1
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Goodson H, Kawahara R, Chatterjee S, Goncalves G, Fehring J, Purcell AW, Croft NP, Thaysen-Andersen M. Profound N-glycan remodelling accompanies MHC-II immunopeptide presentation. Front Immunol 2023; 14:1258518. [PMID: 38022636 PMCID: PMC10663315 DOI: 10.3389/fimmu.2023.1258518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 10/23/2023] [Indexed: 12/01/2023] Open
Abstract
Immunopeptidomics, the study of peptide antigens presented on the cell surface by the major histocompatibility complex (MHC), offers insights into how our immune system recognises self/non-self in health and disease. We recently discovered that hyper-processed (remodelled) N-glycans are dominant features decorating viral spike immunopeptides presented via MHC-class II (MHC-II) molecules by dendritic cells pulsed with SARS-CoV-2 spike protein, but it remains unknown if endogenous immunopeptides also undergo N-glycan remodelling. Taking a multi-omics approach, we here interrogate published MHC-II immunopeptidomics datasets of cultured monocyte-like (THP-1) and breast cancer-derived (MDA-MB-231) cell lines for overlooked N-glycosylated peptide antigens, which we compare to their source proteins in the cellular glycoproteome using proteomics and N-glycomics data from matching cell lines. Hyper-processed chitobiose core and paucimannosidic N-glycans alongside under-processed oligomannosidic N-glycans were found to prevalently modify MHC-II-bound immunopeptides isolated from both THP-1 and MDA-MB-231, while complex/hybrid-type N-glycans were (near-)absent in the immunopeptidome as supported further by new N-glycomics data generated from isolated MHC-II-bound peptides derived from MDA-MB-231 cells. Contrastingly, the cellular proteomics and N-glycomics data from both cell lines revealed conventional N-glycosylation rich in complex/hybrid-type N-glycans, which, together with the identification of key lysosomal glycosidases, suggest that MHC-II peptide antigen processing is accompanied by extensive N-glycan trimming. N-glycan remodelling appeared particularly dramatic for cell surface-located glycoproteins while less remodelling was observed for lysosomal-resident glycoproteins. Collectively, our findings indicate that both under- and hyper-processed N-glycans are prevalent features of endogenous MHC-II immunopeptides, an observation that demands further investigation to enable a better molecular-level understanding of immune surveillance.
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Affiliation(s)
- Hayley Goodson
- School of Natural Sciences, Macquarie University, Sydney, NSW, Australia
| | - Rebeca Kawahara
- School of Natural Sciences, Macquarie University, Sydney, NSW, Australia
- Institute for Glyco-core Research (iGCORE), Nagoya University, Nagoya, Japan
| | - Sayantani Chatterjee
- School of Natural Sciences, Macquarie University, Sydney, NSW, Australia
- Department of Biochemistry & Cell Biology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Gabriel Goncalves
- Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
| | - Joshua Fehring
- 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
| | - Nathan P. Croft
- Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
| | - Morten Thaysen-Andersen
- School of Natural Sciences, Macquarie University, Sydney, NSW, Australia
- Institute for Glyco-core Research (iGCORE), Nagoya University, Nagoya, Japan
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2
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Kraemer AI, Chong C, Huber F, Pak H, Stevenson BJ, Müller M, Michaux J, Altimiras ER, Rusakiewicz S, Simó-Riudalbas L, Planet E, Wiznerowicz M, Dagher J, Trono D, Coukos G, Tissot S, Bassani-Sternberg M. The immunopeptidome landscape associated with T cell infiltration, inflammation and immune editing in lung cancer. NATURE CANCER 2023; 4:608-628. [PMID: 37127787 DOI: 10.1038/s43018-023-00548-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 03/24/2023] [Indexed: 05/03/2023]
Abstract
One key barrier to improving efficacy of personalized cancer immunotherapies that are dependent on the tumor antigenic landscape remains patient stratification. Although patients with CD3+CD8+ T cell-inflamed tumors typically show better response to immune checkpoint inhibitors, it is still unknown whether the immunopeptidome repertoire presented in highly inflamed and noninflamed tumors is substantially different. We surveyed 61 tumor regions and adjacent nonmalignant lung tissues from 8 patients with lung cancer and performed deep antigen discovery combining immunopeptidomics, genomics, bulk and spatial transcriptomics, and explored the heterogeneous expression and presentation of tumor (neo)antigens. In the present study, we associated diverse immune cell populations with the immunopeptidome and found a relatively higher frequency of predicted neoantigens located within HLA-I presentation hotspots in CD3+CD8+ T cell-excluded tumors. We associated such neoantigens with immune recognition, supporting their involvement in immune editing. This could have implications for the choice of combination therapies tailored to the patient's mutanome and immune microenvironment.
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Affiliation(s)
- Anne I Kraemer
- 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
| | - Chloe Chong
- 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
| | - Florian Huber
- 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
| | - HuiSong Pak
- 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
| | - Brian J Stevenson
- Agora Cancer Research Centre, Lausanne, Switzerland
- SIB Swiss Institute of Bioinformatics, University of Lausanne, Lausanne, Switzerland
| | - Markus Müller
- 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
- SIB Swiss Institute of Bioinformatics, University of Lausanne, Lausanne, Switzerland
| | - Justine Michaux
- 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
| | - Emma Ricart Altimiras
- 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
| | - Sylvie Rusakiewicz
- Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland
- Department of Oncology, Centre hospitalier universitaire vaudois, Lausanne, Switzerland
- Center of Experimental Therapeutics, Department of Oncology, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Laia Simó-Riudalbas
- École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Evarist Planet
- École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Maciej Wiznerowicz
- International Institute for Molecular Oncology, Poznań, Poland
- Poznań University of Medical Sciences, Poznań, Poland
| | - Julien Dagher
- Department of Pathology, Centre hospitalier universitaire vaudois, Lausanne, Switzerland
| | - Didier Trono
- École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - George Coukos
- 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
- Center of Experimental Therapeutics, Department of Oncology, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Stephanie Tissot
- Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland
- Department of Oncology, Centre hospitalier universitaire vaudois, Lausanne, Switzerland
- SIB Swiss Institute of Bioinformatics, University of Lausanne, Lausanne, Switzerland
| | - 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.
- Center of Experimental Therapeutics, Department of Oncology, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland.
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3
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Racle J, Guillaume P, Schmidt J, Michaux J, Larabi A, Lau K, Perez MAS, Croce G, Genolet R, Coukos G, Zoete V, Pojer F, Bassani-Sternberg M, Harari A, Gfeller D. Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes. Immunity 2023:S1074-7613(23)00129-2. [PMID: 37023751 DOI: 10.1016/j.immuni.2023.03.009] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 11/09/2022] [Accepted: 03/15/2023] [Indexed: 04/08/2023]
Abstract
CD4+ T cells orchestrate the adaptive immune response against pathogens and cancer by recognizing epitopes presented on class II major histocompatibility complex (MHC-II) molecules. The high polymorphism of MHC-II genes represents an important hurdle toward accurate prediction and identification of CD4+ T cell epitopes. Here we collected and curated a dataset of 627,013 unique MHC-II ligands identified by mass spectrometry. This enabled us to precisely determine the binding motifs of 88 MHC-II alleles across humans, mice, cattle, and chickens. Analysis of these binding specificities combined with X-ray crystallography refined our understanding of the molecular determinants of MHC-II motifs and revealed a widespread reverse-binding mode in HLA-DP ligands. We then developed a machine-learning framework to accurately predict binding specificities and ligands of any MHC-II allele. This tool improves and expands predictions of CD4+ T cell epitopes and enables us to discover viral and bacterial epitopes following the aforementioned reverse-binding mode.
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Affiliation(s)
- Julien Racle
- Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland; Agora Cancer Research Centre, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland.
| | - Philippe Guillaume
- Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland; Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University Hospital of Lausanne, Lausanne, Switzerland
| | - Julien Schmidt
- Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland; Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University Hospital of Lausanne, Lausanne, Switzerland
| | - Justine Michaux
- Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland; Agora Cancer Research Centre, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland; Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University Hospital of Lausanne, Lausanne, Switzerland; Center of Experimental Therapeutics, Department of Oncology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Amédé Larabi
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Kelvin Lau
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Marta A S Perez
- Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland
| | - Giancarlo Croce
- Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland; Agora Cancer Research Centre, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland
| | - Raphaël Genolet
- Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland; Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University Hospital of Lausanne, Lausanne, Switzerland
| | - George Coukos
- Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland; Agora Cancer Research Centre, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland; Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University Hospital of Lausanne, Lausanne, Switzerland
| | - Vincent Zoete
- Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland
| | - Florence Pojer
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Michal Bassani-Sternberg
- Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland; Agora Cancer Research Centre, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland; Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University Hospital of Lausanne, Lausanne, Switzerland; Center of Experimental Therapeutics, Department of Oncology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Alexandre Harari
- Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland; Agora Cancer Research Centre, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland; Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University Hospital of Lausanne, Lausanne, Switzerland
| | - David Gfeller
- Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland; Agora Cancer Research Centre, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland.
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4
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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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5
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Nelde A, Maringer Y, Bilich T, Salih HR, Roerden M, Heitmann JS, Marcu A, Bauer J, Neidert MC, Denzlinger C, Illerhaus G, Aulitzky WE, Rammensee HG, Walz JS. Immunopeptidomics-Guided Warehouse Design for Peptide-Based Immunotherapy in Chronic Lymphocytic Leukemia. Front Immunol 2021; 12:705974. [PMID: 34305947 PMCID: PMC8297687 DOI: 10.3389/fimmu.2021.705974] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 06/24/2021] [Indexed: 12/30/2022] Open
Abstract
Antigen-specific immunotherapies, in particular peptide vaccines, depend on the recognition of naturally presented antigens derived from mutated and unmutated gene products on human leukocyte antigens, and represent a promising low-side-effect concept for cancer treatment. So far, the broad application of peptide vaccines in cancer patients is hampered by challenges of time- and cost-intensive personalized vaccine design, and the lack of neoepitopes from tumor-specific mutations, especially in low-mutational burden malignancies. In this study, we developed an immunopeptidome-guided workflow for the design of tumor-associated off-the-shelf peptide warehouses for broadly applicable personalized therapeutics. Comparative mass spectrometry-based immunopeptidome analyses of primary chronic lymphocytic leukemia (CLL) samples, as representative example of low-mutational burden tumor entities, and a dataset of benign tissue samples enabled the identification of high-frequent non-mutated CLL-associated antigens. These antigens were further shown to be recognized by pre-existing and de novo induced T cells in CLL patients and healthy volunteers, and were evaluated as pre-manufactured warehouse for the construction of personalized multi-peptide vaccines in a first clinical trial for CLL (NCT04688385). This workflow for the design of peptide warehouses is easily transferable to other tumor entities and can provide the foundation for the development of broad personalized T cell-based immunotherapy approaches.
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Affiliation(s)
- Annika Nelde
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany.,Department of Immunology, Institute for Cell Biology, University of Tübingen, Tübingen, Germany.,Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Yacine Maringer
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany.,Department of Immunology, Institute for Cell Biology, University of Tübingen, Tübingen, Germany.,Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Tatjana Bilich
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany.,Department of Immunology, Institute for Cell Biology, University of Tübingen, Tübingen, Germany.,Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Helmut R Salih
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany.,Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Malte Roerden
- Department of Immunology, Institute for Cell Biology, University of Tübingen, Tübingen, Germany.,Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany.,Department of Hematology, Oncology, Clinical Immunology and Rheumatology, University Hospital Tübingen, Tübingen, Germany
| | - Jonas S Heitmann
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany.,Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Ana Marcu
- Department of Immunology, Institute for Cell Biology, University of Tübingen, Tübingen, Germany
| | - Jens Bauer
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany.,Department of Immunology, Institute for Cell Biology, University of Tübingen, Tübingen, Germany
| | - Marian C Neidert
- Department of Neurosurgery, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | | | - Gerald Illerhaus
- Clinic for Hematology and Oncology, Klinikum Stuttgart, Stuttgart, Germany
| | - Walter Erich Aulitzky
- Department of Hematology, Oncology and Palliative Medicine, Robert-Bosch-Krankenhaus Stuttgart, Stuttgart, Germany
| | - Hans-Georg Rammensee
- Department of Immunology, Institute for Cell Biology, 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
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany.,Department of Immunology, Institute for Cell Biology, University of Tübingen, Tübingen, Germany.,Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany.,Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology and Robert Bosch Center for Tumor Diseases (RBCT), Stuttgart, Germany
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6
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Pearlman AH, Hwang MS, Konig MF, Hsiue EHC, Douglass J, DiNapoli SR, Mog BJ, Bettegowda C, Pardoll DM, Gabelli SB, Papadopoulos N, Kinzler KW, Vogelstein B, Zhou S. Targeting public neoantigens for cancer immunotherapy. NATURE CANCER 2021; 2:487-497. [PMID: 34676374 PMCID: PMC8525885 DOI: 10.1038/s43018-021-00210-y] [Citation(s) in RCA: 76] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Accepted: 04/13/2021] [Indexed: 02/06/2023]
Abstract
Several current immunotherapy approaches target private neoantigens derived from mutations that are unique to individual patients' tumors. However, immunotherapeutic agents can also be developed against public neoantigens derived from recurrent mutations in cancer driver genes. The latter approaches target proteins that are indispensable for tumor growth, and each therapeutic agent can be applied to numerous patients. Here we review the opportunities and challenges involved in the identification of suitable public neoantigen targets and the development of therapeutic agents targeting them.
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Affiliation(s)
- Alexander H Pearlman
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Michael S Hwang
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Genentech, Inc., South San Francisco, CA, USA
| | - Maximilian F Konig
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Division of Rheumatology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Emily Han-Chung Hsiue
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Jacqueline Douglass
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Sarah R DiNapoli
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Brian J Mog
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Chetan Bettegowda
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurosurgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Drew M Pardoll
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Bloomberg~Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA
| | - Sandra B Gabelli
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biophysics and Biophysical Chemistry, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nicholas Papadopoulos
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Bloomberg~Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kenneth W Kinzler
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Bloomberg~Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA
- Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Bert Vogelstein
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Bloomberg~Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Shibin Zhou
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Bloomberg~Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA.
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7
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Demmers LC, Wu W, Heck AJR. HLA Class II Presentation Is Specifically Altered at Elevated Temperatures in the B-Lymphoblastic Cell Line JY. Mol Cell Proteomics 2021; 20:100089. [PMID: 33933681 PMCID: PMC8724904 DOI: 10.1016/j.mcpro.2021.100089] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Revised: 03/25/2021] [Accepted: 04/13/2021] [Indexed: 12/22/2022] Open
Abstract
Human leukocyte antigen (HLA) molecules play critical roles in our adaptive immune system by signaling a cell's health status to the immune system, through presentation of small peptides. Understanding HLA biology is important because of its prominent role in autoimmune diseases and cancer immunotherapy. Although both the HLA class I and class II antigen processing and presentation pathways have been studied extensively, the fundamental rules in HLA class II antigen presentation still remain less understood. To clarify the mechanistic and adaptive differences between the HLA systems, we challenged a B lymphoblastic cell line (JY), widely used as model system in studying antigen presentation, with a high temperature treatment to mimic a "fever-like state", representing one of the most common physiological responses to infection. In the absence of real invading pathogenic peptides to present, we could focus on delineating the intrinsic HLA pathway adaptations in response to high temperature in this particular cell line. Following a three-pronged approach, we performed quantitative analyses of the proteome, the HLA class I ligandome, as well as the HLA class II ligandome. The data reveals that elevated temperature may already prepare these cells for an immune-like response through increased HLA class II presentation capacity and specific release of, from the invariant chain originating, CLIP peptides. Interestingly, at high temperature, prominent changes in the composition of the CLIP repertoire were observed, with enrichment of peptides containing C-terminal extensions beyond the CLIP-core region. Collectively, these illustrate intriguing temperature sensitive adaptations in this B cell line.
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Affiliation(s)
- Laura C Demmers
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands; Netherlands Proteomics Centre, Utrecht, Netherlands
| | - Wei Wu
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands; Netherlands Proteomics Centre, Utrecht, Netherlands
| | - Albert J R Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands; Netherlands Proteomics Centre, Utrecht, Netherlands.
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