1
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Yabo YA, Moreno-Sanchez PM, Pires-Afonso Y, Kaoma T, Nosirov B, Scafidi A, Ermini L, Lipsa A, Oudin A, Kyriakis D, Grzyb K, Poovathingal SK, Poli A, Muller A, Toth R, Klink B, Berchem G, Berthold C, Hertel F, Mittelbronn M, Heiland DH, Skupin A, Nazarov PV, Niclou SP, Michelucci A, Golebiewska A. Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts. Genome Med 2024; 16:51. [PMID: 38566128 PMCID: PMC10988817 DOI: 10.1186/s13073-024-01321-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 03/22/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND A major contributing factor to glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive environment, where GBM-associated myeloid cells, including resident microglia and peripheral monocyte-derived macrophages, play critical pro-tumoral roles. However, it is unclear whether recruited myeloid cells are phenotypically and functionally identical in GBM patients and whether this heterogeneity is recapitulated in patient-derived orthotopic xenografts (PDOXs). A thorough understanding of the GBM ecosystem and its recapitulation in preclinical models is currently missing, leading to inaccurate results and failures of clinical trials. METHODS Here, we report systematic characterization of the tumor microenvironment (TME) in GBM PDOXs and patient tumors at the single-cell and spatial levels. We applied single-cell RNA sequencing, spatial transcriptomics, multicolor flow cytometry, immunohistochemistry, and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM PDOXs representing different tumor phenotypes were compared to glioma mouse GL261 syngeneic model and patient tumors. RESULTS We show that GBM tumor cells reciprocally interact with host cells to create a GBM patient-specific TME in PDOXs. We detected the most prominent transcriptomic adaptations in myeloid cells, with brain-resident microglia representing the main population in the cellular tumor, while peripheral-derived myeloid cells infiltrated the brain at sites of blood-brain barrier disruption. More specifically, we show that GBM-educated microglia undergo transition to diverse phenotypic states across distinct GBM landscapes and tumor niches. GBM-educated microglia subsets display phagocytic and dendritic cell-like gene expression programs. Additionally, we found novel microglial states expressing cell cycle programs, astrocytic or endothelial markers. Lastly, we show that temozolomide treatment leads to transcriptomic plasticity and altered crosstalk between GBM tumor cells and adjacent TME components. CONCLUSIONS Our data provide novel insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumors. We show the key role of microglial phenotypic states in supporting GBM tumor growth and response to treatment. Our data place PDOXs as relevant models to assess the functionality of the TME and changes in the GBM ecosystem upon treatment.
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Affiliation(s)
- Yahaya A Yabo
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1210, Luxembourg, Luxembourg
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367, Belvaux, Luxembourg
| | - Pilar M Moreno-Sanchez
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1210, Luxembourg, Luxembourg
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367, Belvaux, Luxembourg
| | - Yolanda Pires-Afonso
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367, Belvaux, Luxembourg
- Neuro-Immunology Group, Department of Cancer Research, Luxembourg Institute of Health, L-1210, Luxembourg, Luxembourg
| | - Tony Kaoma
- Bioinformatics Platform, Department of Medical Informatics, Luxembourg Institute of Health, L-1445, Strassen, Luxembourg
| | - Bakhtiyor Nosirov
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1210, Luxembourg, Luxembourg
- Multiomics Data Science, Department of Cancer Research, Luxembourg Institute of Health, L-1445, Strassen, Luxembourg
| | - Andrea Scafidi
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367, Belvaux, Luxembourg
- Neuro-Immunology Group, Department of Cancer Research, Luxembourg Institute of Health, L-1210, Luxembourg, Luxembourg
| | - Luca Ermini
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1210, Luxembourg, Luxembourg
| | - Anuja Lipsa
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1210, Luxembourg, Luxembourg
| | - Anaïs Oudin
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1210, Luxembourg, Luxembourg
| | - Dimitrios Kyriakis
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367, Belvaux, Luxembourg
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, L-4362, Esch-sur-Alzette, Luxembourg
| | - Kamil Grzyb
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, L-4362, Esch-sur-Alzette, Luxembourg
| | - Suresh K Poovathingal
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, L-4362, Esch-sur-Alzette, Luxembourg
- Single Cell Analytics & Microfluidics Core, Vlaams Instituut Voor Biotechnologie-KU Leuven, 3000, Louvain, Belgium
| | - Aurélie Poli
- Neuro-Immunology Group, Department of Cancer Research, Luxembourg Institute of Health, L-1210, Luxembourg, Luxembourg
| | - Arnaud Muller
- Bioinformatics Platform, Department of Medical Informatics, Luxembourg Institute of Health, L-1445, Strassen, Luxembourg
| | - Reka Toth
- Bioinformatics Platform, Department of Medical Informatics, Luxembourg Institute of Health, L-1445, Strassen, Luxembourg
- Multiomics Data Science, Department of Cancer Research, Luxembourg Institute of Health, L-1445, Strassen, Luxembourg
| | - Barbara Klink
- National Center of Genetics, Laboratoire National de Santé, L-3555, Dudelange, Luxembourg
- Department of Cancer Research, Luxembourg Institute of Health, L-1210, Luxembourg, Luxembourg
- German Cancer Consortium (DKTK): Core Unit for Molecular Tumor Diagnostics (CMTD), National Center for Tumor Diseases (NCT/UCC), Cancer Consortium (DKTK) Partner Site Dresden, and German Cancer Research Center (DKFZ), Dresden, Heidelberg, 01307, Germany
- Institute for Clinical Genetics, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, 01307, Dresden, Germany
| | - Guy Berchem
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367, Belvaux, Luxembourg
- Department of Cancer Research, Luxembourg Institute of Health, L-1210, Luxembourg, Luxembourg
- Centre Hospitalier Luxembourg, L-1210, Luxembourg, Luxembourg
| | | | - Frank Hertel
- Centre Hospitalier Luxembourg, L-1210, Luxembourg, Luxembourg
| | - Michel Mittelbronn
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367, Belvaux, Luxembourg
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, L-4362, Esch-sur-Alzette, Luxembourg
- Department of Cancer Research, Luxembourg Institute of Health, L-1210, Luxembourg, Luxembourg
- Luxembourg Center of Neuropathology (LCNP), L-3555, Dudelange, Luxembourg
- National Center of Pathology (NCP), Laboratoire National de Santé, L-3555, Dudelange, Luxembourg
| | - Dieter H Heiland
- Translational Neurosurgery, Friedrich-Alexander University Erlangen Nuremberg, 91054, Erlangen, Germany
- Department of Neurosurgery, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, 91054, Erlangen, Germany
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Department of Neurosurgery, Medical Center, University of Freiburg, 79106, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, 79106, Freiburg, Germany
| | - Alexander Skupin
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, L-4362, Esch-sur-Alzette, Luxembourg
- Department of Physics and Material Science, University Luxembourg, L-4367, Belvaux, Luxembourg
- Department of Neuroscience, University of California San Diego, La Jolla, CA, 92093, USA
| | - Petr V Nazarov
- Bioinformatics Platform, Department of Medical Informatics, Luxembourg Institute of Health, L-1445, Strassen, Luxembourg
- Multiomics Data Science, Department of Cancer Research, Luxembourg Institute of Health, L-1445, Strassen, Luxembourg
| | - Simone P Niclou
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1210, Luxembourg, Luxembourg
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367, Belvaux, Luxembourg
| | - Alessandro Michelucci
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1210, Luxembourg, Luxembourg.
- Neuro-Immunology Group, Department of Cancer Research, Luxembourg Institute of Health, L-1210, Luxembourg, Luxembourg.
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, L-4362, Esch-sur-Alzette, Luxembourg.
| | - Anna Golebiewska
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1210, Luxembourg, Luxembourg.
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Dusoswa SA, Verhoeff J, van Asten S, Lübbers J, van den Braber M, Peters S, Abeln S, Crommentuijn MH, Wesseling P, Vandertop WP, Twisk JWR, Würdinger T, Noske D, van Kooyk Y, Garcia-Vallejo JJ. The immunological landscape of peripheral blood in glioblastoma patients and immunological consequences of age and dexamethasone treatment. Front Immunol 2024; 15:1343484. [PMID: 38318180 PMCID: PMC10839779 DOI: 10.3389/fimmu.2024.1343484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 01/02/2024] [Indexed: 02/07/2024] Open
Abstract
Background Glioblastomas manipulate the immune system both locally and systemically, yet, glioblastoma-associated changes in peripheral blood immune composition are poorly studied. Age and dexamethasone administration in glioblastoma patients have been hypothesized to limit the effectiveness of immunotherapy, but their effects remain unclear. We compared peripheral blood immune composition in patients with different types of brain tumor to determine the influence of age, dexamethasone treatment, and tumor volume. Methods High-dimensional mass cytometry was used to characterise peripheral blood mononuclear cells of 169 patients with glioblastoma, lower grade astrocytoma, metastases and meningioma. We used blood from medically-refractory epilepsy patients and healthy controls as control groups. Immune phenotyping was performed using FlowSOM and t-SNE analysis in R followed by supervised annotation of the resulting clusters. We conducted multiple linear regression analysis between intracranial pathology and cell type abundance, corrected for clinical variables. We tested correlations between cell type abundance and survival with Cox-regression analyses. Results Glioblastoma patients had significantly fewer naive CD4+ T cells, but higher percentages of mature NK cells than controls. Decreases of naive CD8+ T cells and alternative monocytes and an increase of memory B cells in glioblastoma patients were influenced by age and dexamethasone treatment, and only memory B cells by tumor volume. Progression free survival was associated with percentages of CD4+ regulatory T cells and double negative T cells. Conclusion High-dimensional mass cytometry of peripheral blood in patients with different types of intracranial tumor provides insight into the relation between intracranial pathology and peripheral immune status. Wide immunosuppression associated with age and pre-operative dexamethasone treatment provide further evidence for their deleterious effects on treatment with immunotherapy.
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Affiliation(s)
- Sophie A. Dusoswa
- Department of Molecular Cell Biology and Immunology, Amsterdam Infection and Immunity Institute, Cancer Center Amsterdam, Amsterdam UMC, VU Amsterdam, Amsterdam, Netherlands
- Department of Neurosurgery, Amsterdam UMC, VU Amsterdam, Amsterdam, Netherlands
| | - Jan Verhoeff
- Department of Molecular Cell Biology and Immunology, Amsterdam Infection and Immunity Institute, Cancer Center Amsterdam, Amsterdam UMC, VU Amsterdam, Amsterdam, Netherlands
| | - Saskia van Asten
- Department of Molecular Cell Biology and Immunology, Amsterdam Infection and Immunity Institute, Cancer Center Amsterdam, Amsterdam UMC, VU Amsterdam, Amsterdam, Netherlands
| | - Joyce Lübbers
- Department of Molecular Cell Biology and Immunology, Amsterdam Infection and Immunity Institute, Cancer Center Amsterdam, Amsterdam UMC, VU Amsterdam, Amsterdam, Netherlands
| | - Marlous van den Braber
- Department of Molecular Cell Biology and Immunology, Amsterdam Infection and Immunity Institute, Cancer Center Amsterdam, Amsterdam UMC, VU Amsterdam, Amsterdam, Netherlands
| | - Sophie Peters
- Department of Molecular Cell Biology and Immunology, Amsterdam Infection and Immunity Institute, Cancer Center Amsterdam, Amsterdam UMC, VU Amsterdam, Amsterdam, Netherlands
| | - Sanne Abeln
- Department of Computer Science, Free University, Amsterdam, Netherlands
| | - Matheus H.W. Crommentuijn
- Department of Molecular Cell Biology and Immunology, Amsterdam Infection and Immunity Institute, Cancer Center Amsterdam, Amsterdam UMC, VU Amsterdam, Amsterdam, Netherlands
| | - Pieter Wesseling
- Department of Pathology, Cancer Center Amsterdam, Brain Tumor Center Amsterdam, Amsterdam and Princes Máxima Center for Pediatric Oncology, Amsterdam UMC, VU Amsterdam, Utrecht, Netherlands
| | | | - Jos W. R. Twisk
- Department of Epidemiology and Biostatistics and Biostatistics, Amsterdam Public Health Research Institute, Amsterdam UMC, VU Amsterdam, Amsterdam, Netherlands
| | - Thomas Würdinger
- Department of Neurosurgery, Amsterdam UMC, VU Amsterdam, Amsterdam, Netherlands
| | - David Noske
- Department of Neurosurgery, Amsterdam UMC, VU Amsterdam, Amsterdam, Netherlands
| | - Yvette van Kooyk
- Department of Molecular Cell Biology and Immunology, Amsterdam Infection and Immunity Institute, Cancer Center Amsterdam, Amsterdam UMC, VU Amsterdam, Amsterdam, Netherlands
| | - Juan J. Garcia-Vallejo
- Department of Molecular Cell Biology and Immunology, Amsterdam Infection and Immunity Institute, Cancer Center Amsterdam, Amsterdam UMC, VU Amsterdam, Amsterdam, Netherlands
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3
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Yabo YA, Moreno-Sanchez PM, Pires-Afonso Y, Kaoma T, Nosirov B, Scafidi A, Ermini L, Lipsa A, Oudin A, Kyriakis D, Grzyb K, Poovathingal SK, Poli A, Muller A, Toth R, Klink B, Berchem G, Berthold C, Hertel F, Mittelbronn M, Heiland DH, Skupin A, Nazarov PV, Niclou SP, Michelucci A, Golebiewska A. Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.05.531162. [PMID: 36945572 PMCID: PMC10028830 DOI: 10.1101/2023.03.05.531162] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Background A major contributing factor to glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive environment, where GBM-associated myeloid cells, including resident microglia and peripheral monocyte-derived macrophages, play critical pro-tumoral roles. However, it is unclear whether recruited myeloid cells are phenotypically and functionally identical in GBM patients and whether this heterogeneity is recapitulated in patient-derived orthotopic xenografts (PDOXs). A thorough understanding of the GBM ecosystem and its recapitulation in preclinical models is currently missing, leading to inaccurate results and failures of clinical trials. Methods Here, we report systematic characterization of the tumor microenvironment (TME) in GBM PDOXs and patient tumors at the single-cell and spatial levels. We applied single-cell RNA-sequencing, spatial transcriptomics, multicolor flow cytometry, immunohistochemistry and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM PDOXs representing different tumor phenotypes were compared to glioma mouse GL261 syngeneic model and patient tumors. Results We show that GBM tumor cells reciprocally interact with host cells to create a GBM patient-specific TME in PDOXs. We detected the most prominent transcriptomic adaptations in myeloid cells, with brain-resident microglia representing the main population in the cellular tumor, while peripheral-derived myeloid cells infiltrated the brain at sites of blood-brain barrier disruption. More specifically, we show that GBM-educated microglia undergo transition to diverse phenotypic states across distinct GBM landscapes and tumor niches. GBM-educated microglia subsets display phagocytic and dendritic cell-like gene expression programs. Additionally, we found novel microglial states expressing cell cycle programs, astrocytic or endothelial markers. Lastly, we show that temozolomide treatment leads to transcriptomic plasticity and altered crosstalk between GBM tumor cells and adjacent TME components. Conclusions Our data provide novel insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumors. We show the key role of microglial phenotypic states in supporting GBM tumor growth and response to treatment. Our data place PDOXs as relevant models to assess the functionality of the TME and changes in the GBM ecosystem upon treatment.
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Affiliation(s)
- Yahaya A Yabo
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1526 Luxembourg, Luxembourg
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367 Belvaux, Luxembourg
| | - Pilar M Moreno-Sanchez
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1526 Luxembourg, Luxembourg
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367 Belvaux, Luxembourg
| | - Yolanda Pires-Afonso
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367 Belvaux, Luxembourg
- Neuro-Immunology Group, Department of Cancer Research, Luxembourg Institute of Health, L-1526 Luxembourg, Luxembourg
| | - Tony Kaoma
- Multiomics Data Science, Department of Cancer Research, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg
| | - Bakhtiyor Nosirov
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1526 Luxembourg, Luxembourg
- Multiomics Data Science, Department of Cancer Research, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg
| | - Andrea Scafidi
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367 Belvaux, Luxembourg
- Neuro-Immunology Group, Department of Cancer Research, Luxembourg Institute of Health, L-1526 Luxembourg, Luxembourg
| | - Luca Ermini
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1526 Luxembourg, Luxembourg
| | - Anuja Lipsa
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1526 Luxembourg, Luxembourg
| | - Anaïs Oudin
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1526 Luxembourg, Luxembourg
| | - Dimitrios Kyriakis
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367 Belvaux, Luxembourg
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, L-4362 Esch-sur-Alzette, Luxembourg
| | - Kamil Grzyb
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, L-4362 Esch-sur-Alzette, Luxembourg
| | - Suresh K Poovathingal
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, L-4362 Esch-sur-Alzette, Luxembourg
- Single Cell Analytics & Microfluidics Core, Vlaams Instituut voor Biotechnologie-KU Leuven, 3000 Leuven, Belgium
| | - Aurélie Poli
- Neuro-Immunology Group, Department of Cancer Research, Luxembourg Institute of Health, L-1526 Luxembourg, Luxembourg
| | - Arnaud Muller
- Multiomics Data Science, Department of Cancer Research, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg
| | - Reka Toth
- Multiomics Data Science, Department of Cancer Research, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg
| | - Barbara Klink
- National Center of Genetics, Laboratoire National de Santé, L-3555 Dudelange, Luxembourg
- Department of Cancer Research, Luxembourg Institute of Health, L-1526 Luxembourg, Luxembourg
- German Cancer Consortium (DKTK), 01307 Dresden, Germany; Core Unit for Molecular Tumor Diagnostics (CMTD), National Center for Tumor Diseases (NCT), 01307 Dresden, Germany; German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Institute for Clinical Genetics, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, 01307 Dresden, Germany
| | - Guy Berchem
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367 Belvaux, Luxembourg
- Department of Cancer Research, Luxembourg Institute of Health, L-1526 Luxembourg, Luxembourg
- Centre Hospitalier Luxembourg, 1210 Luxembourg, Luxembourg
| | | | - Frank Hertel
- Centre Hospitalier Luxembourg, 1210 Luxembourg, Luxembourg
| | - Michel Mittelbronn
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367 Belvaux, Luxembourg
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, L-4362 Esch-sur-Alzette, Luxembourg
- Department of Cancer Research, Luxembourg Institute of Health, L-1526 Luxembourg, Luxembourg
- Luxembourg Center of Neuropathology (LCNP), Luxembourg
- National Center of Pathology (NCP), Laboratoire National de Santé, L-3555 Dudelange, Luxembourg
| | - Dieter H Heiland
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany
- Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany
- Department of Neurological Surgery, Lou and Jean Malnati Brain Tumor Institute, Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Alexander Skupin
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, L-4362 Esch-sur-Alzette, Luxembourg
- Department of Physics and Material Science, University Luxembourg, L-4367 Belvaux, Luxembourg
- Department of Neuroscience, University of California San Diego, La Jolla, CA 92093, USA
| | - Petr V Nazarov
- Multiomics Data Science, Department of Cancer Research, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg
| | - Simone P Niclou
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1526 Luxembourg, Luxembourg
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine (FSTM), University of Luxembourg, L-4367 Belvaux, Luxembourg
| | - Alessandro Michelucci
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1526 Luxembourg, Luxembourg
- Neuro-Immunology Group, Department of Cancer Research, Luxembourg Institute of Health, L-1526 Luxembourg, Luxembourg
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, L-4362 Esch-sur-Alzette, Luxembourg
| | - Anna Golebiewska
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health (LIH), L-1526 Luxembourg, Luxembourg
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Martins S, António N, Rodrigues R, Carvalheiro T, Tomaz C, Gonçalves L, Paiva A. Role of monocytes and dendritic cells in cardiac reverse remodelling after cardiac resynchronization therapy. BMC Cardiovasc Disord 2023; 23:558. [PMID: 37968611 PMCID: PMC10652525 DOI: 10.1186/s12872-023-03574-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 10/22/2023] [Indexed: 11/17/2023] Open
Abstract
BACKGROUND AND AIMS Monocytes and dendritic cells (DC) are both key inflammatory cells, with recognized effects on cardiac repair. However, there are distinct subsets of monocytes with potential for beneficial or detrimental effects on heart failure (HF) pathogenesis. The connection between reverse cardiac remodelling, the potential anti-inflammatory effect of cardiac resynchronization therapy (CRT) and monocytes and DC homeostasis in HF is far from being understood. We hypothesized that monocytes and DC play an important role in cardiac reverse remodelling and CRT response. Therefore, we aimed to assess the potential role of baseline peripheral levels of blood monocytes and DC subsets and their phenotypic and functional activity for CRT response, in HF patients. As a secondary objective, we aimed to evaluate the impact of CRT on peripheral blood monocytes and DC subsets, by comparing baseline and post CRT circulating levels and phenotypic and functional activity. METHODS Forty-one patients with advanced HF scheduled for CRT were included in this study. The quantification and phenotypic determination of classical (cMo), intermediate (iMo) and non-classical monocytes (ncMo), as well as of myeloid (mDC) and plasmacytoid DC (pDC) were performed by flow cytometry in a FACSCanto™II (BD) flow cytometer. The functional characterization of total monocytes and mDC was performed by flow cytometry in a FACSCalibur flow cytometer, after in vitro stimulation with lipopolysaccharide from Escherichia coli plus interferon (IFN)-γ, in the presence of Brefeldina A. Comparisons between the control and the patient group, and between responders and non-responders to CRT were performed. RESULTS Compared to the control group, HF population presented a significantly lower frequency of pDC at baseline and a higher proportion of monocytes and mDC producing IL-6 and IL-1β, both before and 6-months after CRT (T6). There was a remarkable decrease of cMo and an increase of iMo after CRT, only in responders. The responder group also presented higher ncMo values at T6 compared to the non-responder group. Both responders and non-responders presented a decrease in the expression of CD86 in all monocyte and DC populations after CRT. Moreover, in non-responders, the increased frequency of IL-6-producing DC persisted after CRT. CONCLUSION Our study provides new knowledge about the possible contribution of pDC and monocytes subsets to cardiac reverse remodelling and response to CRT. Additionally, CRT is associated with a reduction on CD86 expression by monocytes and DC subsets and in their potential to produce pro-inflammatory cytokines, contributing, at least in part, for the well described anti-inflammatory effects of CRT in HF patients.
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Affiliation(s)
- Sílvia Martins
- Health Sciences Research Centre, University of Beira Interior (CICS-UBI), 6200-506, Covilhã, Portugal
- Instituto Politécnico de Castelo Branco, ESALD-Dr. Lopes Dias Health School, Ciências Biomédicas Laboratoriais, Castelo Branco, Portugal
- Department of Clinical Pathology, Centro Hospitalar Universitário Cova da Beira, Quinta Do Alvito, 6200-251, Covilhã, Portugal
- University of Coimbra, Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, Coimbra, Portugal
| | - Natália António
- Cardiology Department, Centro Hospitalar E Universitário de Coimbra, Coimbra, Portugal
- Institute of Pharmacology and Experimental Therapeutics/iCBR, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Ricardo Rodrigues
- Department of Clinical Pathology, Centro Hospitalar Universitário Cova da Beira, Quinta Do Alvito, 6200-251, Covilhã, Portugal
| | - Tiago Carvalheiro
- Centro Do Sangue E da Transplantação de Coimbra, Instituto Português Do Sangue E da Transplantação, Coimbra, Portugal
| | - Cândida Tomaz
- Health Sciences Research Centre, University of Beira Interior (CICS-UBI), 6200-506, Covilhã, Portugal
- Chemistry Department, University of Beira Interior, Covilhã, Portugal
| | - Lino Gonçalves
- Cardiology Department, Centro Hospitalar E Universitário de Coimbra, Coimbra, Portugal
- Institute of Pharmacology and Experimental Therapeutics/iCBR, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Artur Paiva
- University of Coimbra, Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, Coimbra, Portugal.
- Department of Clinical Pathology, Flow Cytometry Unit, Centro Hospitalar E Universitário de Coimbra, Coimbra, Portugal.
- Instituto Politécnico de Coimbra, ESTESC-Coimbra Health School, Ciências Biomédicas Laboratoriais, Coimbra, Portugal.
- Unidade Funcional de Citometria de Fluxo, Centro Hospitalar E Universitário de Coimbra, Praceta Mota Pinto, 3000-075, Coimbra, Portugal.
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Yu L, Yu Z, Sun L, Zhu L, Geng D. A brain tumor computer-aided diagnosis method with automatic lesion segmentation and ensemble decision strategy. Front Med (Lausanne) 2023; 10:1232496. [PMID: 37841015 PMCID: PMC10576559 DOI: 10.3389/fmed.2023.1232496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 09/08/2023] [Indexed: 10/17/2023] Open
Abstract
Objectives Gliomas and brain metastases (Mets) are the most common brain malignancies. The treatment strategy and clinical prognosis of patients are different, requiring accurate diagnosis of tumor types. However, the traditional radiomics diagnostic pipeline requires manual annotation and lacks integrated methods for segmentation and classification. To improve the diagnosis process, a gliomas and Mets computer-aided diagnosis method with automatic lesion segmentation and ensemble decision strategy on multi-center datasets was proposed. Methods Overall, 1,022 high-grade gliomas and 775 Mets patients' preoperative MR images were adopted in the study, including contrast-enhanced T1-weighted (T1-CE) and T2-fluid attenuated inversion recovery (T2-flair) sequences from three hospitals. Two segmentation models trained on the gliomas and Mets datasets, respectively, were used to automatically segment tumors. Multiple radiomics features were extracted after automatic segmentation. Several machine learning classifiers were used to measure the impact of feature selection methods. A weight soft voting (RSV) model and ensemble decision strategy based on prior knowledge (EDPK) were introduced in the radiomics pipeline. Accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC) were used to evaluate the classification performance. Results The proposed pipeline improved the diagnosis of gliomas and Mets with ACC reaching 0.8950 and AUC reaching 0.9585 after automatic lesion segmentation, which was higher than those of the traditional radiomics pipeline (ACC:0.8850, AUC:0.9450). Conclusion The proposed model accurately classified gliomas and Mets patients using MRI radiomics. The novel pipeline showed great potential in diagnosing gliomas and Mets with high generalizability and interpretability.
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Affiliation(s)
- Liheng Yu
- Academy for Engineering and Technology, Fudan University, Shanghai, China
- Center for Shanghai Intelligent Imaging for Critical Brain Diseases Engineering and Technology Research, Huashan Hospital, Fudan University, Shanghai, China
- Greater BayArea Institute of Precision Medicine (Guangzhou), Fudan University, Nansha District, Guangzhou, Guangdong, China
| | - Zekuan Yu
- Academy for Engineering and Technology, Fudan University, Shanghai, China
- Center for Shanghai Intelligent Imaging for Critical Brain Diseases Engineering and Technology Research, Huashan Hospital, Fudan University, Shanghai, China
- Greater BayArea Institute of Precision Medicine (Guangzhou), Fudan University, Nansha District, Guangzhou, Guangdong, China
| | - Linlin Sun
- Department of Radiology, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Li Zhu
- Department of Radiology, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Daoying Geng
- Academy for Engineering and Technology, Fudan University, Shanghai, China
- Center for Shanghai Intelligent Imaging for Critical Brain Diseases Engineering and Technology Research, Huashan Hospital, Fudan University, Shanghai, China
- Greater BayArea Institute of Precision Medicine (Guangzhou), Fudan University, Nansha District, Guangzhou, Guangdong, China
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
- Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China
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6
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Krop J, van der Meeren LE, van der Hoorn MLP, Ijsselsteijn ME, Dijkstra KL, Kapsenberg H, van der Keur C, Cornish EF, Nikkels PGJ, Koning F, Claas FHJ, Heidt S, Eikmans M, Bos M. Identification of a unique intervillous cellular signature in chronic histiocytic intervillositis. Placenta 2023; 139:34-42. [PMID: 37300938 DOI: 10.1016/j.placenta.2023.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 04/15/2023] [Accepted: 05/13/2023] [Indexed: 06/12/2023]
Abstract
INTRODUCTION Chronic histiocytic intervillositis (CHI) is a rare histopathological lesion in the placenta characterized by an infiltrate of CD68+ cells in the intervillous space. CHI is associated with adverse pregnancy outcomes such as miscarriage, fetal growth restriction, and (late) intrauterine fetal death. The adverse pregnancy outcomes and a variable recurrence rate of 25-100% underline its clinical relevance. The pathophysiologic mechanism of CHI is unclear, but it appears to be immunologically driven. The aim of this study was to obtain a better understanding of the phenotype of the cellular infiltrate in CHI. METHOD We used imaging mass cytometry to achieve in-depth visualization of the intervillous maternal immune cells and investigated their spatial orientation in situ in relation to the fetal syncytiotrophoblast. RESULTS We found three phenotypically distinct CD68+HLA-DR+CD38+ cell clusters that were unique for CHI. Additionally, syncytiotrophoblast cells in the vicinity of these CD68+HLA-DR+CD38+ cells showed decreased expression of the immunosuppressive enzyme CD39. DISCUSSION The current results provide novel insight into the phenotype of CD68+ cells in CHI. The identification of unique CD68+ cell clusters will allow more detailed analysis of their function and could result in novel therapeutic targets for CHI.
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Affiliation(s)
- Juliette Krop
- Department of Immunology, Leiden University Medical Centre, Leiden, the Netherlands
| | - Lotte E van der Meeren
- Department of Pathology, Leiden University Medical Centre, Leiden, the Netherlands; Department of Pathology, Erasmus Medical Center, Rotterdam, the Netherlands
| | | | | | - Kyra L Dijkstra
- Department of Pathology, Leiden University Medical Centre, Leiden, the Netherlands
| | - H Kapsenberg
- Department of Immunology, Leiden University Medical Centre, Leiden, the Netherlands
| | - C van der Keur
- Department of Immunology, Leiden University Medical Centre, Leiden, the Netherlands
| | - Emily F Cornish
- Elizabeth Garrett Anderson Institute for Women's Health, University College London, London, UK
| | - Peter G J Nikkels
- Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Frits Koning
- Department of Immunology, Leiden University Medical Centre, Leiden, the Netherlands
| | - Frans H J Claas
- Department of Immunology, Leiden University Medical Centre, Leiden, the Netherlands
| | - Sebastiaan Heidt
- Department of Immunology, Leiden University Medical Centre, Leiden, the Netherlands
| | - Michael Eikmans
- Department of Immunology, Leiden University Medical Centre, Leiden, the Netherlands.
| | - Manon Bos
- Department of Pathology, Leiden University Medical Centre, Leiden, the Netherlands; Department of Gynecology and Obstetrics, Leiden University Medical Centre, Leiden, the Netherlands
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7
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Pro- vs. Anti-Inflammatory Features of Monocyte Subsets in Glioma Patients. Int J Mol Sci 2023; 24:ijms24031879. [PMID: 36768201 PMCID: PMC9915868 DOI: 10.3390/ijms24031879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 01/12/2023] [Accepted: 01/14/2023] [Indexed: 01/19/2023] Open
Abstract
Monocytes constitute a heterogenous group of antigen-presenting cells that can be subdivided based on CD14, CD16 and SLAN expression. This division reflects the functional diversity of cells that may play different roles in a variety of pathologies including gliomas. In the current study, the three monocyte subpopulations: classical (CD14+ CD16+ SLAN-), intermediate (CD14dim CD16+ SLAN-) and non-classical (CD14low/- CD16+ SLAN+) in glioma patients' peripheral blood were analysed with flow cytometry. The immune checkpoint molecule (PD-1, PD-L1, SIRPalpha, TIM-3) expression along with pro- and anti-inflammatory cytokines (TNF, IL-12, TGF-beta, IL-10) were assessed. The significant overproduction of anti-inflammatory cytokines by intermediate monocytes was observed. Additionally, SLAN-positive cells overexpressed IL-12 and TNF when compared to the other two groups of monocytes. In conclusion, these results show the presence of different profiles of glioma patient monocytes depending on CD14, CD16 and SLAN expression. The bifold function of monocyte subpopulations might be an additional obstacle to the effectiveness of possible immunotherapies.
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8
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van der Pan K, de Bruin-Versteeg S, Damasceno D, Hernández-Delgado A, van der Sluijs-Gelling AJ, van den Bossche WBL, de Laat IF, Díez P, Naber BAE, Diks AM, Berkowska MA, de Mooij B, Groenland RJ, de Bie FJ, Khatri I, Kassem S, de Jager AL, Louis A, Almeida J, van Gaans-van den Brink JAM, Barkoff AM, He Q, Ferwerda G, Versteegen P, Berbers GAM, Orfao A, van Dongen JJM, Teodosio C. Development of a standardized and validated flow cytometry approach for monitoring of innate myeloid immune cells in human blood. Front Immunol 2022; 13:935879. [PMID: 36189252 PMCID: PMC9519388 DOI: 10.3389/fimmu.2022.935879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 08/18/2022] [Indexed: 11/13/2022] Open
Abstract
Innate myeloid cell (IMC) populations form an essential part of innate immunity. Flow cytometric (FCM) monitoring of IMCs in peripheral blood (PB) has great clinical potential for disease monitoring due to their role in maintenance of tissue homeostasis and ability to sense micro-environmental changes, such as inflammatory processes and tissue damage. However, the lack of standardized and validated approaches has hampered broad clinical implementation. For accurate identification and separation of IMC populations, 62 antibodies against 44 different proteins were evaluated. In multiple rounds of EuroFlow-based design-testing-evaluation-redesign, finally 16 antibodies were selected for their non-redundancy and separation power. Accordingly, two antibody combinations were designed for fast, sensitive, and reproducible FCM monitoring of IMC populations in PB in clinical settings (11-color; 13 antibodies) and translational research (14-color; 16 antibodies). Performance of pre-analytical and analytical variables among different instruments, together with optimized post-analytical data analysis and reference values were assessed. Overall, 265 blood samples were used for design and validation of the antibody combinations and in vitro functional assays, as well as for assessing the impact of sample preparation procedures and conditions. The two (11- and 14-color) antibody combinations allowed for robust and sensitive detection of 19 and 23 IMC populations, respectively. Highly reproducible identification and enumeration of IMC populations was achieved, independently of anticoagulant, type of FCM instrument and center, particularly when database/software-guided automated (vs. manual “expert-based”) gating was used. Whereas no significant changes were observed in identification of IMC populations for up to 24h delayed sample processing, a significant impact was observed in their absolute counts after >12h delay. Therefore, accurate identification and quantitation of IMC populations requires sample processing on the same day. Significantly different counts were observed in PB for multiple IMC populations according to age and sex. Consequently, PB samples from 116 healthy donors (8-69 years) were used for collecting age and sex related reference values for all IMC populations. In summary, the two antibody combinations and FCM approach allow for rapid, standardized, automated and reproducible identification of 19 and 23 IMC populations in PB, suited for monitoring of innate immune responses in clinical and translational research settings.
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Affiliation(s)
- Kyra van der Pan
- Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
| | | | - Daniela Damasceno
- Translational and Clinical Research Program, Cancer Research Center (IBMCC; University of Salamanca - CSIC), Cytometry Service, NUCLEUS, Department of Medicine, University of Salamanca (Universidad de Salamanca, and Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
| | - Alejandro Hernández-Delgado
- Translational and Clinical Research Program, Cancer Research Center (IBMCC; University of Salamanca - CSIC), Cytometry Service, NUCLEUS, Department of Medicine, University of Salamanca (Universidad de Salamanca, and Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
| | | | - Wouter B. L. van den Bossche
- Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
- Department of Immunology, Department of Neurosurgery, Brain Tumor Center, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Inge F. de Laat
- Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
| | - Paula Díez
- Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
| | | | - Annieck M. Diks
- Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
| | | | - Bas de Mooij
- Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
| | - Rick J. Groenland
- Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
| | - Fenna J. de Bie
- Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
| | - Indu Khatri
- Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
| | - Sara Kassem
- Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
| | - Anniek L. de Jager
- Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
| | - Alesha Louis
- Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
| | - Julia Almeida
- Translational and Clinical Research Program, Cancer Research Center (IBMCC; University of Salamanca - CSIC), Cytometry Service, NUCLEUS, Department of Medicine, University of Salamanca (Universidad de Salamanca, and Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
| | | | - Alex-Mikael Barkoff
- Institute of Biomedicine, Research Center for Infections and Immunity, University of Turku (UTU), Turku, Finland
| | - Qiushui He
- Institute of Biomedicine, Research Center for Infections and Immunity, University of Turku (UTU), Turku, Finland
| | - Gerben Ferwerda
- Section of Paediatric Infectious Diseases, Laboratory of Medical Immunology, Radboud Institute for Molecular Life Sciences, Nijmegen, Netherlands
| | - Pauline Versteegen
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Guy A. M. Berbers
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Alberto Orfao
- Translational and Clinical Research Program, Cancer Research Center (IBMCC; University of Salamanca - CSIC), Cytometry Service, NUCLEUS, Department of Medicine, University of Salamanca (Universidad de Salamanca, and Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
| | - Jacques J. M. van Dongen
- Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
- Translational and Clinical Research Program, Cancer Research Center (IBMCC; University of Salamanca - CSIC), Cytometry Service, NUCLEUS, Department of Medicine, University of Salamanca (Universidad de Salamanca, and Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
- *Correspondence: Jacques J. M. van Dongen,
| | - Cristina Teodosio
- Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
- Translational and Clinical Research Program, Cancer Research Center (IBMCC; University of Salamanca - CSIC), Cytometry Service, NUCLEUS, Department of Medicine, University of Salamanca (Universidad de Salamanca, and Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
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9
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Reinhardt JW, Breuer CK. Fibrocytes: A Critical Review and Practical Guide. Front Immunol 2021; 12:784401. [PMID: 34975874 PMCID: PMC8718395 DOI: 10.3389/fimmu.2021.784401] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 11/30/2021] [Indexed: 01/18/2023] Open
Abstract
Fibrocytes are hematopoietic-derived cells that directly contribute to tissue fibrosis by producing collagen following injury, during disease, and with aging. The lack of a fibrocyte-specific marker has led to the use of multiple strategies for identifying these cells in vivo. This review will detail how past studies were performed, report their findings, and discuss their strengths and limitations. The motivation is to identify opportunities for further investigation and promote the adoption of best practices during future study design.
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Affiliation(s)
- James W. Reinhardt
- Center for Regenerative Medicine, Abigail Wexner Research Institute, Nationwide Children’s Hospital, Columbus, OH, United States
| | - Christopher K. Breuer
- Center for Regenerative Medicine, Abigail Wexner Research Institute, Nationwide Children’s Hospital, Columbus, OH, United States
- Department of Surgery, The Ohio State University Wexner Medical Center, Columbus, OH, United States
- Department of Surgery, Nationwide Children’s Hospital, Columbus, OH, United States
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10
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van Asperen JV, Fedorushkova DM, Robe PAJT, Hol E. Investigation of glial fibrillary acidic protein (GFAP) in body fluids as a potential biomarker for glioma: a systematic review and meta-analysis. Biomarkers 2021; 27:1-12. [PMID: 34844498 DOI: 10.1080/1354750x.2021.2006313] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
INTRODUCTION Liquid biopsies are promising diagnostic tools for glioma. In this quantitative systematic review, we investigate whether the detection of intermediate filaments (IF) in body fluids can be used as a tool for glioma diagnosis and prognosis. MATERIALS AND METHODS We included all studies in which IF-levels were determined in patients with glioma and healthy controls. Of the 28 identified eligible studies, 12 focused on levels of GFAP in serum (sGFAP) and were included for metadata analysis. RESULTS In all studies combined, 62.7% of all grade IV patients had detectable levels of sGFAP compared to 12.7% of healthy controls. sGFAP did not surpass the limit of detection in lower grade patients or healthy controls, but sGFAP was significantly elevated in grade IV glioma (0.12 ng/mL (0.06 - 0.18), P < 0.001) and showed an average median difference of 0.15 ng/mL (0.04 - 0.25, P < 0.01) compared to healthy controls. sGFAP levels were linked to tumour volume, but not to patient outcome. CONCLUSION The presence of sGFAP is indicative of grade IV glioma, but additional studies are necessary to fully determine the usefulness of GFAP in body fluids as a tool for grade IV glioma diagnosis and follow-up.
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Affiliation(s)
- Jessy Van van Asperen
- Department of Translational Neurosciences, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Daria M Fedorushkova
- Department of Translational Neurosciences, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Pierre A J T Robe
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands.,University Hospital Liege, Liege, Belgium
| | - Elly Hol
- Department of Translational Neurosciences, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
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11
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Hofman L, Lawler SE, Lamfers MLM. The Multifaceted Role of Macrophages in Oncolytic Virotherapy. Viruses 2021; 13:v13081570. [PMID: 34452439 PMCID: PMC8402704 DOI: 10.3390/v13081570] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 07/27/2021] [Accepted: 07/30/2021] [Indexed: 12/16/2022] Open
Abstract
One of the cancer hallmarks is immune evasion mediated by the tumour microenvironment (TME). Oncolytic virotherapy is a form of immunotherapy based on the application of oncolytic viruses (OVs) that selectively replicate in and induce the death of tumour cells. Virotherapy confers reciprocal interaction with the host’s immune system. The aim of this review is to explore the role of macrophage-mediated responses in oncolytic virotherapy efficacy. The approach was to study current scientific literature in this field in order to give a comprehensive overview of the interactions of OVs and macrophages and their effects on the TME. The innate immune system has a central influence on the TME; tumour-associated macrophages (TAMs) generally have immunosuppressive, tumour-supportive properties. In the context of oncolytic virotherapy, macrophages were initially thought to predominantly contribute to anti-viral responses, impeding viral spread. However, macrophages have now also been found to mediate transport of OV particles and, after TME infiltration, to be subjected to a phenotypic shift that renders them pro-inflammatory and tumour-suppressive. These TAMs can present tumour antigens leading to a systemic, durable, adaptive anti-tumour immune response. After phagocytosis, they can recirculate carrying tissue-derived proteins, which potentially enables the monitoring of OV replication in the TME. Their role in therapeutic efficacy is therefore multifaceted, but based on research applying relevant, immunocompetent tumour models, macrophages are considered to have a central function in anti-cancer activity. These novel insights hold important clinical implications. When optimised, oncolytic virotherapy, mediating multifactorial inhibition of cancer immune evasion, could contribute to improved patient survival.
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Affiliation(s)
- Laura Hofman
- Department of Neurosurgery, Brain Tumor Center, Erasmus Medical Center, Wytemaweg 80, 3015 CN Rotterdam, The Netherlands;
| | - Sean E. Lawler
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, 75 Francis St., Boston, MA 02115, USA;
| | - Martine L. M. Lamfers
- Department of Neurosurgery, Brain Tumor Center, Erasmus Medical Center, Wytemaweg 80, 3015 CN Rotterdam, The Netherlands;
- Correspondence: ; Tel.: +31-010-703-5993
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12
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Damasceno D, Almeida J, Teodosio C, Sanoja-Flores L, Mayado A, Pérez-Pons A, Puig N, Arana P, Paiva B, Solano F, Romero A, Matarraz S, van den Bossche WBL, Flores-Montero J, Durie B, van Dongen JJM, Orfao A. Monocyte Subsets and Serum Inflammatory and Bone-Associated Markers in Monoclonal Gammopathy of Undetermined Significance and Multiple Myeloma. Cancers (Basel) 2021; 13:cancers13061454. [PMID: 33810169 PMCID: PMC8004952 DOI: 10.3390/cancers13061454] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 03/16/2021] [Accepted: 03/18/2021] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Monocyte/macrophages have been shown to be altered in monoclonal gammopathy of undetermined significance (MGUS), smoldering (SMM) and active multiple myeloma (MM), with an impact on the disruption of the homeostasis of the normal bone marrow (BM) microenvironment. METHODS We investigated the distribution of different subsets of monocytes (Mo) in blood and BM of newly-diagnosed untreated MGUS (n = 23), SMM (n = 14) and MM (n = 99) patients vs. healthy donors (HD; n = 107), in parallel to a large panel of cytokines and bone-associated serum biomarkers. RESULTS Our results showed normal production of monocyte precursors and classical Mo (cMo) in MGUS, while decreased in SMM and MM (p ≤ 0.02), in association with lower blood counts of recently-produced CD62L+ cMo in SMM (p = 0.004) and of all subsets of (CD62L+, CD62L- and FcεRI+) cMo in MM (p ≤ 0.02). In contrast, intermediate and end-stage non-classical Mo were increased in BM of MGUS (p ≤ 0.03), SMM (p ≤ 0.03) and MM (p ≤ 0.002), while normal (MGUS and SMM) or decreased (MM; p = 0.01) in blood. In parallel, increased serum levels of interleukin (IL)1β were observed in MGUS (p = 0.007) and SMM (p = 0.01), higher concentrations of serum IL8 were found in SMM (p = 0.01) and MM (p = 0.002), and higher serum IL6 (p = 0.002), RANKL (p = 0.01) and bone alkaline phosphatase (BALP) levels (p = 0.01) with decreased counts of FcεRI+ cMo, were restricted to MM presenting with osteolytic lesions. This translated into three distinct immune/bone profiles: (1) normal (typical of HD and most MGUS cases); (2) senescent-like (increased IL1β and/or IL8, found in a minority of MGUS, most SMM and few MM cases with no bone lesions); and (3) pro-inflammatory-high serum IL6, RANKL and BALP with significantly (p = 0.01) decreased blood counts of immunomodulatory FcεRI+ cMo-, typical of MM presenting with bone lesions. CONCLUSIONS These results provide new insight into the pathogenesis of plasma cell neoplasms and the potential role of FcεRI+ cMo in normal bone homeostasis.
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Affiliation(s)
- Daniela Damasceno
- Translational and Clinical Research Program, Cancer Research Center (IBMCC, USAL-CSIC), Cytometry Service (NUCLEUS) and Department of Medicine, University of Salamanca and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain; (D.D.); (J.A.); (A.M.); (A.P.-P.); (S.M.); (J.F.-M.)
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC) (CB16/12/00400), Instituto Carlos III, 28029 Madrid, Spain; (L.S.-F.); (N.P.); (B.P.)
| | - Julia Almeida
- Translational and Clinical Research Program, Cancer Research Center (IBMCC, USAL-CSIC), Cytometry Service (NUCLEUS) and Department of Medicine, University of Salamanca and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain; (D.D.); (J.A.); (A.M.); (A.P.-P.); (S.M.); (J.F.-M.)
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC) (CB16/12/00400), Instituto Carlos III, 28029 Madrid, Spain; (L.S.-F.); (N.P.); (B.P.)
| | - Cristina Teodosio
- Leiden University Medical Center, Department of Immunology, 2333 ZA Leiden, The Netherlands; (C.T.); (W.B.L.v.d.B.); (J.J.M.v.D.)
| | - Luzalba Sanoja-Flores
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC) (CB16/12/00400), Instituto Carlos III, 28029 Madrid, Spain; (L.S.-F.); (N.P.); (B.P.)
- Institute of Biomedicine of Seville, Department of Hematology, University Hospital Virgen del Rocío of the Consejo Superior de Investigaciones Científicas (CSIC), University of Seville, 41013 Seville, Spain
| | - Andrea Mayado
- Translational and Clinical Research Program, Cancer Research Center (IBMCC, USAL-CSIC), Cytometry Service (NUCLEUS) and Department of Medicine, University of Salamanca and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain; (D.D.); (J.A.); (A.M.); (A.P.-P.); (S.M.); (J.F.-M.)
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC) (CB16/12/00400), Instituto Carlos III, 28029 Madrid, Spain; (L.S.-F.); (N.P.); (B.P.)
| | - Alba Pérez-Pons
- Translational and Clinical Research Program, Cancer Research Center (IBMCC, USAL-CSIC), Cytometry Service (NUCLEUS) and Department of Medicine, University of Salamanca and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain; (D.D.); (J.A.); (A.M.); (A.P.-P.); (S.M.); (J.F.-M.)
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC) (CB16/12/00400), Instituto Carlos III, 28029 Madrid, Spain; (L.S.-F.); (N.P.); (B.P.)
| | - Noemi Puig
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC) (CB16/12/00400), Instituto Carlos III, 28029 Madrid, Spain; (L.S.-F.); (N.P.); (B.P.)
- Service of Hematology, University Hospital of Salamanca (CAUSA) and IBSAL, 37007 Salamanca, Spain
| | - Paula Arana
- Regulation of the Immune System Group, Biocruces Bizkaia Health Research Institute, Hospital Universitario Cruces, Plaza de Cruces 12, 48903 Barakaldo, Spain;
| | - Bruno Paiva
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC) (CB16/12/00400), Instituto Carlos III, 28029 Madrid, Spain; (L.S.-F.); (N.P.); (B.P.)
- Centro de Investigación Médica Aplicada (CIMA), Instituto de Investigación Sanitaria de Navarra (IDISNA), Clinica Universidad de Navarra, 31008 Pamplona, Spain
| | - Fernando Solano
- Hematology Service, Hospital Nuestra Señora del Prado, Talavera de la Reina, 45600 Toledo, Spain;
| | - Alfonso Romero
- Primary Health Care Center “Miguel Armijo”, Primary Health Care of Salamanca, Conserjería de Sanidad de Castilla y León (SACYL), 37007 Salamanca, Spain;
| | - Sergio Matarraz
- Translational and Clinical Research Program, Cancer Research Center (IBMCC, USAL-CSIC), Cytometry Service (NUCLEUS) and Department of Medicine, University of Salamanca and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain; (D.D.); (J.A.); (A.M.); (A.P.-P.); (S.M.); (J.F.-M.)
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC) (CB16/12/00400), Instituto Carlos III, 28029 Madrid, Spain; (L.S.-F.); (N.P.); (B.P.)
| | - Wouter B. L. van den Bossche
- Leiden University Medical Center, Department of Immunology, 2333 ZA Leiden, The Netherlands; (C.T.); (W.B.L.v.d.B.); (J.J.M.v.D.)
- Department of Immunology, Erasmus University Medical Center, 3015 GA Rotterdam, The Netherlands
| | - Juan Flores-Montero
- Translational and Clinical Research Program, Cancer Research Center (IBMCC, USAL-CSIC), Cytometry Service (NUCLEUS) and Department of Medicine, University of Salamanca and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain; (D.D.); (J.A.); (A.M.); (A.P.-P.); (S.M.); (J.F.-M.)
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC) (CB16/12/00400), Instituto Carlos III, 28029 Madrid, Spain; (L.S.-F.); (N.P.); (B.P.)
| | - Brian Durie
- Centro del Cáncer Cedars-Sinai Samuel Oschin, Los Angeles, CA 90048, USA;
| | - Jacques J. M. van Dongen
- Leiden University Medical Center, Department of Immunology, 2333 ZA Leiden, The Netherlands; (C.T.); (W.B.L.v.d.B.); (J.J.M.v.D.)
| | - Alberto Orfao
- Translational and Clinical Research Program, Cancer Research Center (IBMCC, USAL-CSIC), Cytometry Service (NUCLEUS) and Department of Medicine, University of Salamanca and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain; (D.D.); (J.A.); (A.M.); (A.P.-P.); (S.M.); (J.F.-M.)
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC) (CB16/12/00400), Instituto Carlos III, 28029 Madrid, Spain; (L.S.-F.); (N.P.); (B.P.)
- Correspondence:
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