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Boeren M, de Vrij N, Ha MK, Valkiers S, Souquette A, Gielis S, Kuznetsova M, Schippers J, Bartholomeus E, Van den Bergh J, Michels N, Aerts O, Leysen J, Bervoets A, Lambert J, Leuridan E, Wens J, Peeters K, Emonds MP, Elias G, Vandamme N, Jansens H, Adriaensen W, Suls A, Vanhee S, Hens N, Smits E, Van Damme P, Thomas PG, Beutels P, Ponsaerts P, Van Tendeloo V, Delputte P, Laukens K, Meysman P, Ogunjimi B. Lack of functional TCR-epitope interaction is associated with herpes zoster through reduced downstream T cell activation. Cell Rep 2024; 43:114062. [PMID: 38588339 DOI: 10.1016/j.celrep.2024.114062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 02/23/2024] [Accepted: 03/21/2024] [Indexed: 04/10/2024] Open
Abstract
The role of T cell receptor (TCR) diversity in infectious disease susceptibility is not well understood. We use a systems immunology approach on three cohorts of herpes zoster (HZ) patients and controls to investigate whether TCR diversity against varicella-zoster virus (VZV) influences the risk of HZ. We show that CD4+ T cell TCR diversity against VZV glycoprotein E (gE) and immediate early 63 protein (IE63) after 1-week culture is more restricted in HZ patients. Single-cell RNA and TCR sequencing of VZV-specific T cells shows that T cell activation pathways are significantly decreased after stimulation with VZV peptides in convalescent HZ patients. TCR clustering indicates that TCRs from HZ patients co-cluster more often together than TCRs from controls. Collectively, our results suggest that not only lower VZV-specific TCR diversity but also reduced functional TCR affinity for VZV-specific proteins in HZ patients leads to lower T cell activation and consequently affects the susceptibility for viral reactivation.
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Affiliation(s)
- Marlies Boeren
- Laboratory of Microbiology, Parasitology and Hygiene (LMPH), University of Antwerp, Antwerp, Belgium; Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium; Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Nicky de Vrij
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium; Clinical Immunology Unit, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - My K Ha
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Sebastiaan Valkiers
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Aisha Souquette
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Sofie Gielis
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Maria Kuznetsova
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Jolien Schippers
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Esther Bartholomeus
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Johan Van den Bergh
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Nele Michels
- Department of Family Medicine and Population Health (FAMPOP), Center for General Practice/Family Medicine, University of Antwerp, Antwerp, Belgium
| | - Olivier Aerts
- Department of Dermatology, Antwerp University Hospital and University of Antwerp, Antwerp, Belgium
| | - Julie Leysen
- Department of Dermatology, Antwerp University Hospital and University of Antwerp, Antwerp, Belgium
| | - An Bervoets
- Department of Dermatology, Antwerp University Hospital and University of Antwerp, Antwerp, Belgium
| | - Julien Lambert
- Department of Dermatology, Antwerp University Hospital and University of Antwerp, Antwerp, Belgium
| | - Elke Leuridan
- Centre for the Evaluation of Vaccination (CEV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Johan Wens
- Department of Family Medicine and Population Health (FAMPOP), Center for General Practice/Family Medicine, University of Antwerp, Antwerp, Belgium
| | - Karin Peeters
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Marie-Paule Emonds
- Histocompatibility and Immunogenetic Laboratory, Rode Kruis-Vlaanderen, Mechelen, Belgium
| | - George Elias
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium; Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Niels Vandamme
- Data Mining and Modeling for Biomedicine Group, VIB-UGent Center for Inflammation Research, 9052 Ghent, Belgium; Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
| | - Hilde Jansens
- Department of Clinical Microbiology, Antwerp University Hospital, Antwerp, Belgium
| | - Wim Adriaensen
- Clinical Immunology Unit, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Arvid Suls
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Medical Genetics, University of Antwerp and Antwerp University Hospital, Antwerp, Belgium
| | - Stijn Vanhee
- Laboratory of Immunoregulation and Mucosal Immunology, VIB Center for Inflammation Research, Ghent, Belgium; Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium; Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Niel Hens
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Evelien Smits
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
| | - Pierre Van Damme
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for the Evaluation of Vaccination (CEV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Paul G Thomas
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Philippe Beutels
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Peter Ponsaerts
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Viggo Van Tendeloo
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
| | - Peter Delputte
- Laboratory of Microbiology, Parasitology and Hygiene (LMPH), University of Antwerp, Antwerp, Belgium
| | - Kris Laukens
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Pieter Meysman
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Benson Ogunjimi
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Department of Paediatrics, Antwerp University Hospital, Antwerp, Belgium.
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2
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Vujkovic A, Ha M, de Block T, van Petersen L, Brosius I, Theunissen C, van Ierssel SH, Bartholomeus E, Adriaensen W, Vanham G, Elias G, Van Damme P, Van Tendeloo V, Beutels P, van Frankenhuijsen M, Vlieghe E, Ogunjimi B, Laukens K, Meysman P, Vercauteren K. Diagnosing Viral Infections Through T-Cell Receptor Sequencing of Activated CD8+ T Cells. J Infect Dis 2024; 229:507-516. [PMID: 37787611 PMCID: PMC10873181 DOI: 10.1093/infdis/jiad430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 08/26/2023] [Accepted: 09/29/2023] [Indexed: 10/04/2023] Open
Abstract
T-cell-based diagnostic tools identify pathogen exposure but lack differentiation between recent and historical exposures in acute infectious diseases. Here, T-cell receptor (TCR) RNA sequencing was performed on HLA-DR+/CD38+CD8+ T-cell subsets of hospitalized coronavirus disease 2019 (COVID-19) patients (n = 30) and healthy controls (n = 30; 10 of whom had previously been exposed to severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]). CDR3α and CDR3β TCR regions were clustered separately before epitope specificity annotation using a database of SARS-CoV-2-associated CDR3α and CDR3β sequences corresponding to >1000 SARS-CoV-2 epitopes. The depth of the SARS-CoV-2-associated CDR3α/β sequences differentiated COVID-19 patients from the healthy controls with a receiver operating characteristic area under the curve of 0.84 ± 0.10. Hence, annotating TCR sequences of activated CD8+ T cells can be used to diagnose an acute viral infection and discriminate it from historical exposure. In essence, this work presents a new paradigm for applying the T-cell repertoire to accomplish TCR-based diagnostics.
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Affiliation(s)
- Alexandra Vujkovic
- Clinical Virology Unit, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium
- Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium
| | - My Ha
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium
- Antwerp Center for Translational Immunology and Virology (ACTIV), Antwerp, Belgium
- Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), University of Antwerp, Belgium
- Vaccine and Infectious Disease Institute, University of Antwerp, Belgium
| | - Tessa de Block
- Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Lida van Petersen
- Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Isabel Brosius
- Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Caroline Theunissen
- Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Sabrina H van Ierssel
- Department of General Internal Medicine, Infectious Diseases and Tropical Medicine, University Hospital Antwerp, Belgium
| | - Esther Bartholomeus
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium
- Antwerp Center for Translational Immunology and Virology (ACTIV), Antwerp, Belgium
| | - Wim Adriaensen
- Clinical Immunology Unit, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Guido Vanham
- Biomedical Department, Institute of Tropical Medicine, Antwerp, Belgium
| | - George Elias
- Laboratory of Experimental Hematology, Faculty of Medicine and Health Sciences, University of Antwerp, Belgium
| | - Pierre Van Damme
- Vaccine and Infectious Disease Institute, University of Antwerp, Belgium
| | - Viggo Van Tendeloo
- Laboratory of Experimental Hematology, Faculty of Medicine and Health Sciences, University of Antwerp, Belgium
| | - Philippe Beutels
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium
- Antwerp Center for Translational Immunology and Virology (ACTIV), Antwerp, Belgium
- Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), University of Antwerp, Belgium
| | | | - Erika Vlieghe
- Department of General Internal Medicine, Infectious Diseases and Tropical Medicine, University Hospital Antwerp, Belgium
| | - Benson Ogunjimi
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium
- Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium
- Antwerp Center for Translational Immunology and Virology (ACTIV), Antwerp, Belgium
- Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), University of Antwerp, Belgium
- Vaccine and Infectious Disease Institute, University of Antwerp, Belgium
- Department of Paediatrics, Antwerp University Hospital, Antwerp, Belgium
| | - Kris Laukens
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium
- Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium
| | - Pieter Meysman
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium
- Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium
| | - Koen Vercauteren
- Clinical Virology Unit, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
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Vandoren R, Boeren M, Schippers J, Bartholomeus E, Mullan K, Michels N, Aerts O, Leysen J, Bervoets A, Lambert J, Leuridan E, Wens J, Peeters K, Emonds MP, Jansens H, Casanova JL, Bastard P, Suls A, Van Tendeloo V, Ponsaerts P, Delputte P, Ogunjimi B, Laukens K, Meysman P. Unravelling the immune signature of herpes zoster: Insights into pathophysiology and the HLA risk profile. J Infect Dis 2024:jiad609. [PMID: 38195164 DOI: 10.1093/infdis/jiad609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 12/15/2023] [Accepted: 12/27/2023] [Indexed: 01/11/2024] Open
Abstract
The varicella-zoster virus (VZV) infects over 95% of the population. VZV reactivation causes herpes zoster (HZ), known as shingles, primarily affecting the elderly and immunocompromised individuals. However, HZ can also occur in otherwise healthy individuals. We analyzed the immune signature and risk profile in HZ patients using a genome-wide association study across different UK Biobank HZ cohorts. Additionally, we conducted one of the largest HZ HLA association studies to date, coupled with transcriptomic analysis of pathways underlying HZ susceptibility. Our findings highlight the significance of the MHC locus for HZ development, identifying five protective and four risk HLA alleles. This demonstrates that HZ susceptibility is largely governed by variations in the MHC. Furthermore, functional analyses revealed the upregulation of type I interferon and adaptive immune responses. These findings provide fresh molecular insights into the pathophysiology and the activation of innate and adaptive immune responses triggered by symptomatic VZV reactivation.
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Affiliation(s)
- Romi Vandoren
- Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
- Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Marlies Boeren
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
- Laboratory of Microbiology, Parasitology and Hygiene (LMPH) & Infla-Med Center of Excellence, University of Antwerp, Antwerp, Belgium
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
- Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Jolien Schippers
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
- Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Esther Bartholomeus
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
- Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Kerry Mullan
- Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
- Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Nele Michels
- Department of Family Medicine and Population Health (FAMPOP), Center for general practice/family Medicine, University of Antwerp, Antwerp, Belgium
| | - Olivier Aerts
- Department of Dermatology, Antwerp University Hospital & University of Antwerp, Antwerp, Belgium
| | - Julie Leysen
- Department of Dermatology, Antwerp University Hospital & University of Antwerp, Antwerp, Belgium
| | - An Bervoets
- Department of Dermatology, Antwerp University Hospital & University of Antwerp, Antwerp, Belgium
| | - Julien Lambert
- Department of Dermatology, Antwerp University Hospital & University of Antwerp, Antwerp, Belgium
| | - Elke Leuridan
- Centre for the Evaluation of Vaccination (CEV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Johan Wens
- Department of Family Medicine and Population Health (FAMPOP), Center for general practice/family Medicine, University of Antwerp, Antwerp, Belgium
| | - Karin Peeters
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
- Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Marie-Paule Emonds
- Histocompatibility and Immunogenetic Laboratory, Rode Kruis-Vlaanderen, Mechelen, Belgium
| | - Hilde Jansens
- Department of Clinical Microbiology, Antwerp University Hospital, Antwerp, Belgium
| | - Jean-Laurent Casanova
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, Institut National de la Santé et de la Recherche Médicale (INSERM) U1163, Necker Hospital for Sick Children, Paris, France
- Paris Cité University, Imagine Institute, Paris, France
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
- Howard Hughes Medical Institute, New York, NY, USA
- Department of Pediatrics, Necker Hospital for Sick Children, Paris, France
| | - Paul Bastard
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, Institut National de la Santé et de la Recherche Médicale (INSERM) U1163, Necker Hospital for Sick Children, Paris, France
- Paris Cité University, Imagine Institute, Paris, France
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
- Pediatric Hematology-Immunology and Rheumatology Unit, Necker Hospital for Sick Children, Assistante Publique-Hôpitaux de Paris, Paris, France
| | - Arvid Suls
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
- Medical Genetics, University of Antwerp and Antwerp University Hospital, Antwerp, Belgium
| | - Viggo Van Tendeloo
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Peter Ponsaerts
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Peter Delputte
- Laboratory of Microbiology, Parasitology and Hygiene (LMPH) & Infla-Med Center of Excellence, University of Antwerp, Antwerp, Belgium
| | - Benson Ogunjimi
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
- Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
- Department of Paediatrics, Antwerp University Hospital, Antwerp, Belgium
| | - Kris Laukens
- Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
- Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Pieter Meysman
- Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
- Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
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Souquette A, Allen EK, Oshansky CM, Tang L, Wong SS, Jeevan T, Shi L, Pounds S, Elias G, Kuan G, Balmaseda A, Zapata R, Shaw-Saliba K, Damme PV, Tendeloo VV, Dib JC, Ogunjimi B, Webby R, Schultz-Cherry S, Pekosz A, Rothman R, Gordon A, Thomas PG. Integrated Drivers of Basal and Acute Immunity in Diverse Human Populations. bioRxiv 2023:2023.03.25.534227. [PMID: 36993205 PMCID: PMC10055315 DOI: 10.1101/2023.03.25.534227] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Prior studies have identified genetic, infectious, and biological associations with immune competence and disease severity; however, there have been few integrative analyses of these factors and study populations are often limited in demographic diversity. Utilizing samples from 1,705 individuals in 5 countries, we examined putative determinants of immunity, including: single nucleotide polymorphisms, ancestry informative markers, herpesvirus status, age, and sex. In healthy subjects, we found significant differences in cytokine levels, leukocyte phenotypes, and gene expression. Transcriptional responses also varied by cohort, and the most significant determinant was ancestry. In influenza infected subjects, we found two disease severity immunophenotypes, largely driven by age. Additionally, cytokine regression models show each determinant differentially contributes to acute immune variation, with unique and interactive, location-specific herpesvirus effects. These results provide novel insight into the scope of immune heterogeneity across diverse populations, the integrative effects of factors which drive it, and the consequences for illness outcomes.
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van der Heijden S, Flumens D, Versteven M, Peeters S, Reu HD, Campillo-Davo D, Willemen Y, Ogunjimi B, Van Tendeloo V, Berneman ZN, Anguille S, Smits E, Lion E. In vitro expansion of Wilms' tumor protein 1 epitope-specific primary T cells from healthy human peripheral blood mononuclear cells. STAR Protoc 2023; 4:102053. [PMID: 36853720 PMCID: PMC9918782 DOI: 10.1016/j.xpro.2023.102053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 11/25/2022] [Accepted: 01/03/2023] [Indexed: 01/31/2023] Open
Abstract
Wilms' tumor protein 1 (WT1) is a tumor-associated antigen overexpressed in various cancers. As a self-antigen, negative selection reduces the number of WT1-specific T cell receptors (TCRs). Here, we provide a protocol to generate WT137-45-specific TCRs using healthy human peripheral blood mononuclear cells. We describe the expansion of WT1-specific T cell clones by two consecutive in vitro stimulations with autologous WT137-45-pulsed dendritic cells and peripheral blood lymphocytes. We then detail the detection with human leukocyte antigen/WT137-45 tetramers.
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Affiliation(s)
- Sanne van der Heijden
- Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium; Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Donovan Flumens
- Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium.
| | - Maarten Versteven
- Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Stefanie Peeters
- Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Hans De Reu
- Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Diana Campillo-Davo
- Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Yannick Willemen
- Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Benson Ogunjimi
- Centre for Health Economics Research & Modeling Infectious Diseases (CHERMID), VAXINFECTIO, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Viggo Van Tendeloo
- Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Zwi N Berneman
- Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Sébastien Anguille
- Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium; Division of Hematology, Antwerp University Hospital (UZA), Drie Eikenstraat 655, 2650 Edegem, Belgium
| | - Evelien Smits
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Eva Lion
- Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium.
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6
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Versteven M, Flumens D, Campillo-Davó D, De Reu H, Van Bruggen L, Peeters S, Van Tendeloo V, Berneman Z, Dolstra H, Anguille S, Hobo W, Smits E, Lion E. Anti-Tumor Potency of Short-Term Interleukin-15 Dendritic Cells Is Potentiated by In Situ Silencing of Programmed-Death Ligands. Front Immunol 2022; 13:734256. [PMID: 35250967 PMCID: PMC8891487 DOI: 10.3389/fimmu.2022.734256] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 01/27/2022] [Indexed: 11/24/2022] Open
Abstract
Dendritic cell (DC) vaccines have proven to be a valuable tool in cancer immune therapy. With several DC vaccines being currently tested in clinical trials, knowledge about their therapeutic value has been significantly increased in the past decade. Despite their established safety, it has become clear that objective clinical responses are not yet robust enough, requiring further optimization. Improvements of this advanced therapy medicinal product encompass, among others, regulating their immune stimulating capacity by in situ gene engineering, in addition to their implementation in combination therapy regimens. Previously, we have reported on a superior monocyte-derived DC preparation, including interleukin-15, pro-inflammatory cytokines and immunological danger signals in the culture process. These so-called IL-15 DCs have already proven to exhibit several favorable properties as cancer vaccine. Evolving research into mechanisms that could further modulate the immune response towards cancer, points to programmed death-1 as an important player that dampens anti-tumor immunity. Aiming at leveraging the immunogenicity of DC vaccines, we hypothesized that additional implementation of the inhibitory immune checkpoint molecules programmed death-ligand (PD-L)1 and PD-L2 in IL-15 DC vaccines would exhibit superior stimulatory potential. In this paper, we successfully implemented PD-L silencing at the monocyte stage in the 3-day IL-15 DC culture protocol resulting in substantial downregulation of both PD-L1 and PD-L2 to levels below 30%. Additionally, we validated that these DCs retain their specific characteristics, both at the level of phenotype and interferon gamma secretion. Evaluating their functional characteristics, we demonstrate that PD-L silencing does not affect the capacity to induce allogeneic proliferation. Ultimately designed to induce a durable tumor antigen-specific immune response, PD-L silenced IL-15 DCs were capable of surpassing PD-1-mediated inhibition by antigen-specific T cells. Further corroborating the superior potency of short-term IL-15 DCs, the combination of immune stimulatory components during DC differentiation and maturation with in situ checkpoint inhibition supports further clinical translation.
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Affiliation(s)
- Maarten Versteven
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Donovan Flumens
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Diana Campillo-Davó
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Hans De Reu
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Laura Van Bruggen
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Stefanie Peeters
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Viggo Van Tendeloo
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Zwi Berneman
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
- Division of Hematology, Antwerp University Hospital, Edegem, Belgium
- Center for Cell Therapy and Regenerative Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Harry Dolstra
- Department of Laboratory Medicine – Laboratory of Hematology, Radboud University Medical Center, Nijmegen, Netherlands
| | - Sébastien Anguille
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
- Division of Hematology, Antwerp University Hospital, Edegem, Belgium
- Center for Cell Therapy and Regenerative Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Willemijn Hobo
- Department of Laboratory Medicine – Laboratory of Hematology, Radboud University Medical Center, Nijmegen, Netherlands
| | - Evelien Smits
- Center for Cell Therapy and Regenerative Medicine, Antwerp University Hospital, Edegem, Belgium
- Center for Oncological Research (CORE), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Eva Lion
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
- Center for Cell Therapy and Regenerative Medicine, Antwerp University Hospital, Edegem, Belgium
- *Correspondence: Eva Lion,
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7
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Elias G, Meysman P, Bartholomeus E, De Neuter N, Keersmaekers N, Suls A, Jansens H, Souquette A, De Reu H, Emonds MP, Smits E, Lion E, Thomas PG, Mortier G, Van Damme P, Beutels P, Laukens K, Van Tendeloo V, Ogunjimi B. Preexisting memory CD4 T cells in naïve individuals confer robust immunity upon hepatitis B vaccination. eLife 2022; 11:68388. [PMID: 35074048 PMCID: PMC8824481 DOI: 10.7554/elife.68388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Accepted: 01/07/2022] [Indexed: 11/22/2022] Open
Abstract
Antigen recognition through the T cell receptor (TCR) αβ heterodimer is one of the primary determinants of the adaptive immune response. Vaccines activate naïve T cells with high specificity to expand and differentiate into memory T cells. However, antigen-specific memory CD4 T cells exist in unexposed antigen-naïve hosts. In this study, we use high-throughput sequencing of memory CD4 TCRβ repertoire and machine learning to show that individuals with preexisting vaccine-reactive memory CD4 T cell clonotypes elicited earlier and higher antibody titers and mounted a more robust CD4 T cell response to hepatitis B vaccine. In addition, integration of TCRβ sequence patterns into a hepatitis B epitope-specific annotation model can predict which individuals will have an early and more vigorous vaccine-elicited immunity. Thus, the presence of preexisting memory T cell clonotypes has a significant impact on immunity and can be used to predict immune responses to vaccination. Immune cells called CD4 T cells help the body build immunity to infections caused by bacteria and viruses, or after vaccination. Receptor proteins on the outside of the cells recognize pathogens, foreign molecules called antigens, or vaccine antigens. Vaccine antigens are usually inactivated bacteria or viruses, or fragments of these pathogens. After recognizing an antigen, CD4 T cells develop into memory CD4 T cells ready to defend against future infections with the pathogen. People who have never been exposed to a pathogen, or have never been vaccinated against it, may nevertheless have preexisting memory cells ready to defend against it. This happens because CD4 T cells can recognize multiple targets, which enables the immune system to be ready to defend against both new and familiar pathogens. Elias, Meysman, Bartholomeus et al. wanted to find out whether having preexisting memory CD4 T cells confers an advantage for vaccine-induced immunity. Thirty-four people who were never exposed to hepatitis B or vaccinated against it participated in the study. These individuals provided blood samples before vaccination, with 2 doses of the hepatitis B vaccine, and at 3 time points afterward. Using next generation immune sequencing and machine learning techniques, Elias et al. analyzed the individuals’ memory CD4 T cells before and after vaccination. The experiments showed that preexisting memory CD4 T cells may determine vaccination outcomes, and people with more preexisting memory cells develop quicker and stronger immunity after vaccination against hepatitis B. This information may help scientists to better understand how people develop immunity to pathogens. It may guide them develop better vaccines or predict who will develop immunity after vaccination.
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Affiliation(s)
- George Elias
- Laboratory of Experimental Hematology (LEH), University of Antwerp
| | - Pieter Meysman
- Biomedical Informatics Research Network Antwerp, Department of Mathematics and Informatics, University of Antwerp
| | | | - Nicolas De Neuter
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
| | - Nina Keersmaekers
- Centre for Health Economics Research & Modeling Infectious Diseases, University of Antwerp
| | - Arvid Suls
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
| | - Hilde Jansens
- Department of Clinical Microbiology, Antwerp University Hospital
| | - Aisha Souquette
- Department of Immunology, St. Jude Children's Research Hospital
| | - Hans De Reu
- Laboratory of Experimental Hematology, University of Antwerp
| | | | - Evelien Smits
- Laboratory of Experimental Hematology, University of Antwerp
| | - Eva Lion
- Laboratory of Experimental Hematology, University of Antwerp
| | - Paul G Thomas
- Department of Immunology, St. Jude Children's Research Hospital
| | - Geert Mortier
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
| | - Pierre Van Damme
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
| | - Philippe Beutels
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
| | - Kris Laukens
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
| | - Viggo Van Tendeloo
- Janssen Research and Development, Immunosciences WWDA, Johnson and Johnson
| | - Benson Ogunjimi
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
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8
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Jordaens S, Cooksey L, Freire Boullosa L, Van Tendeloo V, Smits E, Mills KI, Orchard KH, Guinn BA. New targets for therapy: antigen identification in adults with B-cell acute lymphoblastic leukaemia. Cancer Immunol Immunother 2020; 69:867-877. [PMID: 31970440 PMCID: PMC7183504 DOI: 10.1007/s00262-020-02484-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Accepted: 01/04/2020] [Indexed: 12/11/2022]
Abstract
Acute lymphoblastic leukaemia (ALL) in adults is a rare and difficult-to-treat cancer that is characterised by excess lymphoblasts in the bone marrow. Although many patients achieve remission with chemotherapy, relapse rates are high and the associated impact on survival devastating. Most patients receive chemotherapy and for those whose overall fitness supports it, the most effective treatment to date is allogeneic stem cell transplant that can improve overall survival rates in part due to a 'graft-versus-leukaemia' effect. However, due to the rarity of this disease, and the availability of mature B-cell antigens on the cell surface, few new cancer antigens have been identified in adult B-ALL that could act as targets to remove residual disease in first remission or provide alternative targets for escape variants if and when current immunotherapy strategies fail. We have used RT-PCR analysis, literature searches, antibody-specific profiling and gene expression microarray analysis to identify and prioritise antigens as novel targets for the treatment of adult B-ALL.
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Affiliation(s)
- Stephanie Jordaens
- Department of Biomedical Sciences, University of Hull, Cottingham Road, Hardy Building, Room 111, Hull, HU7 6RX, UK
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Leah Cooksey
- Department of Biomedical Sciences, University of Hull, Cottingham Road, Hardy Building, Room 111, Hull, HU7 6RX, UK
| | | | - Viggo Van Tendeloo
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Evelien Smits
- Centre for Oncological Research, University of Antwerp, Antwerp, Belgium
| | - Ken I Mills
- Centre for Cancer Research and Cell Biology, Queens University Belfast, Lisburn Road, Belfast, UK
| | - Kim H Orchard
- Department of Haematology, University Hospital Southampton NHS Foundation Trust and University of Southampton, Southampton, UK
| | - Barbara-Ann Guinn
- Department of Biomedical Sciences, University of Hull, Cottingham Road, Hardy Building, Room 111, Hull, HU7 6RX, UK.
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9
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Bartholomeus E, De Neuter N, Suls A, Elias G, van der Heijden S, Keersmaekers N, Jansens H, Van Tendeloo V, Beutels P, Laukens K, Ogunjimi B, Mortier G, Meysman P, Van Damme P. Transcriptomic profiling of different responder types in adults after a Priorix® vaccination. Vaccine 2020; 38:3218-3226. [PMID: 32165045 DOI: 10.1016/j.vaccine.2020.03.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Revised: 02/24/2020] [Accepted: 03/01/2020] [Indexed: 12/12/2022]
Abstract
Thanks to the recommendation of a combined Measles/Mumps/Rubella (MMR) vaccine, like Priorix®, these childhood diseases are less common now. This is beneficial to limit the spread of these diseases and work towards their elimination. However, the measles, mumps and rubella antibody titers show a large variability in short- and long-term immunity. The recent outbreaks worldwide of measles and mumps and previous studies, which mostly focused on only one of the three virus responses, illustrate that there is a clear need for better understanding the immune responses after vaccination. Our healthy cohort was already primed with the MMR antigens in their childhood. In this study, the adult volunteers received one Priorix® vaccine dose at day 0. First, we defined 4 different groups of responders, based on their antibody titers' evolution over 4 time points (Day 0, 21, 150 and 365). This showed a high variability within and between individuals. Second, we determined transcriptome profiles using 3'mRNA sequencing at day 0, 3 and 7. Using two analytical approaches, "one response group per time point" and "a time comparison per response group", we correlated the short-term gene expression profiles to the different response groups. In general, the list of differentially expressed genes is limited, however, most of them are clearly immune-related and upregulated at day 3 and 7, compared to the baseline day 0. Depending on the specific response group there are overlapping signatures for two of the three viruses. Antibody titers and transcriptomics data showed that an additional Priorix vaccination does not facilitate an equal immune response against the 3 viruses or among different vaccine recipients.
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Affiliation(s)
- Esther Bartholomeus
- Department of Medical Genetics, University of Antwerp/Antwerp University Hospital, Edegem, Belgium; AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium.
| | - Nicolas De Neuter
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Arvid Suls
- Department of Medical Genetics, University of Antwerp/Antwerp University Hospital, Edegem, Belgium; AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium
| | - George Elias
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Sanne van der Heijden
- Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Nina Keersmaekers
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Centre for Health Economics Research & Modeling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Hilde Jansens
- Department of Laboratory Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Viggo Van Tendeloo
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Philippe Beutels
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Centre for Health Economics Research & Modeling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Kris Laukens
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Benson Ogunjimi
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium; Centre for Health Economics Research & Modeling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium; Department of Paediatrics, Antwerp University Hospital, Edegem, Belgium.
| | - Geert Mortier
- Department of Medical Genetics, University of Antwerp/Antwerp University Hospital, Edegem, Belgium; AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium
| | - Pieter Meysman
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Pierre Van Damme
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Centre for the Evaluation of Vaccination (CEV), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
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10
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Jordaens S, Cooksey L, Bonney S, Orchard L, Coutinho M, Van Tendeloo V, Mills KI, Orchard K, Guinn BA. Serum profiling identifies ibrutinib as a treatment option for young adults with B-cell acute lymphoblastic leukaemia. Br J Haematol 2020; 189:500-512. [PMID: 32064588 DOI: 10.1111/bjh.16407] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 11/10/2019] [Indexed: 12/19/2022]
Abstract
Acute lymphoblastic leukaemia (ALL) is a haematological malignancy that is characterized by the uncontrolled proliferation of immature lymphocytes. 80% of cases occur in children where ALL is well understood and treated. However it has a devastating affects on adults, where multi-agent chemotherapy is the standard of care with allogeneic stem cell transplantation for those who are eligible. New treatments are required to extend remission and prevent relapse to improve patient survival rates. We used serum profiling to compare samples from presentation adult B-ALL patients with age- and sex-matched healthy volunteer (HV) sera and identified 69 differentially recognised antigens (P ≤ 0·02). BMX, DCTPP1 and VGLL4 showed no differences in transcription between patients and healthy donors but were each found to be present at higher levels in B-ALL patient samples than HVs by ICC. BMX plays a crucial role in the Bruton's Tyrosine Kinase (BTK) pathway which is bound by the BTK inhibitor, ibrutinib, suggesting adult B-ALL would also be a worthy target patient group for future clinical trials. We have shown the utility of proto-array analysis of B-ALL patient sera, predominantly from young adults, to help characterise the B-ALL immunome and identified a new target patient population for existing small molecule therapy.
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Affiliation(s)
- Stephanie Jordaens
- Department of Biomedical Sciences, University of Hull, Hull, UK.,Vaccine & Infectious Disease Institute, Laboratory of Experimental Hematology, University of Antwerp, Antwerpen, Belgium
| | - Leah Cooksey
- Department of Biomedical Sciences, University of Hull, Hull, UK
| | - Stephanie Bonney
- Cancer Sciences Unit, Somers Cancer Sciences Building, University of Southampton, Southampton, UK
| | - Laurence Orchard
- Cancer Sciences Unit, Somers Cancer Sciences Building, University of Southampton, Southampton, UK
| | | | - Viggo Van Tendeloo
- Vaccine & Infectious Disease Institute, Laboratory of Experimental Hematology, University of Antwerp, Antwerpen, Belgium
| | - Ken I Mills
- Centre for Cancer Research and Cell Biology, Queens University Belfast, Belfast, UK
| | - Kim Orchard
- Department of Haematology, University Hospital Southampton NHS Foundation Trust and University of Southampton, Southampton, UK
| | - Barbara-Ann Guinn
- Department of Biomedical Sciences, University of Hull, Hull, UK.,Cancer Sciences Unit, Somers Cancer Sciences Building, University of Southampton, Southampton, UK
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11
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Elias G, Ogunjimi B, Van Tendeloo V. Tracking Dye-Independent Approach to Identify and Isolate In Vitro Expanded T Cells. Cytometry A 2019; 95:1096-1107. [PMID: 31356002 DOI: 10.1002/cyto.a.23867] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 07/08/2019] [Accepted: 07/09/2019] [Indexed: 01/03/2023]
Abstract
T cell proliferation is routinely identified in vitro using tracking dyes or through detecting intracellular upregulation of the nuclear protein, Ki-67. However, labeling with tracking dyes is cumbersome, associated with cellular toxicity, while Ki-67 cannot be used to identify and isolate viable T cells, and both techniques are incompatible with MACS technology. Here, we introduce a simple tool to identify and isolate in vitro T cell expansion that is tracking dye-independent and allows for sorting of viable T cells. We show that CD71, a transferrin receptor, and CD98, a heterodimer glycoprotein involved in both integrin signaling and amino-acid transport, are both highly upregulated on proliferating T cells upon in vitro stimulation, and that CD71 expression is maximal on the more recent progeny T cells, while CD98 upregulation remains stable across different generations of progeny T cells. Moreover, we demonstrate that the upregulation of CD71 and CD98 identifies CFSElow T cells and provides further proof of the antigen-specificity of T cells identified by CD71 and CD98 dual upregulation based on tetramer staining. We further show that CD71 can be used to enrich for in vitro expanding T cells using MACS technology. In conclusion, we show that CD71 and CD98 can be used to identify and isolate expanded T cells following in vitro stimulation and that CD71 is an MACS-compatible alternative to tracking dyes or Ki-67 detection. © 2019 International Society for Advancement of Cytometry.
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Affiliation(s)
- George Elias
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.,Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
| | - Benson Ogunjimi
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.,Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium.,Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.,Department of Pediatrics, Antwerp University Hospital, Edegem, Belgium.,Antwerp Centre for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Viggo Van Tendeloo
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.,Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
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12
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Campillo-Davo D, Fujiki F, Van den Bergh JMJ, De Reu H, Smits ELJM, Goossens H, Sugiyama H, Lion E, Berneman ZN, Van Tendeloo V. Efficient and Non-genotoxic RNA-Based Engineering of Human T Cells Using Tumor-Specific T Cell Receptors With Minimal TCR Mispairing. Front Immunol 2018; 9:2503. [PMID: 30464762 PMCID: PMC6234959 DOI: 10.3389/fimmu.2018.02503] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Accepted: 10/10/2018] [Indexed: 12/12/2022] Open
Abstract
Genetic engineering of T cells with tumor specific T-cell receptors (TCR) is a promising strategy to redirect their specificity against cancer cells in adoptive T cell therapy protocols. Most studies are exploiting integrating retro- or lentiviral vectors to permanently introduce the therapeutic TCR, which can pose serious safety issues when treatment-related toxicities would occur. Therefore, we developed a versatile, non-genotoxic transfection method for human unstimulated CD8+ T cells. We describe an optimized double sequential electroporation platform whereby Dicer-substrate small interfering RNAs (DsiRNA) are first introduced to suppress endogenous TCR α and β expression, followed by electroporation with DsiRNA-resistant tumor-specific TCR mRNA. We demonstrate that double sequential electroporation of human primary unstimulated T cells with DsiRNA and TCR mRNA leads to unprecedented levels of transgene TCR expression due to a strongly reduced degree of TCR mispairing. Importantly, superior transgenic TCR expression boosts epitope-specific CD8+ T cell activation and killing activity. Altogether, DsiRNA and TCR mRNA double sequential electroporation is a rapid, non-integrating and highly efficient approach with an enhanced biosafety profile to engineer T cells with antigen-specific TCRs for use in early phase clinical trials.
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Affiliation(s)
- Diana Campillo-Davo
- Faculty of Medicine and Health Sciences, Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Fumihiro Fujiki
- Department of Cancer Immunology, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Johan M J Van den Bergh
- Faculty of Medicine and Health Sciences, Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Hans De Reu
- Faculty of Medicine and Health Sciences, Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Evelien L J M Smits
- Faculty of Medicine and Health Sciences, Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.,Center for Cell Therapy & Regenerative Medicine, Antwerp University Hospital, Edegem, Belgium.,Faculty of Medicine and Health Sciences, Center for Oncological Research (CORE), University of Antwerp, Antwerp, Belgium
| | - Herman Goossens
- Faculty of Medicine and Health Sciences, Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.,Division of Clinical Biology, Antwerp University Hospital, Edegem, Belgium
| | - Haruo Sugiyama
- Department of Cancer Immunology, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Eva Lion
- Faculty of Medicine and Health Sciences, Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.,Center for Cell Therapy & Regenerative Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Zwi N Berneman
- Faculty of Medicine and Health Sciences, Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.,Center for Cell Therapy & Regenerative Medicine, Antwerp University Hospital, Edegem, Belgium.,Division of Hematology, Antwerp University Hospital, Edegem, Belgium
| | - Viggo Van Tendeloo
- Faculty of Medicine and Health Sciences, Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
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13
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Bartholomeus E, De Neuter N, Meysman P, Suls A, Keersmaekers N, Elias G, Jansens H, Hens N, Smits E, Van Tendeloo V, Beutels P, Van Damme P, Ogunjimi B, Laukens K, Mortier G. Transcriptome profiling in blood before and after hepatitis B vaccination shows significant differences in gene expression between responders and non-responders. Vaccine 2018; 36:6282-6289. [PMID: 30205979 DOI: 10.1016/j.vaccine.2018.09.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Revised: 08/31/2018] [Accepted: 09/01/2018] [Indexed: 12/27/2022]
Abstract
INTRODUCTION As the hepatitis B virus is widely spread and responsible for considerable morbidity and mortality, WHO recommends vaccination from infancy to reduce acute infection and chronic carriers. However, current subunit vaccines are not 100% efficacious and leave 5-10% of recipients unprotected. METHODS To evaluate immune responses after Engerix-B vaccination, we determined, using mRNA-sequencing, whole blood early gene expression signatures before, at day 3 and day 7 after the first dose and correlated this with the resulting antibody titer after two vaccine doses. RESULTS Our results indicate that immune related genes are differentially expressed in responders mostly at day 3 and in non-responders mostly at day 7. The most remarkable difference between responders and non-responders were the differentially expressed genes before vaccination. The granulin precursor gene (GRN) was significantly downregulated in responders while upregulated in non-responders at day 0. Furthermore, absolute granulocytes numbers were significantly higher in non-responders at day 0. CONCLUSION The non-responders already showed an activated state of the immune system before vaccination. Furthermore, after vaccination, they exhibited a delayed and partial immune response in comparison to the responders. Our data may indicate that the baseline and untriggered immune system can influence the response upon hepatitis B vaccination.
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Affiliation(s)
- Esther Bartholomeus
- Department of Medical Genetics, University of Antwerp/Antwerp University Hospital, Edegem, Belgium; AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium
| | - Nicolas De Neuter
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Pieter Meysman
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Arvid Suls
- Department of Medical Genetics, University of Antwerp/Antwerp University Hospital, Edegem, Belgium; AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium
| | - Nina Keersmaekers
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Centre for Health Economics Research & Modeling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - George Elias
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Hilde Jansens
- Department of Laboratory Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Niel Hens
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Centre for Health Economics Research & Modeling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium; Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium; Centre for the Evaluation of Vaccination (CEV), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Evelien Smits
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium; Center for Cell Therapy and Regenerative Medicine, Antwerp University Hospital, Edegem, Belgium; Center for Oncological Research Antwerp, University of Antwerp, Antwerp, Belgium
| | - Viggo Van Tendeloo
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Philippe Beutels
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Centre for Health Economics Research & Modeling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Pierre Van Damme
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Centre for the Evaluation of Vaccination (CEV), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Benson Ogunjimi
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Centre for Health Economics Research & Modeling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium; Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium; Department of Paediatrics, Antwerp University Hospital, Edegem, Belgium
| | - Kris Laukens
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Geert Mortier
- Department of Medical Genetics, University of Antwerp/Antwerp University Hospital, Edegem, Belgium; AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium.
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14
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De Neuter N, Bartholomeus E, Elias G, Keersmaekers N, Suls A, Jansens H, Smits E, Hens N, Beutels P, Van Damme P, Mortier G, Van Tendeloo V, Laukens K, Meysman P, Ogunjimi B. Memory CD4 + T cell receptor repertoire data mining as a tool for identifying cytomegalovirus serostatus. Genes Immun 2018; 20:255-260. [PMID: 29904098 DOI: 10.1038/s41435-018-0035-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Revised: 04/18/2018] [Accepted: 04/25/2018] [Indexed: 12/17/2022]
Abstract
Pathogens of past and current infections have been identified directly by means of PCR or indirectly by measuring a specific immune response (e.g., antibody titration). Using a novel approach, Emerson and colleagues showed that the cytomegalovirus serostatus can also be accurately determined by using a T cell receptor repertoire data mining approach. In this study, we have sequenced the CD4+ memory T cell receptor repertoire of a Belgian cohort with known cytomegalovirus serostatus. A random forest classifier was trained on the CMV specific T cell receptor repertoire signature and used to classify individuals in the Belgian cohort. This study shows that the novel approach can be reliably replicated with an equivalent performance as that reported by Emerson and colleagues. Additionally, it provides evidence that the T cell receptor repertoire signature is to a large extent present in the CD4+ memory repertoire.
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Affiliation(s)
- Nicolas De Neuter
- Department of Mathematics and Computer Science, Adrem Data Lab, University of Antwerp, Antwerp, Belgium. .,Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium. .,AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium.
| | - Esther Bartholomeus
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium.,Center for Medical Genetics, University of Antwerp/Antwerp University Hospital, Edegem, Belgium
| | - George Elias
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium.,Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Nina Keersmaekers
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium.,Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Arvid Suls
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium.,Center for Medical Genetics, University of Antwerp/Antwerp University Hospital, Edegem, Belgium
| | - Hilde Jansens
- Department of Laboratory Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Evelien Smits
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium.,Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.,Center for Cell Therapy and Regenerative Medicine, Antwerp University Hospital, Edegem, Belgium.,Center for Oncological Research Antwerp, University of Antwerp, Antwerp, Belgium
| | - Niel Hens
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium.,Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.,Interuniversity Institute for Biostatistics and statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium.,Centre for the Evaluation of Vaccination (CEV), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Philippe Beutels
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium.,Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Pierre Van Damme
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium.,Centre for the Evaluation of Vaccination (CEV), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Geert Mortier
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium.,Center for Medical Genetics, University of Antwerp/Antwerp University Hospital, Edegem, Belgium
| | - Viggo Van Tendeloo
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium.,Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Kris Laukens
- Department of Mathematics and Computer Science, Adrem Data Lab, University of Antwerp, Antwerp, Belgium.,Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium.,AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium
| | - Pieter Meysman
- Department of Mathematics and Computer Science, Adrem Data Lab, University of Antwerp, Antwerp, Belgium.,Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium.,AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium
| | - Benson Ogunjimi
- AUDACIS, Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp, Antwerp, Belgium.,Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.,Department of Paediatrics, Antwerp University Hospital, Edegem, Belgium
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15
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Meysman P, De Neuter N, Bartholomeus E, Elias G, Van den Bergh J, Emonds MP, Haasnoot GW, Heynderickx S, Wens J, Michels NR, Lambert J, Lion E, Claas FHJ, Goossens H, Smits E, Van Damme P, Van Tendeloo V, Beutels P, Suls A, Mortier G, Laukens K, Ogunjimi B. Increased herpes zoster risk associated with poor HLA-A immediate early 62 protein (IE62) affinity. Immunogenetics 2017; 70:363-372. [PMID: 29196796 DOI: 10.1007/s00251-017-1047-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 11/20/2017] [Indexed: 01/08/2023]
Abstract
Around 30% of individuals will develop herpes zoster (HZ), caused by the varicella zoster virus (VZV), during their life. While several risk factors for HZ, such as immunosuppressive therapy, are well known, the genetic and molecular components that determine the risk of otherwise healthy individuals to develop HZ are still poorly understood. We created a computational model for the Human Leukocyte Antigen (HLA-A, -B, and -C) presentation capacity of peptides derived from the VZV Immediate Early 62 (IE62) protein. This model could then be applied to a HZ cohort with known HLA molecules. We found that HLA-A molecules with poor VZV IE62 presentation capabilities were more common in a cohort of 50 individuals with a history of HZ compared to a nationwide control group, which equated to a HZ risk increase of 60%. This tendency was most pronounced for cases of HZ at a young age, where other risk factors are less prevalent. These findings provide new molecular insights into the development of HZ and reveal a genetic predisposition in those individuals most at risk to develop HZ.
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Affiliation(s)
- Pieter Meysman
- ADREM Data Lab, Department of Mathematics and Computer Science, University of Antwerp, 2020, Antwerp, Belgium. .,Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, 2020, Antwerp, Belgium. .,Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.
| | - Nicolas De Neuter
- ADREM Data Lab, Department of Mathematics and Computer Science, University of Antwerp, 2020, Antwerp, Belgium.,Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, 2020, Antwerp, Belgium.,Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium
| | - Esther Bartholomeus
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Center for Medical Genetics, Antwerp University Hospital, 2650, Edegem, Belgium.,Center for Medical Genetics, University of Antwerp, 2650, Edegem, Belgium
| | - George Elias
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2650, Antwerp, Belgium.,Center for Cell Therapy and Regenerative Medicine, Antwerp University Hospital, 2650, Edegem, Belgium
| | - Johan Van den Bergh
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2650, Antwerp, Belgium
| | - Marie-Paule Emonds
- Laboratory for Histocompatibility and Immunogenetics (HILA), Red Cross Flanders, 2800, Mechelen, Belgium
| | - Geert W Haasnoot
- Department of Immunohaematology and Blood Transfusion, Leiden University Medical Center, 2300, Leiden, The Netherlands
| | - Steven Heynderickx
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2650, Antwerp, Belgium.,Center for Cell Therapy and Regenerative Medicine, Antwerp University Hospital, 2650, Edegem, Belgium
| | - Johan Wens
- Department of Primary and Interdisciplinary Care, University of Antwerp, 2610, Wilrijk, Belgium
| | - Nele R Michels
- Department of Primary and Interdisciplinary Care, University of Antwerp, 2610, Wilrijk, Belgium
| | - Julien Lambert
- Department of Dermatology, Antwerp University Hospital/University of Antwerp, 2650, Edegem, Belgium
| | - Eva Lion
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2650, Antwerp, Belgium.,Center for Cell Therapy and Regenerative Medicine, Antwerp University Hospital, 2650, Edegem, Belgium
| | - Frans H J Claas
- Department of Immunohaematology and Blood Transfusion, Leiden University Medical Center, 2300, Leiden, The Netherlands
| | - Herman Goossens
- Department of Laboratory Medicine, Antwerp University Hospital, 2650, Edegem, Belgium.,Lab of Medical Microbiology (LMM), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2610, Antwerp, Belgium
| | - Evelien Smits
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2650, Antwerp, Belgium.,Center for Cell Therapy and Regenerative Medicine, Antwerp University Hospital, 2650, Edegem, Belgium.,Center for Oncological Research Antwerp, University of Antwerp, 2610, Antwerp, Belgium
| | - Pierre Van Damme
- Centre for the Evaluation of Vaccination, Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2610, Antwerp, Belgium
| | - Viggo Van Tendeloo
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2650, Antwerp, Belgium
| | - Philippe Beutels
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2610, Antwerp, Belgium.,School of Public Health and Community Medicine, The University of New South Wales, Sydney, NSW, 2052, Australia
| | - Arvid Suls
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Center for Medical Genetics, Antwerp University Hospital, 2650, Edegem, Belgium.,Center for Medical Genetics, University of Antwerp, 2650, Edegem, Belgium
| | - Geert Mortier
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Center for Medical Genetics, Antwerp University Hospital, 2650, Edegem, Belgium.,Center for Medical Genetics, University of Antwerp, 2650, Edegem, Belgium
| | - Kris Laukens
- ADREM Data Lab, Department of Mathematics and Computer Science, University of Antwerp, 2020, Antwerp, Belgium.,Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, 2020, Antwerp, Belgium.,Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium
| | - Benson Ogunjimi
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2650, Antwerp, Belgium.,Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2610, Antwerp, Belgium.,Department of Paediatric Nephrology and Rheumatology, Ghent University Hospital, 9000, Ghent, Belgium.,Department of Paediatrics, Antwerp University Hospital, 2650, Edegem, Belgium
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16
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Van den Bergh J, Willemen Y, Lion E, Van Acker H, De Reu H, Anguille S, Goossens H, Berneman Z, Van Tendeloo V, Smits E. Transpresentation of interleukin-15 by IL-15/IL-15Rα mRNA-engineered human dendritic cells boosts antitumoral natural killer cell activity. Oncotarget 2016; 6:44123-33. [PMID: 26675759 DOI: 10.18632/oncotarget.6536] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2015] [Accepted: 11/28/2015] [Indexed: 01/20/2023] Open
Abstract
In cancer immunotherapy, the use of dendritic cell (DC)-based vaccination strategies can improve overall survival, but until now durable clinical responses remain scarce. To date, DC vaccines are designed primarily to induce effective T-cell responses, ignoring the antitumor activity potential of natural killer (NK) cells. Aiming to further improve current DC vaccination outcome, we engineered monocyte-derived DC to produce interleukin (IL)-15 and/or IL-15 receptor alpha (IL-15Rα) using mRNA electroporation. The addition of IL-15Rα to the protocol, enabling IL-15 transpresentation to neighboring NK cells, resulted in significantly better NK-cell activation compared to IL-15 alone. Next to upregulation of NK-cell membrane activation markers, IL-15 transpresentation resulted in increased NK-cell secretion of IFN-γ, granzyme B and perforin. Moreover, IL-15-transpresenting DC/NK cell cocultures from both healthy donors and acute myeloid leukemia (AML) patients in remission showed markedly enhanced cytotoxic activity against NK cell sensitive and resistant tumor cells. Blocking IL-15 transpresentation abrogated NK cell-mediated cytotoxicity against tumor cells, pointing to a pivotal role of IL-15 transpresentation by IL-15Rα to exert its NK cell-activating effects. In conclusion, we report an attractive approach to improve antitumoral NK-cell activity in DC-based vaccine strategies through the use of IL-15/IL-15Rα mRNA-engineered designer DC.
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Affiliation(s)
- Johan Van den Bergh
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Yannick Willemen
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Eva Lion
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Heleen Van Acker
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Hans De Reu
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Sébastien Anguille
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Herman Goossens
- Laboratory of Medical Microbiology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Zwi Berneman
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Viggo Van Tendeloo
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Evelien Smits
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium.,Center for Oncological Research Antwerp, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
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Van Damme P, Bouillette-Marussig M, Hens A, De Coster I, Depuydt C, Goubier A, Van Tendeloo V, Cools N, Goossens H, Hercend T, Timmerman B, Bissery MC. GTL001, A Therapeutic Vaccine for Women Infected with Human Papillomavirus 16 or 18 and Normal Cervical Cytology: Results of a Phase I Clinical Trial. Clin Cancer Res 2016; 22:3238-48. [PMID: 27252412 DOI: 10.1158/1078-0432.ccr-16-0085] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2016] [Accepted: 04/13/2016] [Indexed: 11/16/2022]
Abstract
PURPOSE Women infected with human papillomavirus (HPV) with normal cytology to mild abnormalities currently have no treatment options other than watchful waiting or surgery if high-grade cervical lesions or cancer develop. A therapeutic vaccine would offer the possibility of preventing high-grade lesions in HPV-infected women. GTL001 is a therapeutic vaccine composed of recombinant HPV16 and HPV18 E7 proteins fused to catalytically inactive Bordetella pertussis CyaA. This study examined the tolerability and immunogenicity of GTL001 in women infected with HPV16 or HPV18 with normal cytology. EXPERIMENTAL DESIGN This was a phase I trial (EudraCT No. 2010-018629-21). In an open-label part, subjects received two intradermal vaccinations 6 weeks apart of 100 or 600 μg GTL001 + topical 5% imiquimod cream at the injection site. In a double-blind part, subjects were randomized 2:1:1 to two vaccinations 6 weeks apart of 600 μg GTL001 + imiquimod, 600 μg GTL001 + placebo cream, or placebo + imiquimod. RESULTS Forty-seven women were included. No dropouts, treatment-related serious adverse events, or dose-limiting toxicities occurred. Local reactions were transient and mostly mild or moderate. HPV16/18 viral load decreased the most in the 600 μg GTL001 + imiquimod group. In post hoc analyses, the 600 μg GTL001 + imiquimod group had the highest rates of initial and sustained HPV16/18 clearance. Imiquimod increased antigen-specific T-cell response rates but not rates of solicited reactions. All subjects seroconverted to CyaA. CONCLUSIONS For women infected with HPV16 or HPV18 with normal cervical cytology, GTL001 was immunogenic and had acceptable safety profile. Clin Cancer Res; 22(13); 3238-48. ©2016 AACR.
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Affiliation(s)
| | | | | | | | - Christophe Depuydt
- Department of Molecular Diagnostics, AML, Sonic Healthcare, Antwerp, Belgium
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18
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Meysman P, Fedorov D, Van Tendeloo V, Ogunjimi B, Laukens K. Erratum to: Immunological evasion of immediate-early varicella zoster virus proteins. Immunogenetics 2016; 68:487. [PMID: 27107763 DOI: 10.1007/s00251-016-0912-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Affiliation(s)
- Pieter Meysman
- Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium. .,Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Edegem, Belgium.
| | - Dmitry Fedorov
- Institute of Cellular Neurosciences, University of Bonn, Bonn, Germany
| | - Viggo Van Tendeloo
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Benson Ogunjimi
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.,Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.,Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Hasselt, Belgium
| | - Kris Laukens
- Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium.,Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Edegem, Belgium
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19
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Meysman P, Fedorov D, Van Tendeloo V, Ogunjimi B, Laukens K. Immunological evasion of immediate-early varicella zoster virus proteins. Immunogenetics 2016; 68:483-486. [PMID: 27020058 DOI: 10.1007/s00251-016-0911-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Accepted: 03/22/2016] [Indexed: 12/22/2022]
Abstract
The varicella zoster virus (VZV) causes the childhood disease commonly known as chickenpox and can later in life reactivate as herpes zoster. The adaptive immune system is known to play an important role in suppressing VZV reactivation. A central aspect of this system is the presentation of VZV-derived peptides by the major histocompatibility complex (MHC) proteins. Here, we investigate if key VZV proteins have evolved their amino acid sequence to avoid presentation by MHC based on predictive models of MHC-peptide affinity. This study shows that the immediate-early proteins of all characterized VZV strains are profoundly depleted for high-affinity MHC-I-restricted epitopes. The same depletion can be found in its closest animal analog, the simian varicella virus. Further orthology analysis towards other herpes viruses suggests that the protein amino acid frequency is one of the primary drivers of targeted epitope depletion.
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Affiliation(s)
- Pieter Meysman
- Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium. .,Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Edegem, Belgium.
| | - Dmitry Fedorov
- Institute of Cellular Neurosciences, University of Bonn, Bonn, Germany
| | - Viggo Van Tendeloo
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Benson Ogunjimi
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.,Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.,Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Hasselt, Belgium
| | - Kris Laukens
- Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium.,Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Edegem, Belgium
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Abstract
Monitoring the immune response is an essential aspect of numerous clinical vaccination trials in order to evaluate the efficacy. In these clinical vaccination trials, peripheral blood mononuclear cells (PBMC) are isolated at different time points from patient blood samples and subsequently cryopreserved to allow batch analysis at a later time point. Here, we present a newly developed short-time assay which allows direct ex vivo analysis of multi-epitope antigen-specific immune responses using mRNA electroporation of cryopreserved PBMC. This novel method is a rapid and elegant tool and will be convenient for monitoring the cellular immune status of patients in clinical vaccination settings.
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Affiliation(s)
- Nathalie Cools
- Laboratory of Experimental Hematology, Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine & Health Sciences, University of Antwerp, Wilrijk, Belgium.
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21
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Ogunjimi B, Peeters D, Hens N, Malfait R, Van Tendeloo V, Van Damme P, Beutels P, Smits E. Sampling site matters when counting lymphocyte subpopulations. PLoS One 2012; 7:e41405. [PMID: 22848485 PMCID: PMC3405139 DOI: 10.1371/journal.pone.0041405] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2012] [Accepted: 06/21/2012] [Indexed: 12/02/2022] Open
Abstract
Clinical and scientific work routinely relies on antecubital venipunctures for hematological, immunological or other analyses on blood. This study tested the hypothesis that antecubital veins can be considered to be a good proxy for other sampling sites. Using a hematocytometer and a flow cytometer, we analyzed the cell counts from samples coming from the radial artery, the dorsal hand veins and the antecubital veins from 18 volunteers. Most surprisingly, we identified the greatest difference not to exist between arterial and venous circulation, but between the distal (radial artery & dorsal hand veins) and proximal (antecubital veins) sampling sites. Naïve T cells had a higher cell count distally compared to proximally and the reverse was true for effector memory T cells. Despite these differences there were high correlations between the different sampling sites, which partially supports our initial hypothesis. Our findings are crucial for the future design and interpretation of immunological research, and for clinical practice. Furthermore, our results suggest a role for interval lymph nodes in the trafficking of lymphocytes.
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Affiliation(s)
- Benson Ogunjimi
- Centre for Health Economics Research and Modeling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.
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Willemen Y, Huizing MT, Smits E, Anguille S, Nijs G, Stein B, Van Tendeloo V, Peeters M, Berneman ZN. Open label phase I/II study of Wilms' tumor gene 1 (WT1) mRNA-transfected autologous dendritic cell vaccination in patients with solid tumors. J Clin Oncol 2012. [DOI: 10.1200/jco.2012.30.15_suppl.e13051] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
e13051 Background: Active specific immunotherapy, aimed at stimulating tumor-specific immunity, is widely under investigation to determine its place in cancer treatment. Methods: We are conducting an open label phase I/II clinical trial to evaluate the feasibility, toxicity and immunogenicity of intradermal vaccination with keyhole limpet hemocyanin (KLH)-exposed WT1 mRNA-transfected autologous monocyte-derived dendritic cells (DC). Recruitment has finished, but vaccination and follow-up continue. Vaccination consists of biweekly intradermal injection of 10 million DC in the medial region of the arm close to the axilla. Clinical evaluation with PET, CAT or MRI is done before start of the vaccination and repeated every 8 weeks. After 4 vaccinations patients undergo a delayed-type hypersensitivity (DTH) skin test to evaluate immunological responses. Results: 18 patients (8 breast cancer and 3 astrocytoma patients, 1 melanoma, 1 mesothelioma, 1 ovarian, 1 colon, 1 esophageal, 1 renal cell and 1 peritoneal cancer patient) were included in this trial from May, 2010 until January, 2012 to whom we administered a total of 175 vaccines. The median number of vaccines produced per patient was 15 (range 5-34). Median follow-up from start of the vaccination is 26 weeks (range 2-83). All evaluable patients exhibited local symptoms such as itching and/or redness at the sites of injection after the second vaccination and onward (n=17) and displayed positive DTH skin reactions (induration ≥2 mm) to the vaccine and its components (n=15). Systemic side effects were limited to 2 patients who each experienced a single episode of flu-like symptoms within 24 hours after vaccination. Thus far, 3 patients died of disease progression, while 7 others had progressive disease and 6 had stable disease at the most recent evaluation compared to before vaccination according to RECIST 1.1. Of the latter group 4 patients received another form of therapy at some point during vaccination. Conclusions: Based on these results our WT1 mRNA-transfected DC vaccination appears to be feasible and safe for patients with solid tumors. Furthermore, our vaccine is capable of inducing immune responses in these patients.
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Affiliation(s)
| | | | | | | | - Griet Nijs
- Antwerp University Hospital, Edegem, Belgium
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23
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Ogunjimi B, Van Tendeloo V, Van Damme P, Beutels P. What counts in cytometric analysis to document vaccine immunogenicity? Hum Vaccin Immunother 2012; 8:499-500. [PMID: 22370519 DOI: 10.4161/hv.18855] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Studies on vaccines and infectious diseases are increasingly adding immune cytometry (for e.g., flow cytometry or ELISPOT assays) to the routine use of antibody titers as a way to report immunogenicity. We advocate that the classical presentation of cytometric data in terms of percentages should best be supplemented by an absolute cell count per ml. We do this by discussing a simple hypothetical example illustrating that without knowledge of the absolute cell count per ml detection competition will render a correct comparison between different samples impossible in all situations where an inter-individual or intra-individual (longitudinal) variation in peripheral blood mononuclear cell concentrations is present.
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Affiliation(s)
- Benson Ogunjimi
- Centre for Health Economics Research and Modeling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.
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24
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Ogunjimi B, Smits E, Hens N, Hens A, Lenders K, Ieven M, Van Tendeloo V, Van Damme P, Beutels P. Exploring the impact of exposure to primary varicella in children on varicella-zoster virus immunity of parents. Viral Immunol 2011; 24:151-7. [PMID: 21449725 DOI: 10.1089/vim.2010.0031] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Varicella-zoster virus (VZV) causes both primary varicella, and through reactivation of the virus, herpes zoster. It is hypothesized that VZV-immune adults may reduce the probability of developing herpes zoster through exposure to varicella. In this study we examine the existence of immunological boosting in VZV-immune adults after close contact with primary varicella. We followed-up 18 parents with household exposure to primary varicella for 1 y. Fifteen age-matched healthy and 20 older volunteers served as control groups. Cellular (IFN-γ ELISPOT) and humoral responses were measured. Data analyses were performed by t-tests and linear mixed models. The young control group only showed higher cellular responses than the older control group and the exposed group 1 mo after exposure. The exposed group had a strong tendency toward higher cellular responses compared to the older control group, reaching significance 1 y post-exposure. The best fitting linear mixed model predicts a decline in cellular response of 50% between 1 wk and 1 mo post-exposure, followed by an increase to attain an 80% higher level at 1 y compared to the first week post-exposure. No significant results emerged based on the humoral response of the individual parents in the exposed group, despite a general tendency toward higher antibody concentrations in the exposed versus the control groups. No significant difference in humoral immunity was found between the control groups. One year after initial re-exposure to VZV, VZV-immune adults showed a rise in cellular response as assessed by IFN-γ ELISPOT, and steady-state levels for the humoral response.
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Affiliation(s)
- Benson Ogunjimi
- Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), University of Antwerp, Antwerp, Belgium.
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25
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Lambrechts N, Nelissen I, Van Tendeloo V, Witters H, Van Den Heuvel R, Hooyberghs J, Schoeters G. Functionality and specificity of gene markers for skin sensitization in dendritic cells. Toxicol Lett 2011; 203:106-10. [DOI: 10.1016/j.toxlet.2011.02.015] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2011] [Revised: 02/10/2011] [Accepted: 02/14/2011] [Indexed: 10/18/2022]
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26
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Zakaria N, Koppen C, Van Tendeloo V, Berneman Z, Hopkinson A, Tassignon MJ. Standardized Limbal Epithelial Stem Cell Graft Generation and Transplantation. Tissue Eng Part C Methods 2010; 16:921-7. [DOI: 10.1089/ten.tec.2009.0634] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Affiliation(s)
- Nadia Zakaria
- Department of Ophthalmology, University Hospital Antwerp, Antwerp, Belgium
- Center for Cell Therapy and Regenerative Medicine, University Hospital Antwerp, Antwerp, Belgium
| | - Carina Koppen
- Department of Ophthalmology, University Hospital Antwerp, Antwerp, Belgium
| | - Viggo Van Tendeloo
- Center for Cell Therapy and Regenerative Medicine, University Hospital Antwerp, Antwerp, Belgium
| | - Zwi Berneman
- Center for Cell Therapy and Regenerative Medicine, University Hospital Antwerp, Antwerp, Belgium
| | - Andrew Hopkinson
- Department of Ophthalmology and Visual Sciences, Nottingham University, Nottingham, United Kingdom
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27
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Coosemans A, Wölfl M, Berneman ZN, Van Tendeloo V, Vergote I, Amant F, Van Gool SW. Immunological response after therapeutic vaccination with WT1 mRNA-loaded dendritic cells in end-stage endometrial carcinoma. Anticancer Res 2010; 30:3709-3714. [PMID: 20944158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
BACKGROUND Wilms' tumour gene 1 (WT1), a highly ranked immunotherapeutic target, is expressed in uterine cancer and therefore WT1 immunotherapy may present an attractive treatment option. PATIENT AND METHODS An HLA-A2.1-positive 46-year-old woman with end-stage serous endometrial cancer received 4 weekly injections of WT1-RNA-loaded dendritic cells. Response was measured clinically (CT scan), biochemically (CA125) and immunologically (WT1-specific T cells). RESULTS The patient showed WT1 positivity in 10% of tumour cells and diffusely in the intratumoural endothelial cells of the recurrent disease. After 2 injections, CA125 started to decrease and WT1-specific T-cells increased 2.5-fold. The treatment was feasible and there were no treatment-related side-effects. However, the patient, suffering from diffuse disease which became progressive again, died 8 months later. CONCLUSION This is the first patient with a WT1-positive endometrial carcinoma, to receive immunotherapy with WT1-RNA-loaded dendritic cells, resulting in a vaccine-specific T cell response.
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Affiliation(s)
- Ann Coosemans
- Department of Child and Women, UZ Gasthuisberg, Katholieke Universiteit Leuven, Belgium.
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28
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Lambrechts N, Vanheel H, Nelissen I, Witters H, Van Den Heuvel R, Van Tendeloo V, Schoeters G, Hooyberghs J. Assessment of chemical skin-sensitizing potency by an in vitro assay based on human dendritic cells. Toxicol Sci 2010; 116:122-9. [PMID: 20375081 DOI: 10.1093/toxsci/kfq108] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The skin-sensitizing potential of chemicals is an important concern for public health and thus a significant end point in the hazard identification process. To determine skin-sensitizing capacity, large research efforts focus on the development of assays, which do not require animals. As such, an in vitro test has previously been developed based on the differential expression of CREM and CCR2 transcripts in CD34(+) progenitor-derived dendritic cells (CD34-DC), which allows to classify chemicals as skin (non-)sensitizing. However, skin sensitization is not an all-or-none phenomenon, and up to now, the assessment of relative potency can only be derived using the in vivo local lymph node assay (LLNA). In our study, we analyzed the feasibility to predict the sensitizing potency, i.e., the LLNA EC3 values, of 15 skin sensitizers using in vitro data from the CD34-DC-based assay. Hereto, we extended the in vitro-generated gene expression data set by an additional source of information, the concentration of the compound that causes 20% cell damage (IC20) in CD34-DC. We statistically confirmed that this IC20 is linearly independent from the gene expression changes but that it does correlate with LLNA EC3 values. In a further analysis, we applied a robust linear regression with both IC20 and expression changes of CREM and CCR2 as explanatory variables. For 13 out of 15 compounds, a high linear correlation was established between the in vitro model and the LLNA EC3 values over a range of four orders of magnitude, i.e., from weak to extreme sensitizers.
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Affiliation(s)
- Nathalie Lambrechts
- Unit Environmental Risk and Health, Toxicology, Flemish Institute for Technological Research (VITO NV), Mol, Belgium.
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29
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Lambrechts N, Verstraelen S, Hooyberghs J, Witters H, Van Tendeloo V, Van Cauwenberge P, Nelissen I, Van Den Heuvel R, Schoeters G. THP-1 monocytes but not macrophages as a potential alternative for CD34+ dendritic cells to identify chemical skin sensitizers. Toxicol Lett 2009. [DOI: 10.1016/j.toxlet.2009.06.216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Lambrechts N, Verstraelen S, Lodewyckx H, Felicio A, Hooyberghs J, Witters H, Van Tendeloo V, Van Cauwenberge P, Nelissen I, Van Den Heuvel R, Schoeters G. THP-1 monocytes but not macrophages as a potential alternative for CD34+ dendritic cells to identify chemical skin sensitizers. Toxicol Appl Pharmacol 2009; 236:221-30. [DOI: 10.1016/j.taap.2009.01.026] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2008] [Revised: 01/16/2009] [Accepted: 01/30/2009] [Indexed: 10/21/2022]
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Bergwerf I, De Vocht N, Tambuyzer B, Verschueren J, Reekmans K, Daans J, Ibrahimi A, Van Tendeloo V, Chatterjee S, Goossens H, Jorens PG, Baekelandt V, Ysebaert D, Van Marck E, Berneman ZN, Linden AVD, Ponsaerts P. Reporter gene-expressing bone marrow-derived stromal cells are immune-tolerated following implantation in the central nervous system of syngeneic immunocompetent mice. BMC Biotechnol 2009; 9:1. [PMID: 19128466 PMCID: PMC2630974 DOI: 10.1186/1472-6750-9-1] [Citation(s) in RCA: 43] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2008] [Accepted: 01/07/2009] [Indexed: 01/09/2023] Open
Abstract
Background Cell transplantation is likely to become an important therapeutic tool for the treatment of various traumatic and ischemic injuries to the central nervous system (CNS). However, in many pre-clinical cell therapy studies, reporter gene-assisted imaging of cellular implants in the CNS and potential reporter gene and/or cell-based immunogenicity, still remain challenging research topics. Results In this study, we performed cell implantation experiments in the CNS of immunocompetent mice using autologous (syngeneic) luciferase-expressing bone marrow-derived stromal cells (BMSC-Luc) cultured from ROSA26-L-S-L-Luciferase transgenic mice, and BMSC-Luc genetically modified using a lentivirus encoding the enhanced green fluorescence protein (eGFP) and the puromycin resistance gene (Pac) (BMSC-Luc/eGFP/Pac). Both reporter gene-modified BMSC populations displayed high engraftment capacity in the CNS of immunocompetent mice, despite potential immunogenicity of introduced reporter proteins, as demonstrated by real-time bioluminescence imaging (BLI) and histological analysis at different time-points post-implantation. In contrast, both BMSC-Luc and BMSC-Luc/eGFP/Pac did not survive upon intramuscular cell implantation, as demonstrated by real-time BLI at different time-points post-implantation. In addition, ELISPOT analysis demonstrated the induction of IFN-γ-producing CD8+ T-cells upon intramuscular cell implantation, but not upon intracerebral cell implantation, indicating that BMSC-Luc and BMSC-Luc/eGFP/Pac are immune-tolerated in the CNS. However, in our experimental transplantation model, results also indicated that reporter gene-specific immune-reactive T-cell responses were not the main contributors to the immunological rejection of BMSC-Luc or BMSC-Luc/eGFP/Pac upon intramuscular cell implantation. Conclusion We here demonstrate that reporter gene-modified BMSC derived from ROSA26-L-S-L-Luciferase transgenic mice are immune-tolerated upon implantation in the CNS of syngeneic immunocompetent mice, providing a research model for studying survival and localisation of autologous BMSC implants in the CNS by real-time BLI and/or histological analysis in the absence of immunosuppressive therapy.
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Affiliation(s)
- Irene Bergwerf
- Laboratory of Experimental Hematology, University of Antwerp, Antwerp, Belgium.
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Lambrechts N, Hooyberghs J, Schoeters E, De Boever P, Witters H, Van Den Heuvel R, Van Tendeloo V, Nelissen I, Schoeters G. Pathway analysis of dendritic cell markers for skin sensitization. Toxicol Lett 2008. [DOI: 10.1016/j.toxlet.2008.06.440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Van den Plas D, Ponsaerts P, Van Tendeloo V, Van Bockstaele DR, Berneman ZN, Merregaert J. Efficient removal of LoxP-flanked genes by electroporation of Cre-recombinase mRNA. Biochem Biophys Res Commun 2003; 305:10-5. [PMID: 12732189 DOI: 10.1016/s0006-291x(03)00669-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Introduction of Cre-recombinase in target cells is currently achieved by transfection of plasmid DNA or by viral-mediated transduction. However, efficiency of non-viral DNA transfection is often low in many cell types, and the use of viral vectors for transduction implies a more complex and laborious manipulation associated with safety issues. We have developed a non-viral non-DNA technique for rapid and highly efficient excision of LoxP-flanked DNA sequences based on electroporation of in vitro transcribed mRNA encoding Cre-recombinase. A K562-DSRed[EGFP] cell line was developed in order to measure Cre-mediated recombination by flow cytometric analysis. These cells have a stable integrated DSRed reporter gene flanked by two LoxP sites, and an EGFP reporter gene, which could only be transcribed when the coding sequence for DSRed was removed. The presented data show recombination efficiencies, as measured by appearance of EGFP-fluorescence, of up to 85% in Cre-recombinase mRNA-electroporated K562-DSRed[EGFP] cells. In conclusion, mRNA electroporation of Cre-recombinase is a powerful, safe, and clinically applicable alternative to current technologies used for excision of stably integrated LoxP-flanked DNA sequences.
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Affiliation(s)
- Dave Van den Plas
- Department of Biomedical Sciences, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk, Belgium
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Van Meirvenne S, Straetman L, Heirman C, Dullaers M, De Greef C, Van Tendeloo V, Thielemans K. Efficient genetic modification of murine dendritic cells by electroporation with mRNA. Cancer Gene Ther 2002; 9:787-97. [PMID: 12189529 DOI: 10.1038/sj.cgt.7700499] [Citation(s) in RCA: 89] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2002] [Indexed: 11/08/2022]
Abstract
Recently, human dendritic cells (DCs) pulsed with mRNA encoding a broad range of tumor antigens have proven to be potent activators of a primary anti-tumor-specific T-cell response in vitro. The aim of this study was to improve the mRNA pulsing of murine DC. Compared to a standard lipofection protocol and passive pulsing, electroporation was, in our hands, the most efficient method. The optimal conditions to electroporate murine bone marrow-derived DCs with mRNA were determined using enhanced green fluorescent protein and a truncated form of the nerve growth factor receptor. We could obtain high transfection efficiencies around 70-80% with a mean fluorescence intensity of 100-200. A maximal expression level was reached 3 hours after electroporation. A clear dose-response effect was seen depending on the amount of mRNA used. Importantly, the electroporation process did not affect the viability nor the allostimulatory capacity or phenotype of the DC. To study the capacity of mRNA-electroporated DCs to present antigen in the context of MHC classes I and II, we made use of chimeric constructs of ovalbumin. The dose-dependent response effect and the duration of presentation were also determined. Together, these results demonstrate that mRNA electroporation is a useful method to generate genetically modified murine DC, which can be used for preclinical studies testing immunotherapeutic approaches.
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Affiliation(s)
- Sonja Van Meirvenne
- Laboratory of Physiology-Immunology of the Medical School of the Vrije Universiteit Brussel (VUB), Brussels, Belgium
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