Karolinska Institute, Department of Women's and Children's Health, Karolinska University Hospital, Stockholm, Sweden.
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32
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Klaeger S, Apffel A, Clauser KR, Sarkizova S, Oliveira G, Rachimi S, Le PM, Tarren A, Chea V, Abelin JG, Braun DA, Ott PA, Keshishian H, Hacohen N, Keskin DB, Wu CJ, Carr SA. Optimized liquid and gas phase fractionation increases HLA-peptidome coverage for primary cell and tissue samples. Mol Cell Proteomics 2021; 20:100133. [PMID: 34391888 PMCID: PMC8724927 DOI: 10.1016/j.mcpro.2021.100133] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 07/08/2021] [Accepted: 08/01/2021] [Indexed: 12/20/2022] Open
Abstract
Mass spectrometry is the most effective method to directly identify peptides presented on 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 off-line followed by ion mobility coupled to LC-MS/MS for analysis. The combination of these two separation methods enabled identification of 20% to 50% more peptides compared to samples analyzed without either prior fractionation or use of ion mobility alone. We demonstrate coverage of HLA immunopeptidomes with up to 8,107 distinct peptides starting with as few as 100 million cells. The increased sensitivity obtained using our methods can provide data useful to improve HLA binding prediction algorithms as well as to enable detection of clinically relevant epitopes such as neoantigens.
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Affiliation(s)
- Susan Klaeger
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Annie Apffel
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | | | - Giacomo Oliveira
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | | | - Phuong M Le
- Translational Immunogenomics Laboratory, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Anna Tarren
- Translational Immunogenomics Laboratory, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Vipheaviny Chea
- Translational Immunogenomics Laboratory, Dana-Farber Cancer Institute, Boston, MA, USA
| | | | - David A Braun
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Patrick A Ott
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Nir Hacohen
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Massachusetts General Hospital Cancer Center, Boston, MA, USA
| | - Derin B Keskin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Translational Immunogenomics Laboratory, Dana-Farber Cancer Institute, Boston, MA, USA; Health Informatics Lab, Metropolitan College, Boston University, Boston, MA, USA
| | - Catherine J Wu
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Steven A Carr
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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33
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Taylor HB, Klaeger S, Clauser KR, Sarkizova S, Weingarten-Gabbay S, Graham DB, Carr SA, Abelin JG. MS-Based HLA-II Peptidomics Combined With Multiomics Will Aid the Development of Future Immunotherapies. Mol Cell Proteomics 2021; 20:100116. [PMID: 34146720 PMCID: PMC8327157 DOI: 10.1016/j.mcpro.2021.100116] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 06/02/2021] [Accepted: 06/03/2021] [Indexed: 12/25/2022] Open
Abstract
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.
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Affiliation(s)
- Hannah B Taylor
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Susan Klaeger
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Karl R Clauser
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | | | - Shira Weingarten-Gabbay
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, USA
| | - Daniel B Graham
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA; Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Steven A Carr
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
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Pollock SB, Rose CM, Darwish M, Bouziat R, Delamarre L, Blanchette C, Lill JR. Sensitive and Quantitative Detection of MHC-I Displayed Neoepitopes Using a Semiautomated Workflow and TOMAHAQ Mass Spectrometry. Mol Cell Proteomics 2021; 20:100108. [PMID: 34129938 PMCID: PMC8255936 DOI: 10.1016/j.mcpro.2021.100108] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 04/28/2021] [Accepted: 06/04/2021] [Indexed: 12/26/2022] Open
Abstract
Advances in several key technologies, including MHC peptidomics, have helped fuel our understanding of basic immune regulatory mechanisms and the identification of 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. However, the current multistep analytical process is challenging, and improvements in throughput and reproducibility would enable rapid characterization of 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 such as MC38, can be enriched in a semiautomated fashion on reusable, dry-storage, customized antibody cartridges. Using this method, a researcher, with very little hands-on time and in a single day, can perform up to 96 simultaneous enrichments at a similar level of quality as a manual workflow. TOMAHAQ (Triggered by Offset, Multiplexed, Accurate-mass, High-resolution, and Absolute Quantification), 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. This unique combination of robust semiautomated MHC-I peptide isolation and high-throughput multiplexed targeted quantitation allows for both the routine analysis of >4000 unique MHC-I peptides from 250 million cells using nontargeted methods, as well as quantitative sensitivity down to the low amol/μl level using TOMAHAQ targeted MS. Semiautomated peptide immunoprecipitation on reusable antibody cartridges. Application of TOMAHAQ for MHC-I detection and quantitation. Routine analysis of >4000 unique MHC-I peptides from 250 million cells via automation. Quantitative sensitivity down to the low amol/μl level using TOMAHAQ targeted MS.
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Affiliation(s)
- Samuel B Pollock
- Department of Microchemistry, Proteomics, Lipidomics and Next Generation Sequencing, Genentech, South San Francisco, California, USA
| | - Christopher M Rose
- Department of Microchemistry, Proteomics, Lipidomics and Next Generation Sequencing, Genentech, South San Francisco, California, USA
| | - Martine Darwish
- Department of Protein Chemistry, Genentech, South San Francisco, California, USA
| | - Romain Bouziat
- Department of Cancer Immunology, Genentech, South San Francisco, California, USA
| | - Lélia Delamarre
- Department of Cancer Immunology, Genentech, South San Francisco, California, USA
| | - Craig Blanchette
- Department of Protein Chemistry, Genentech, South San Francisco, California, USA
| | - Jennie R Lill
- Department of Microchemistry, Proteomics, Lipidomics and Next Generation Sequencing, Genentech, South San Francisco, California, USA.
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35
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Mayer RL, Impens F. Immunopeptidomics for next-generation bacterial vaccine development. Trends Microbiol 2021; 29:1034-1045. [PMID: 34030969 DOI: 10.1016/j.tim.2021.04.010] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 04/28/2021] [Accepted: 04/30/2021] [Indexed: 12/12/2022]
Abstract
Antimicrobial resistance is an increasing global threat and alternative treatments substituting failing antibiotics are urgently needed. Vaccines are recognized as highly effective tools to mitigate antimicrobial resistance; however, the selection of bacterial antigens as vaccine candidates remains challenging. In recent years, advances in mass spectrometry-based proteomics have led to the development of so-called immunopeptidomics approaches that allow the untargeted discovery of bacterial epitopes that are presented on the surface of infected cells. Especially for intracellular bacterial pathogens, immunopeptidomics holds great promise to uncover antigens that can be encoded in viral vector- or nucleic acid-based vaccines. This review provides an overview of immunopeptidomics studies on intracellular bacterial pathogens and considers future directions and challenges in advancing towards next-generation vaccines.
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Affiliation(s)
- Rupert L Mayer
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium; VIB Proteomics Core, VIB, Ghent, Belgium
| | - Francis Impens
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium; VIB Proteomics Core, VIB, Ghent, Belgium.
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36
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Pak H, Michaux J, Huber F, Chong C, Stevenson BJ, Müller M, Coukos G, Bassani-Sternberg M. Sensitive Immunopeptidomics by Leveraging Available Large-Scale Multi-HLA Spectral Libraries, Data-Independent Acquisition, and MS/MS Prediction. Mol Cell Proteomics 2021; 20:100080. [PMID: 33845167 PMCID: PMC8724634 DOI: 10.1016/j.mcpro.2021.100080] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 03/18/2021] [Accepted: 04/05/2021] [Indexed: 12/15/2022] Open
Abstract
Mass spectrometry (MS) is the state-of-the-art methodology for capturing the breadth and depth of the immunopeptidome across human leukocyte antigen (HLA) allotypes and cell types. The majority of studies in the immunopeptidomics field are discovery driven. Hence, data-dependent tandem MS (MS/MS) acquisition (DDA) is widely used, as it generates high-quality references of peptide fingerprints. However, DDA suffers from the stochastic selection of abundant ions that impairs sensitivity and reproducibility. In contrast, in data-independent acquisition (DIA), the systematic fragmentation and acquisition of all fragment ions within given isolation m/z windows yield a comprehensive map for a given sample. However, many DIA approaches commonly require generating comprehensive DDA-based spectrum libraries, which can become impractical for studying noncanonical and personalized neoantigens. Because the amount of HLA peptides eluted from biological samples such as small tissue biopsies is typically not sufficient for acquiring both meaningful DDA data necessary for generating comprehensive spectral libraries and DIA MS measurements, the implementation of DIA in the immunopeptidomics translational research domain has remained limited. We implemented a DIA immunopeptidomics workflow and assessed its sensitivity and accuracy by matching DIA data against libraries with growing complexity-from sample-specific libraries to libraries combining 2 to 40 different immunopeptidomics samples. Analyzing DIA immunopeptidomics data against a complex multi-HLA spectral library resulted in a two-fold increase in peptide identification compared with sample-specific library and in a three-fold increase compared with DDA measurements, yet with no detrimental effect on the specificity. Furthermore, we demonstrated the implementation of DIA for sensitive personalized neoantigen discovery through the analysis of DIA data with predicted MS/MS spectra of clinically relevant HLA ligands. We conclude that a comprehensive multi-HLA library for DIA approach in combination with MS/MS prediction is highly advantageous for clinical immunopeptidomics, especially when low amounts of biological samples are available.
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Affiliation(s)
- HuiSong Pak
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland
| | - Justine Michaux
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland
| | - Florian Huber
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland
| | - Chloe Chong
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland
| | | | - Markus Müller
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - George Coukos
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland
| | - Michal Bassani-Sternberg
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland.
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37
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Mpakali A, Stratikos E. The Role of Antigen Processing and Presentation in Cancer and the Efficacy of Immune Checkpoint Inhibitor Immunotherapy. Cancers (Basel) 2021; 13:E134. [PMID: 33406696 PMCID: PMC7796214 DOI: 10.3390/cancers13010134] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2020] [Revised: 12/28/2020] [Accepted: 12/30/2020] [Indexed: 02/07/2023] Open
Abstract
Recent clinical successes of cancer immunotherapy using immune checkpoint inhibitors (ICIs) are rapidly changing the landscape of cancer treatment. Regardless of initial impressive clinical results though, the therapeutic benefit of ICIs appears to be limited to a subset of patients and tumor types. Recent analyses have revealed that the potency of ICI therapies depends on the efficient presentation of tumor-specific antigens by cancer cells and professional antigen presenting cells. Here, we review current knowledge on the role of antigen presentation in cancer. We focus on intracellular antigen processing and presentation by Major Histocompatibility class I (MHCI) molecules and how it can affect cancer immune evasion. Finally, we discuss the pharmacological tractability of manipulating intracellular antigen processing as a complementary approach to enhance tumor immunogenicity and the effectiveness of ICI immunotherapy.
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Affiliation(s)
- Anastasia Mpakali
- National Centre for Scientific Research Demokritos, Agia Paraskevi, 15341 Athens, Greece
| | - Efstratios Stratikos
- National Centre for Scientific Research Demokritos, Agia Paraskevi, 15341 Athens, Greece
- Laboratory of Biochemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zographou, 15784 Athens, Greece
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Khazaei S, De Jay N, Deshmukh S, Hendrikse LD, Jawhar W, Chen CCL, Mikael LG, Faury D, Marchione DM, Lanoix J, Bonneil É, Ishii T, Jain SU, Rossokhata K, Sihota TS, Eveleigh R, Lisi V, Harutyunyan AS, Jung S, Karamchandani J, Dickson BC, Turcotte R, Wunder JS, Thibault P, Lewis PW, Garcia BA, Mack SC, Taylor MD, Garzia L, Kleinman CL, Jabado N. H3.3 G34W Promotes Growth and Impedes Differentiation of Osteoblast-Like Mesenchymal Progenitors in Giant Cell Tumor of Bone. Cancer Discov 2020; 10:1968-1987. [PMID: 32967858 PMCID: PMC7710565 DOI: 10.1158/2159-8290.cd-20-0461] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 08/10/2020] [Accepted: 09/17/2020] [Indexed: 11/16/2022]
Abstract
Glycine 34-to-tryptophan (G34W) substitutions in H3.3 arise in approximately 90% of giant cell tumor of bone (GCT). Here, we show H3.3 G34W is necessary for tumor formation. By profiling the epigenome, transcriptome, and secreted proteome of patient samples and tumor-derived cells CRISPR-Cas9-edited for H3.3 G34W, we show that H3.3K36me3 loss on mutant H3.3 alters the deposition of the repressive H3K27me3 mark from intergenic to genic regions, beyond areas of H3.3 deposition. This promotes redistribution of other chromatin marks and aberrant transcription, altering cell fate in mesenchymal progenitors and hindering differentiation. Single-cell transcriptomics reveals that H3.3 G34W stromal cells recapitulate a neoplastic trajectory from a SPP1+ osteoblast-like progenitor population toward an ACTA2+ myofibroblast-like population, which secretes extracellular matrix ligands predicted to recruit and activate osteoclasts. Our findings suggest that H3.3 G34W leads to GCT by sustaining a transformed state in osteoblast-like progenitors, which promotes neoplastic growth, pathologic recruitment of giant osteoclasts, and bone destruction. SIGNIFICANCE: This study shows that H3.3 G34W drives GCT tumorigenesis through aberrant epigenetic remodeling, altering differentiation trajectories in mesenchymal progenitors. H3.3 G34W promotes in neoplastic stromal cells an osteoblast-like progenitor state that enables undue interactions with the tumor microenvironment, driving GCT pathogenesis. These epigenetic changes may be amenable to therapeutic targeting in GCT.See related commentary by Licht, p. 1794.This article is highlighted in the In This Issue feature, p. 1775.
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Affiliation(s)
- Sima Khazaei
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Nicolas De Jay
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
- Lady Davis Research Institute, Jewish General Hospital, Montreal, Quebec, Canada
| | - Shriya Deshmukh
- Department of Experimental Medicine, McGill University, Montreal, Quebec, Canada
| | - Liam D Hendrikse
- Cancer and Stem Cell Biology Program, The Hospital for Sick Children, Toronto, Ontario, Canada
- The Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Wajih Jawhar
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
- Cancer Research Program, The Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
| | - Carol C L Chen
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Leonie G Mikael
- Department of Pediatrics, McGill University, and The Research Institute of the McGill University Health Center, Montreal, Quebec, Canada
| | - Damien Faury
- Department of Pediatrics, McGill University, and The Research Institute of the McGill University Health Center, Montreal, Quebec, Canada
| | - Dylan M Marchione
- Department of Biochemistry and Biophysics, and Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Joel Lanoix
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, Quebec, Canada
| | - Éric Bonneil
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, Quebec, Canada
| | - Takeaki Ishii
- Cancer Research Program, The Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
- Department of Experimental Surgery, McGill University, Montreal, Quebec, Canada
| | - Siddhant U Jain
- Department of Biomolecular Chemistry, School of Medicine and Public Health and Wisconsin Institute for Discovery, University of Wisconsin, Madison, Wisconsin
| | | | - Tianna S Sihota
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Robert Eveleigh
- McGill University and Génome Québec Innovation Centre, Montreal, Quebec, Canada
| | - Véronique Lisi
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Ashot S Harutyunyan
- Department of Pediatrics, McGill University, and The Research Institute of the McGill University Health Center, Montreal, Quebec, Canada
| | - Sungmi Jung
- Department of Pathology, McGill University Health Centre, Montreal, Quebec, Canada
| | - Jason Karamchandani
- Department of Pathology, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Brendan C Dickson
- Department of Pathology and Laboratory Medicine, Mt. Sinai Hospital, Toronto, Ontario, Canada
| | - Robert Turcotte
- Division of Orthopaedic Surgery, McGill University, Montreal, Quebec, Canada
| | - Jay S Wunder
- University of Toronto Musculoskeletal Oncology Unit, Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Surgical Oncology, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Pierre Thibault
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, Quebec, Canada
- Department of Chemistry, Université de Montréal, Montreal, Quebec, Canada
| | - Peter W Lewis
- Department of Biomolecular Chemistry, School of Medicine and Public Health and Wisconsin Institute for Discovery, University of Wisconsin, Madison, Wisconsin
| | - Benjamin A Garcia
- Department of Biochemistry and Biophysics, and Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Stephen C Mack
- Department of Pediatrics, Division of Hematology and Oncology, Texas Children's Cancer and Hematology Centers, Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Michael D Taylor
- Cancer and Stem Cell Biology Program, The Hospital for Sick Children, Toronto, Ontario, Canada
- The Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Livia Garzia
- Cancer Research Program, The Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
- Division of Orthopaedic Surgery, McGill University, Montreal, Quebec, Canada
| | - Claudia L Kleinman
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada.
- Lady Davis Research Institute, Jewish General Hospital, Montreal, Quebec, Canada
| | - Nada Jabado
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada.
- Department of Experimental Medicine, McGill University, Montreal, Quebec, Canada
- Department of Pediatrics, McGill University, and The Research Institute of the McGill University Health Center, Montreal, Quebec, Canada
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39
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Apavaloaei A, Hardy MP, Thibault P, Perreault C. The Origin and Immune Recognition of Tumor-Specific Antigens. Cancers (Basel) 2020; 12:E2607. [PMID: 32932620 PMCID: PMC7565792 DOI: 10.3390/cancers12092607] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 09/09/2020] [Accepted: 09/11/2020] [Indexed: 02/07/2023] Open
Abstract
The dominant paradigm holds that spontaneous and therapeutically induced anti-tumor responses are mediated mainly by CD8 T cells and directed against tumor-specific antigens (TSAs). The presence of specific TSAs on cancer cells can only be proven by mass spectrometry analyses. Bioinformatic predictions and reverse immunology studies cannot provide this type of conclusive evidence. Most TSAs are coded by unmutated non-canonical transcripts that arise from cancer-specific epigenetic and splicing aberrations. When searching for TSAs, it is therefore important to perform mass spectrometry analyses that interrogate not only the canonical reading frame of annotated exome but all reading frames of the entire translatome. The majority of aberrantly expressed TSAs (aeTSAs) derive from unstable short-lived proteins that are good substrates for direct major histocompatibility complex (MHC) I presentation but poor substrates for cross-presentation. This is an important caveat, because cancer cells are poor antigen-presenting cells, and the immune system, therefore, depends on cross-presentation by dendritic cells (DCs) to detect the presence of TSAs. We, therefore, postulate that, in the untreated host, most aeTSAs are undetected by the immune system. We present evidence suggesting that vaccines inducing direct aeTSA presentation by DCs may represent an attractive strategy for cancer treatment.
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Affiliation(s)
| | | | - Pierre Thibault
- Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada; (A.A.); (M.-P.H.)
| | - Claude Perreault
- Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada; (A.A.); (M.-P.H.)
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