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Balog JÁ, Horti-Oravecz K, Kövesdi D, Bozsik A, Papp J, Butz H, Patócs A, Szebeni GJ, Grolmusz VK. Peripheral immunophenotyping reveals lymphocyte stimulation in healthy women living with hereditary breast and ovarian cancer syndrome. iScience 2024; 27:109882. [PMID: 38799565 PMCID: PMC11126817 DOI: 10.1016/j.isci.2024.109882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 03/11/2024] [Accepted: 04/30/2024] [Indexed: 05/29/2024] Open
Abstract
Germline pathogenic variants in BRCA1 and BRCA2 (gpath(BRCA1/2)) represent genetic susceptibility for hereditary breast and ovarian cancer syndrome. Tumor-immune interactions are key contributors to breast cancer pathogenesis. Although earlier studies confirmed pro-tumorigenic immunological alterations in breast cancer patients, data are lacking in healthy carriers of gpath(BRCA1/2). Peripheral blood mononuclear cells of 66 women with or without germline predisposition or breast cancer were studied with a mass cytometry panel that identified 4 immune subpopulations of altered frequencies between healthy controls and healthy gpath(BRCA1) carriers, while no difference was observed in healthy gpath(BRCA2) carriers compared to controls. Moreover, 3 (one IgD-CD27+CD95+ B cell subpopulation and two CD45RA-CCR7+CD38+ CD4+ T cell subpopulations) out of these 4 subpopulations were also elevated in triple-negative breast cancer patients compared to controls. Our results reveal an activated peripheral immune phenotype in healthy carriers of gpath(BRCA1) that needs to be further elucidated to be leveraged in risk-reducing strategies.
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Affiliation(s)
- József Ágoston Balog
- Institute of Genetics, Laboratory of Functional Genomics, HUN-REN Biological Research Center, 6726 Szeged, Hungary
- Core Facility, HUN-REN Biological Research Center, 6726 Szeged, Hungary
| | - Klaudia Horti-Oravecz
- Department of Molecular Genetics and the National Tumorbiology Laboratory, National Institute of Oncology, Comprehensive Cancer Center, 1122 Budapest, Hungary
- Semmelweis University, Doctoral School, 1085 Budapest, Hungary
| | - Dorottya Kövesdi
- Department of Immunology, Eötvös Loránd University, 1117 Budapest, Hungary
| | - Anikó Bozsik
- Department of Molecular Genetics and the National Tumorbiology Laboratory, National Institute of Oncology, Comprehensive Cancer Center, 1122 Budapest, Hungary
- HUN-REN-SE Hereditary Cancers Research Group, Hungarian Research Network – Semmelweis University, 1122 Budapest, Hungary
| | - Janos Papp
- Department of Molecular Genetics and the National Tumorbiology Laboratory, National Institute of Oncology, Comprehensive Cancer Center, 1122 Budapest, Hungary
- HUN-REN-SE Hereditary Cancers Research Group, Hungarian Research Network – Semmelweis University, 1122 Budapest, Hungary
| | - Henriett Butz
- Department of Molecular Genetics and the National Tumorbiology Laboratory, National Institute of Oncology, Comprehensive Cancer Center, 1122 Budapest, Hungary
- HUN-REN-SE Hereditary Cancers Research Group, Hungarian Research Network – Semmelweis University, 1122 Budapest, Hungary
- Department of Oncology Biobank, National Institute of Oncology, Comprehensive Cancer Center, 1122 Budapest, Hungary
- Department of Laboratory Medicine, Semmelweis University, 1089 Budapest, Hungary
| | - Attila Patócs
- Department of Molecular Genetics and the National Tumorbiology Laboratory, National Institute of Oncology, Comprehensive Cancer Center, 1122 Budapest, Hungary
- HUN-REN-SE Hereditary Cancers Research Group, Hungarian Research Network – Semmelweis University, 1122 Budapest, Hungary
- Department of Laboratory Medicine, Semmelweis University, 1089 Budapest, Hungary
| | - Gábor János Szebeni
- Institute of Genetics, Laboratory of Functional Genomics, HUN-REN Biological Research Center, 6726 Szeged, Hungary
- Core Facility, HUN-REN Biological Research Center, 6726 Szeged, Hungary
- Department of Internal Medicine, Hematology Centre, Faculty of Medicine University of Szeged, 6725 Szeged, Hungary
| | - Vince Kornél Grolmusz
- Department of Molecular Genetics and the National Tumorbiology Laboratory, National Institute of Oncology, Comprehensive Cancer Center, 1122 Budapest, Hungary
- HUN-REN-SE Hereditary Cancers Research Group, Hungarian Research Network – Semmelweis University, 1122 Budapest, Hungary
- Department of Laboratory Medicine, Semmelweis University, 1089 Budapest, Hungary
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Kayvanjoo AH, Splichalova I, Bejarano DA, Huang H, Mauel K, Makdissi N, Heider D, Tew HM, Balzer NR, Greto E, Osei-Sarpong C, Baßler K, Schultze JL, Uderhardt S, Kiermaier E, Beyer M, Schlitzer A, Mass E. Fetal liver macrophages contribute to the hematopoietic stem cell niche by controlling granulopoiesis. eLife 2024; 13:e86493. [PMID: 38526524 PMCID: PMC11006421 DOI: 10.7554/elife.86493] [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: 01/29/2023] [Accepted: 03/23/2024] [Indexed: 03/26/2024] Open
Abstract
During embryogenesis, the fetal liver becomes the main hematopoietic organ, where stem and progenitor cells as well as immature and mature immune cells form an intricate cellular network. Hematopoietic stem cells (HSCs) reside in a specialized niche, which is essential for their proliferation and differentiation. However, the cellular and molecular determinants contributing to this fetal HSC niche remain largely unknown. Macrophages are the first differentiated hematopoietic cells found in the developing liver, where they are important for fetal erythropoiesis by promoting erythrocyte maturation and phagocytosing expelled nuclei. Yet, whether macrophages play a role in fetal hematopoiesis beyond serving as a niche for maturing erythroblasts remains elusive. Here, we investigate the heterogeneity of macrophage populations in the murine fetal liver to define their specific roles during hematopoiesis. Using a single-cell omics approach combined with spatial proteomics and genetic fate-mapping models, we found that fetal liver macrophages cluster into distinct yolk sac-derived subpopulations and that long-term HSCs are interacting preferentially with one of the macrophage subpopulations. Fetal livers lacking macrophages show a delay in erythropoiesis and have an increased number of granulocytes, which can be attributed to transcriptional reprogramming and altered differentiation potential of long-term HSCs. Together, our data provide a detailed map of fetal liver macrophage subpopulations and implicate macrophages as part of the fetal HSC niche.
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Affiliation(s)
- Amir Hossein Kayvanjoo
- Developmental Biology of the Immune System, Life & Medical Sciences (LIMES) Institute, University of BonnBonnGermany
| | - Iva Splichalova
- Developmental Biology of the Immune System, Life & Medical Sciences (LIMES) Institute, University of BonnBonnGermany
| | - David Alejandro Bejarano
- Quantitative Systems Biology, Life & Medical Sciences (LIMES) Institute, University of BonnBonnGermany
| | - Hao Huang
- Developmental Biology of the Immune System, Life & Medical Sciences (LIMES) Institute, University of BonnBonnGermany
| | - Katharina Mauel
- Developmental Biology of the Immune System, Life & Medical Sciences (LIMES) Institute, University of BonnBonnGermany
| | - Nikola Makdissi
- Developmental Biology of the Immune System, Life & Medical Sciences (LIMES) Institute, University of BonnBonnGermany
| | - David Heider
- Developmental Biology of the Immune System, Life & Medical Sciences (LIMES) Institute, University of BonnBonnGermany
| | - Hui Ming Tew
- Developmental Biology of the Immune System, Life & Medical Sciences (LIMES) Institute, University of BonnBonnGermany
| | - Nora Reka Balzer
- Developmental Biology of the Immune System, Life & Medical Sciences (LIMES) Institute, University of BonnBonnGermany
| | - Eric Greto
- Department of Internal Medicine 3-Rheumatology and Immunology, Deutsches Zentrum für Immuntherapie (DZI) and FAU Profile Center Immunomedicine (FAU I-MED), Friedrich Alexander University Erlangen-Nuremberg and Universitätsklinikum ErlangenErlangenGermany
- Exploratory Research Unit, Optical Imaging Centre ErlangenErlangenGermany
| | - Collins Osei-Sarpong
- Immunogenomics & Neurodegeneration, Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE)BonnGermany
| | - Kevin Baßler
- Genomics & Immunoregulation, LIMES Institute, University of BonnBonnGermany
| | - Joachim L Schultze
- Genomics & Immunoregulation, LIMES Institute, University of BonnBonnGermany
- Systems Medicine, Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE)BonnGermany
- PRECISE Platform for Single Cell Genomics and Epigenomics, DZNE and University of BonnBonnGermany
| | - Stefan Uderhardt
- Department of Internal Medicine 3-Rheumatology and Immunology, Deutsches Zentrum für Immuntherapie (DZI) and FAU Profile Center Immunomedicine (FAU I-MED), Friedrich Alexander University Erlangen-Nuremberg and Universitätsklinikum ErlangenErlangenGermany
- Exploratory Research Unit, Optical Imaging Centre ErlangenErlangenGermany
| | - Eva Kiermaier
- Immune and Tumor Biology, Life & Medical Sciences (LIMES) Institute, University of BonnBonnGermany
| | - Marc Beyer
- Immunogenomics & Neurodegeneration, Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE)BonnGermany
- Systems Medicine, Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE)BonnGermany
- PRECISE Platform for Single Cell Genomics and Epigenomics, DZNE and University of BonnBonnGermany
| | - Andreas Schlitzer
- Quantitative Systems Biology, Life & Medical Sciences (LIMES) Institute, University of BonnBonnGermany
| | - Elvira Mass
- Developmental Biology of the Immune System, Life & Medical Sciences (LIMES) Institute, University of BonnBonnGermany
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3
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Zhang J, Li J, Lin L. Statistical and machine learning methods for immunoprofiling based on single-cell data. Hum Vaccin Immunother 2023:2234792. [PMID: 37485833 PMCID: PMC10373621 DOI: 10.1080/21645515.2023.2234792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 06/30/2023] [Accepted: 07/04/2023] [Indexed: 07/25/2023] Open
Abstract
Immunoprofiling has become a crucial tool for understanding the complex interactions between the immune system and diseases or interventions, such as therapies and vaccinations. Immune response biomarkers are critical for understanding those relationships and potentially developing personalized intervention strategies. Single-cell data have emerged as a promising source for identifying immune response biomarkers. In this review, we discuss the current state-of-the-art methods for immunoprofiling, including those for reducing the dimensionality of high-dimensional single-cell data and methods for clustering, classification, and prediction. We also draw attention to recent developments in data integration.
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Affiliation(s)
- Jingxuan Zhang
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - Jia Li
- Department of Statistics, Pennsylvania State University, University Park, PA, USA
| | - Lin Lin
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
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Bechi Genzano C, Bezzecchi E, Carnovale D, Mandelli A, Morotti E, Castorani V, Favalli V, Stabilini A, Insalaco V, Ragogna F, Codazzi V, Scotti GM, Del Rosso S, Mazzi BA, De Pellegrin M, Giustina A, Piemonti L, Bosi E, Battaglia M, Morelli MJ, Bonfanti R, Petrelli A. Combined unsupervised and semi-automated supervised analysis of flow cytometry data reveals cellular fingerprint associated with newly diagnosed pediatric type 1 diabetes. Front Immunol 2022; 13:1026416. [PMID: 36389771 PMCID: PMC9647173 DOI: 10.3389/fimmu.2022.1026416] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 10/11/2022] [Indexed: 11/03/2023] Open
Abstract
An unbiased and replicable profiling of type 1 diabetes (T1D)-specific circulating immunome at disease onset has yet to be identified due to experimental and patient selection limitations. Multicolor flow cytometry was performed on whole blood from a pediatric cohort of 107 patients with new-onset T1D, 85 relatives of T1D patients with 0-1 islet autoantibodies (pre-T1D_LR), 58 patients with celiac disease or autoimmune thyroiditis (CD_THY) and 76 healthy controls (HC). Unsupervised clustering of flow cytometry data, validated by a semi-automated gating strategy, confirmed previous findings showing selective increase of naïve CD4 T cells and plasmacytoid DCs, and revealed a decrease in CD56brightNK cells in T1D. Furthermore, a non-selective decrease of CD3+CD56+ regulatory T cells was observed in T1D. The frequency of naïve CD4 T cells at disease onset was associated with partial remission, while it was found unaltered in the pre-symptomatic stages of the disease. Thanks to a broad cohort of pediatric individuals and the implementation of unbiased approaches for the analysis of flow cytometry data, here we determined the circulating immune fingerprint of newly diagnosed pediatric T1D and provide a reference dataset to be exploited for validation or discovery purposes to unravel the pathogenesis of T1D.
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Affiliation(s)
| | - Eugenia Bezzecchi
- Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy
- Center for Omics Sciences, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Debora Carnovale
- Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Elisa Morotti
- Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy
- Department of Pediatrics, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Valeria Castorani
- Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Valeria Favalli
- Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy
- Department of Pediatrics, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Angela Stabilini
- Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Vittoria Insalaco
- Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Francesca Ragogna
- Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Valentina Codazzi
- Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Stefania Del Rosso
- Laboratory Medicine, Autoimmunity Section, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Benedetta Allegra Mazzi
- Immuno-Hematology and Transfusion Medicine (ITMS), IRCCS Ospedale San Raffaele, Milan, Italy
| | - Maurizio De Pellegrin
- Pediatric Orthopedic and Traumatology Unit, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Andrea Giustina
- Institute of Endocrine and Metabolic Sciences, IRCCS Ospedale San Raffaele, Milan, Italy
- Università Vita-Salute San Raffaele, Milan, Italy
| | - Lorenzo Piemonti
- Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy
- Università Vita-Salute San Raffaele, Milan, Italy
| | - Emanuele Bosi
- Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy
- Department of General Medicine, Diabetes and Endocrinology, IRCCS Ospedale San Raffaele, Milan, Italy
- Università Vita-Salute San Raffaele, Milan, Italy
| | - Manuela Battaglia
- Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Marco J. Morelli
- Center for Omics Sciences, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Riccardo Bonfanti
- Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy
- Department of Pediatrics, IRCCS Ospedale San Raffaele, Milan, Italy
- Università Vita-Salute San Raffaele, Milan, Italy
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