1
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Larbi A. From Genesis to Old Age: Exploring the Immune System One Cell at a Time with Flow Cytometry. Biomedicines 2024; 12:1469. [PMID: 39062042 PMCID: PMC11275137 DOI: 10.3390/biomedicines12071469] [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: 05/12/2024] [Revised: 06/21/2024] [Accepted: 06/28/2024] [Indexed: 07/28/2024] Open
Abstract
The immune system is a highly complex and tightly regulated system that plays a crucial role in protecting the body against external threats, such as pathogens, and internal abnormalities, like cancer cells. It undergoes development during fetal stages and continuously learns from each encounter with pathogens, allowing it to develop immunological memory and provide a wide range of immune protection. Over time, after numerous encounters and years of functioning, the immune system can begin to show signs of erosion, which is commonly named immunosenescence. In this review, we aim to explore how the immune system responds to initial encounters with antigens and how it handles persistent stimulations throughout a person's lifetime. Our understanding of the immune system has greatly benefited from advanced technologies like flow cytometry. In this context, we will discuss the valuable contribution of flow cytometry in enhancing our knowledge of the immune system behavior in aging, with a specific focus on T-cells. Moreover, we will expand our discussion to the flow cytometry-based assessment of extracellular vesicles, a recently discovered communication channel in biology, and their implications for immune system functioning.
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Affiliation(s)
- Anis Larbi
- Medical and Scientific Affairs, Beckman Coulter Life Sciences, 22 Avenue des Nations, 93420 Villepinte, France;
- Department of Medicine, Division of Geriatrics, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada
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2
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Chea M, Rigolot L, Canali A, Vergez F. Minimal Residual Disease in Acute Myeloid Leukemia: Old and New Concepts. Int J Mol Sci 2024; 25:2150. [PMID: 38396825 PMCID: PMC10889505 DOI: 10.3390/ijms25042150] [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: 12/31/2023] [Revised: 02/01/2024] [Accepted: 02/08/2024] [Indexed: 02/25/2024] Open
Abstract
Minimal residual disease (MRD) is of major importance in onco-hematology, particularly in acute myeloid leukemia (AML). MRD measures the amount of leukemia cells remaining in a patient after treatment, and is an essential tool for disease monitoring, relapse prognosis, and guiding treatment decisions. Patients with a negative MRD tend to have superior disease-free and overall survival rates. Considerable effort has been made to standardize MRD practices. A variety of techniques, including flow cytometry and molecular methods, are used to assess MRD, each with distinct strengths and weaknesses. MRD is recognized not only as a predictive biomarker, but also as a prognostic tool and marker of treatment efficacy. Expected advances in MRD assessment encompass molecular techniques such as NGS and digital PCR, as well as optimization strategies such as unsupervised flow cytometry analysis and leukemic stem cell monitoring. At present, there is no perfect method for measuring MRD, and significant advances are expected in the future to fully integrate MRD assessment into the management of AML patients.
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Affiliation(s)
- Mathias Chea
- Laboratoire d’Hématologie Biologique, Institut Universitaire du Cancer de Toulouse Oncopole, Centre Hospitalier Universitaire de Toulouse, 31059 Toulouse, France; (M.C.); (L.R.); (A.C.)
| | - Lucie Rigolot
- Laboratoire d’Hématologie Biologique, Institut Universitaire du Cancer de Toulouse Oncopole, Centre Hospitalier Universitaire de Toulouse, 31059 Toulouse, France; (M.C.); (L.R.); (A.C.)
- School of Medicine, Université Toulouse III Paul Sabatier, 31062 Toulouse, France
| | - Alban Canali
- Laboratoire d’Hématologie Biologique, Institut Universitaire du Cancer de Toulouse Oncopole, Centre Hospitalier Universitaire de Toulouse, 31059 Toulouse, France; (M.C.); (L.R.); (A.C.)
- School of Medicine, Université Toulouse III Paul Sabatier, 31062 Toulouse, France
| | - Francois Vergez
- Laboratoire d’Hématologie Biologique, Institut Universitaire du Cancer de Toulouse Oncopole, Centre Hospitalier Universitaire de Toulouse, 31059 Toulouse, France; (M.C.); (L.R.); (A.C.)
- School of Medicine, Université Toulouse III Paul Sabatier, 31062 Toulouse, France
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3
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Proto-Siqueira R, Lanes S, Bortolini JF, Zouain-Figueiredo G, Barros-Nascimento E, Marinato AF. Remote Onco-Hematology Laboratory Using Reflex Testing for Increased Accessibility and Reduced Costs in a Developing Country: A Proof of Concept. J Appl Lab Med 2023; 8:1190-1192. [PMID: 37738660 DOI: 10.1093/jalm/jfad056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 07/13/2023] [Indexed: 09/24/2023]
Affiliation(s)
| | - Silvania Lanes
- Flow Diagnósticos, Laboratório e Diagnósticos de Alta Complexidade, São Paulo, Brazil
| | - Joana F Bortolini
- Hospital Infantil Nossa Senhora da Glória (HINSG), Serviço de Pediatria e de Oncohematologia, Vitória, Brazil
| | - Glaucia Zouain-Figueiredo
- Hospital Infantil Nossa Senhora da Glória (HINSG), Serviço de Pediatria e de Oncohematologia, Vitória, Brazil
| | | | - André F Marinato
- Flow Diagnósticos, Laboratório e Diagnósticos de Alta Complexidade, São Paulo, Brazil
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4
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Tettero JM, Dakappagari N, Heidinga ME, Oussoren-Brockhoff Y, Hanekamp D, Pahuja A, Burns K, Kaur P, Alfonso Z, van der Velden VHJ, Te Marvelde JG, Hobo W, Slomp J, Bachas C, Kelder A, Nguyen K, Cloos J. Analytical assay validation for acute myeloid leukemia measurable residual disease assessment by multiparametric flow cytometry. CYTOMETRY. PART B, CLINICAL CYTOMETRY 2023; 104:426-439. [PMID: 37766649 DOI: 10.1002/cyto.b.22144] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 08/30/2023] [Accepted: 09/07/2023] [Indexed: 09/29/2023]
Abstract
BACKGROUND Measurable residual disease (MRD) assessed by multiparametric flow cytometry (MFC) has gained importance in clinical decision-making for acute myeloid leukemia (AML) patients. However, complying with the recent In Vitro Diagnostic Regulations (IVDR) in Europe and Food and Drug Administration (FDA) guidance in the United States requires rigorous validation prior to their use in investigational clinical trials and diagnostics. Validating AML MRD-MFC assays poses challenges due to the unique underlying disease biology and paucity of patient specimens. In this study, we describe an experimental framework for validation that meets regulatory expectations. METHODS Our validation efforts focused on evaluating assay accuracy, analytical specificity, analytical and functional sensitivity (limit of blank (LoB), detection (LLoD) and quantitation (LLoQ)), precision, linearity, sample/reagent stability and establishing the assay background frequencies. RESULTS Correlation between different MFC methods was highly significant (r = 0.99 for %blasts and r = 0.93 for %LAIPs). The analysis of LAIP specificity accurately discriminated from negative control cells. The assay demonstrated a LoB of 0.03, LLoD of 0.04, and LLoQ of 0.1%. Precision experiments yielded highly reproducible results (Coefficient of Variation <20%). Stability experiments demonstrated reliable measurement of samples up to 96 h from collection. Furthermore, the reference range of LAIP frequencies in non-AML patients was below 0.1%, ranging from 0.0% to 0.04%. CONCLUSION In this manuscript, we present the validation of an AML MFC-MRD assay using BM/PB patient specimens, adhering to best practices. Our approach is expected to assist other laboratories in expediting their validation activities to fulfill recent health authority guidelines.
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Affiliation(s)
- Jesse M Tettero
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands
| | | | - Maaike E Heidinga
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands
| | - Yvonne Oussoren-Brockhoff
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands
| | - Diana Hanekamp
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands
- Department of Hematology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Anil Pahuja
- Navigate BioPharma (a Novartis Subsidiary), Carlsbad, California, USA
| | - Kerri Burns
- Navigate BioPharma (a Novartis Subsidiary), Carlsbad, California, USA
| | - Pavinder Kaur
- Navigate BioPharma (a Novartis Subsidiary), Carlsbad, California, USA
| | - Zeni Alfonso
- Navigate BioPharma (a Novartis Subsidiary), Carlsbad, California, USA
| | | | - Jeroen G Te Marvelde
- Department of Immunology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Willemijn Hobo
- Department of Laboratory Medicine-Laboratory of Hematology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jennichjen Slomp
- Department of Clinical Chemistry, Medisch Spectrum Twente/Medlon, Enschede, The Netherlands
| | - Costa Bachas
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands
| | - Angele Kelder
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands
| | - Kevin Nguyen
- Navigate BioPharma (a Novartis Subsidiary), Carlsbad, California, USA
| | - Jacqueline Cloos
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands
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5
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Johansson U, Rolf N, Futhee N, Stewart A. Erythroid side scatter: A parameter that improves diagnostic accuracy of flow cytometry myelodysplastic syndrome scoring. CYTOMETRY. PART B, CLINICAL CYTOMETRY 2023; 104:151-161. [PMID: 35388621 DOI: 10.1002/cyto.b.22067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 02/23/2022] [Accepted: 03/22/2022] [Indexed: 11/08/2022]
Abstract
BACKGROUND Flow cytometry immunophenotyping (FCM) is a benchmark test for integrated diagnosis of myelodysplastic syndromes (MDS). Our department's FCM-MDS-score follows international guidelines and additionally includes the maturing erythroid (mEry) side scatter (SSC)/lymphocyte SSC ratio (mErySSCr), often increased in MDS patients. A recent exploratory computational flow analysis study highlighted mErySSC as the top feature for separating MDS from non-MDS. Thus, we sought to systematically evaluate the diagnostic accuracy of mErySSCr in conventional diagnostic FCM as used currently in-house. METHODS Historical MDS (n = 93), chronic myelomonocytic leukemia (CMML; n = 27) and non-neoplastic cytopenia (n = 57) cohorts were created. Differences between these cohorts and LG-MDS entities were mapped and the mErySSCr cut-off was refined. Prospective bone marrows (n = 213) received for marrow failure work-up were used to determine the sensitivity and specificity of mErySSCr, both as a sole parameter and as a component of the MDS-score. RESULTS Low-grade (LG)-MDS mErySSCr differed more prominently from controls (p = <0.0001) than high-grade (HG)-MDS (p = 0.024). CMML and controls had a similar mErySSCr. As sole parameter, mErySSCr specificity was 91.1% (n = 112 non-MDS diagnoses) and sensitivity was 36% for LG-MDS (n = 36) and 25% for new HG-MDS diagnoses (n = 16). The specificity of the MDS-score was similar if mErySSCr was omitted (81.3% with and 82.1% without). The MDS-score sensitivity for new HG-MDS diagnoses and CMML (n = 17) was 100%, and was not affected by mErySSCr. The score sensitivity for LG-MDS however, dropped from 86.1% to 72.2% when mErySSCr was excluded. CONCLUSION mErySSCr increases the diagnostic accuracy of flow-based MDS scoring in our setting, particularly for LG-MDS.
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Affiliation(s)
- Ulrika Johansson
- SI-HMDS, University Hospitals and Weston NHS Foundation Trust, Bristol, UK
| | - Nina Rolf
- University of British Columbia, BC Children's Hospital Research Institute, Michael Cuccione Childhood Cancer Research Program, Vancouver, British Columbia, Canada
| | - Natasha Futhee
- SI-HMDS, University Hospitals and Weston NHS Foundation Trust, Bristol, UK
| | - Andrew Stewart
- SI-HMDS, University Hospitals and Weston NHS Foundation Trust, Bristol, UK
- Department of Haematology, University Hospitals and Weston NHS Foundation Trust, Bristol, UK
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6
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van der Velden VHJ, Preijers F, Johansson U, Westers TM, Dunlop A, Porwit A, Béné MC, Valent P, Te Marvelde J, Wagner-Ballon O, Oelschlaegel U, Saft L, Kordasti S, Ireland R, Cremers E, Alhan C, Duetz C, Hobo W, Chapuis N, Fontenay M, Bettelheim P, Eidenshink-Brodersen L, Font P, Loken MR, Matarraz S, Ogata K, Orfao A, Psarra K, Subirá D, Wells DA, Della Porta MG, Burbury K, Bellos F, Weiß E, Kern W, van de Loosdrecht A. Flow cytometric analysis of myelodysplasia: Pre-analytical and technical issues-Recommendations from the European LeukemiaNet. CYTOMETRY. PART B, CLINICAL CYTOMETRY 2023; 104:15-26. [PMID: 34894176 PMCID: PMC10078694 DOI: 10.1002/cyto.b.22046] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 11/18/2021] [Accepted: 11/29/2021] [Indexed: 01/19/2023]
Abstract
BACKGROUND Flow cytometry (FCM) aids the diagnosis and prognostic stratification of patients with suspected or confirmed myelodysplastic syndrome (MDS). Over the past few years, significant progress has been made in the FCM field concerning technical issues (including software and hardware) and pre-analytical procedures. METHODS Recommendations are made based on the data and expert discussions generated from 13 yearly meetings of the European LeukemiaNet international MDS Flow working group. RESULTS We report here on the experiences and recommendations concerning (1) the optimal methods of sample processing and handling, (2) antibody panels and fluorochromes, and (3) current hardware technologies. CONCLUSIONS These recommendations will support and facilitate the appropriate application of FCM assays in the diagnostic workup of MDS patients. Further standardization and harmonization will be required to integrate FCM in MDS diagnostic evaluations in daily practice.
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Affiliation(s)
- Vincent H J van der Velden
- Laboratory Medical Immunology, Department of Immunology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Frank Preijers
- Department of Laboratory Medicine - Laboratory for Hematology, Radboudumc, Nijmegen, The Netherlands
| | - Ulrika Johansson
- Laboratory Medicine, SI-HMDS, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Theresia M Westers
- Department of Hematology, Amsterdam UMC, location VU University Medical Center, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Alan Dunlop
- Department of Haemato-Oncology, Royal Marsden Hospital, Sutton, Surrey, UK
| | - Anna Porwit
- Department of Clinical Sciences, Division of Oncology And Pathology, Faculty of Medicine, Lund University, Lund, Sweden
| | - Marie C Béné
- Hematology Biology, Nantes University Hospital and CRCINA, Nantes, France
| | - Peter Valent
- Department of Internal Medicine I, Division of Hematology & Hemostaseology, Medical University of Vienna, Vienna, Austria
- Ludwig Boltzmann Institute for Hematology and Oncology, Medical University of Vienna, Vienna, Austria
| | - Jeroen Te Marvelde
- Laboratory Medical Immunology, Department of Immunology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Orianne Wagner-Ballon
- Department of Hematology and Immunology; and Université Paris-Est Créteil, Assistance Publique-Hôpitaux de Paris, University Hospital Henri Mondor, Inserm U955, Créteil, France
| | - Uta Oelschlaegel
- Department of Internal Medicine, University Hospital Carl-Gustav-Carus, Dresden, TU, Germany
| | - Leonie Saft
- Department of Clinical Pathology and Oncology, Karolinska University Hospital and Institute, Solna, Stockholm, Sweden
| | - Sharham Kordasti
- Comprehensive Cancer Centre, King's College London and Hematology Department, Guy's Hospital, London, UK
| | - Robin Ireland
- Comprehensive Cancer Centre, King's College London and Hematology Department, Guy's Hospital, London, UK
| | - Eline Cremers
- Department of Internal Medicine, Division of Hematology, Maastricht University Medical Center, AZ, Maastricht, The Netherlands
| | - Canan Alhan
- Department of Hematology, Amsterdam UMC, location VU University Medical Center, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Carolien Duetz
- Department of Hematology, Amsterdam UMC, location VU University Medical Center, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Willemijn Hobo
- Department of Laboratory Medicine - Laboratory for Hematology, Radboudumc, Nijmegen, The Netherlands
| | - Nicolas Chapuis
- Assistance Publique-Hôpitaux de Paris. Centre-Université de Paris, Cochin Hospital, Laboratory of Hematology and Université de Paris, Institut Cochin, INSERM U1016, CNRS UMR8104, Paris, France
| | - Michaela Fontenay
- Assistance Publique-Hôpitaux de Paris. Centre-Université de Paris, Cochin Hospital, Laboratory of Hematology and Université de Paris, Institut Cochin, INSERM U1016, CNRS UMR8104, Paris, France
| | - Peter Bettelheim
- Department of Internal Medicine, Ordensklinikum Linz Barmherzige Schwestern - Elisabethinen, Linz, Austria
| | | | - Patricia Font
- Department of Hematology, Hospital General Universitario Gregorio Marañon-IiSGM, Madrid, Spain
| | | | - Sergio Matarraz
- Cancer Research Center (IBMCC, USAL-CSIC), Department of Medicine and Cytometry Service, University of Salamanca, Institute for Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC), Instituto Carlos III, Salamanca, Spain
| | - Kiyoyuki Ogata
- Metropolitan Research and Treatment Centre for Blood Disorders (MRTC Japan), Tokyo, Japan
| | - Alberto Orfao
- Cancer Research Center (IBMCC, USAL-CSIC), Department of Medicine and Cytometry Service, University of Salamanca, Institute for Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC), Instituto Carlos III, Salamanca, Spain
| | - Katherina Psarra
- Immunology Histocompatibility Department, Evangelismos Hospital, Athens, Greece
| | - Dolores Subirá
- Flow Cytometry Unit. Department of Hematology, Hospital Universitario de Guadalajara, Guadalajara, Spain
| | | | - Matteo G Della Porta
- IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy & Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy
| | - Kate Burbury
- Department of Haematology, Peter MacCallum Cancer Centre, University of Melbourne, Melbourne, Australia
| | | | | | | | - Arjan van de Loosdrecht
- Department of Hematology, Amsterdam UMC, location VU University Medical Center, Cancer Center Amsterdam, Amsterdam, The Netherlands
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Röhnert MA, Kramer M, Schadt J, Ensel P, Thiede C, Krause SW, Bücklein V, Hoffmann J, Jaramillo S, Schlenk RF, Röllig C, Bornhäuser M, McCarthy N, Freeman S, Oelschlägel U, von Bonin M. Reproducible measurable residual disease detection by multiparametric flow cytometry in acute myeloid leukemia. Leukemia 2022; 36:2208-2217. [PMID: 35851154 PMCID: PMC9417981 DOI: 10.1038/s41375-022-01647-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 06/24/2022] [Accepted: 07/01/2022] [Indexed: 11/08/2022]
Abstract
Measurable residual disease (MRD) detected by multiparametric flow cytometry (MFC) is associated with unfavorable outcome in patients with AML. A simple, broadly applicable eight-color panel was implemented and analyzed utilizing a hierarchical gating strategy with fixed gates to develop a clear-cut LAIP-based DfN approach. In total, 32 subpopulations with aberrant phenotypes with/without expression of markers of immaturity were monitored in 246 AML patients after completion of induction chemotherapy. Reference values were established utilizing 90 leukemia-free controls. Overall, 73% of patients achieved a response by cytomorphology. In responders, the overall survival was shorter for MRDpos patients (HR 3.8, p = 0.006). Overall survival of MRDneg non-responders was comparable to MRDneg responders. The inter-rater-reliability for MRD detection was high with a Krippendorffs α of 0.860. The mean time requirement for MRD analyses at follow-up was very short with 04:31 minutes. The proposed one-tube MFC approach for detection of MRD allows a high level of standardization leading to a promising inter-observer-reliability with a fast turnover. MRD defined by this strategy provides relevant prognostic information and establishes aberrancies outside of cell populations with markers of immaturity as an independent risk feature. Our results imply that this strategy may provide the base for multicentric immunophenotypic MRD assessment.
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Affiliation(s)
- Maximilian A Röhnert
- Department of Medicine I, University Hospital Carl Gustav Carus TU Dresden, Dresden, Germany.
| | - Michael Kramer
- Department of Medicine I, University Hospital Carl Gustav Carus TU Dresden, Dresden, Germany
| | - Jonas Schadt
- Department of Medicine I, University Hospital Carl Gustav Carus TU Dresden, Dresden, Germany
| | - Philipp Ensel
- Department of Medicine I, University Hospital Carl Gustav Carus TU Dresden, Dresden, Germany
| | - Christian Thiede
- Department of Medicine I, University Hospital Carl Gustav Carus TU Dresden, Dresden, Germany
- AgenDix GmbH, Dresden, Germany
| | - Stefan W Krause
- Department of Medicine 5, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Veit Bücklein
- Department of Medicine III, University Hospital LMU Munich, Munich, Germany
- Laboratory for Translational Cancer Immunology, Gene Center, LMU Munich, Munich, Germany
| | - Jörg Hoffmann
- Department of Internal Medicine and Hematology, Oncology and Immunology, Philipps University Marburg and University Hospital Giessen and Marburg, Marburg, Germany
| | - Sonia Jaramillo
- Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany
| | - Richard F Schlenk
- Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany
- NCT Trial Center, National Center of Tumor Diseases, German Cancer Research Center, Heidelberg, Germany
| | - Christoph Röllig
- Department of Medicine I, University Hospital Carl Gustav Carus TU Dresden, Dresden, Germany
| | - Martin Bornhäuser
- Department of Medicine I, University Hospital Carl Gustav Carus TU Dresden, Dresden, Germany
- National Center of Tumor Diseases, Dresden, Germany
| | - Nicholas McCarthy
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK
| | - Sylvie Freeman
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK
| | - Uta Oelschlägel
- Department of Medicine I, University Hospital Carl Gustav Carus TU Dresden, Dresden, Germany
| | - Malte von Bonin
- Department of Medicine I, University Hospital Carl Gustav Carus TU Dresden, Dresden, Germany
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8
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Civelekoglu O, Wang N, Arifuzzman A, Boya M, Sarioglu AF. Automated lightless cytometry on a microchip with adaptive immunomagnetic manipulation. Biosens Bioelectron 2022; 203:114014. [DOI: 10.1016/j.bios.2022.114014] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 12/13/2021] [Accepted: 01/15/2022] [Indexed: 01/08/2023]
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9
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Technical Aspects of Flow Cytometry-based Measurable Residual Disease Quantification in Acute Myeloid Leukemia: Experience of the European LeukemiaNet MRD Working Party. Hemasphere 2022; 6:e676. [PMID: 34964040 PMCID: PMC8701786 DOI: 10.1097/hs9.0000000000000676] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 11/23/2021] [Indexed: 12/12/2022] Open
Abstract
Measurable residual disease (MRD) quantified by multiparameter flow cytometry (MFC) is a strong and independent prognostic factor in acute myeloid leukemia (AML). However, several technical factors may affect the final read-out of the assay. Experts from the MRD Working Party of the European LeukemiaNet evaluated which aspects are crucial for accurate MFC-MRD measurement. Here, we report on the agreement, obtained via a combination of a cross-sectional questionnaire, live discussions, and a Delphi poll. The recommendations consist of several key issues from bone marrow sampling to final laboratory reporting to ensure quality and reproducibility of results. Furthermore, the experiences were tested by comparing two 8-color MRD panels in multiple laboratories. The results presented here underscore the feasibility and the utility of a harmonized theoretical and practical MFC-MRD assessment and are a next step toward further harmonization.
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10
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Heuser M, Freeman SD, Ossenkoppele GJ, Buccisano F, Hourigan CS, Ngai LL, Tettero JM, Bachas C, Baer C, Béné MC, Bücklein V, Czyz A, Denys B, Dillon R, Feuring-Buske M, Guzman ML, Haferlach T, Han L, Herzig JK, Jorgensen JL, Kern W, Konopleva MY, Lacombe F, Libura M, Majchrzak A, Maurillo L, Ofran Y, Philippe J, Plesa A, Preudhomme C, Ravandi F, Roumier C, Subklewe M, Thol F, van de Loosdrecht AA, van der Reijden BA, Venditti A, Wierzbowska A, Valk PJM, Wood BL, Walter RB, Thiede C, Döhner K, Roboz GJ, Cloos J. 2021 Update on MRD in acute myeloid leukemia: a consensus document from the European LeukemiaNet MRD Working Party. Blood 2021; 138:2753-2767. [PMID: 34724563 PMCID: PMC8718623 DOI: 10.1182/blood.2021013626] [Citation(s) in RCA: 333] [Impact Index Per Article: 111.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 10/15/2021] [Indexed: 11/20/2022] Open
Abstract
Measurable residual disease (MRD) is an important biomarker in acute myeloid leukemia (AML) that is used for prognostic, predictive, monitoring, and efficacy-response assessments. The European LeukemiaNet (ELN) MRD Working Party evaluated standardization and harmonization of MRD in an ongoing manner and has updated the 2018 ELN MRD recommendations based on significant developments in the field. New and revised recommendations were established during in-person and online meetings, and a 2-stage Delphi poll was conducted to optimize consensus. All recommendations are graded by levels of evidence and agreement. Major changes include technical specifications for next-generation sequencing-based MRD testing and integrative assessments of MRD irrespective of technology. Other topics include use of MRD as a prognostic and surrogate end point for drug testing; selection of the technique, material, and appropriate time points for MRD assessment; and clinical implications of MRD assessment. In addition to technical recommendations for flow- and molecular-MRD analysis, we provide MRD thresholds and define MRD response, and detail how MRD results should be reported and combined if several techniques are used. MRD assessment in AML is complex and clinically relevant, and standardized approaches to application, interpretation, technical conduct, and reporting are of critical importance.
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Affiliation(s)
- Michael Heuser
- Department of Hematology, Hemostasis, Oncology, and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany
| | - Sylvie D Freeman
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, United Kingdom
| | - Gert J Ossenkoppele
- Department of Hematology, Amsterdam University Medical Center (UMC), Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Francesco Buccisano
- Department of Biomedicine and Prevention, Hematology, University Tor Vergata, Rome, Italy
| | - Christopher S Hourigan
- Laboratory of Myeloid Malignancy, Hematology Branch, National Heart, Lung, and Blood Institute, Bethesda, MD
| | - Lok Lam Ngai
- Department of Hematology, Amsterdam University Medical Center (UMC), Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Jesse M Tettero
- Department of Hematology, Amsterdam University Medical Center (UMC), Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Costa Bachas
- Department of Hematology, Amsterdam University Medical Center (UMC), Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | | | - Marie-Christine Béné
- Department of Hematology and Biology, Centre Hospitalier Universitaire (CHU) Nantes, Nantes, France
| | - Veit Bücklein
- Department of Medicine III, University Hospital, Ludwig Maximilian University Munich, Munich, Germany
| | - Anna Czyz
- Department of Hematology, Blood Neoplasms, and Bone Marrow Transplantation, Wrocław Medical University, Wrocław, Poland
| | - Barbara Denys
- Department of Diagnostic Sciences, Faculty of Medicine and Health Sciences, Ghent University
| | - Richard Dillon
- Department of Medical and Molecular Genetics, King's College, London, United Kingdom
| | | | - Monica L Guzman
- Department of Medicine, Division of Hematology and Oncology, Weill Cornell Medicine, New York, NY
| | | | | | - Julia K Herzig
- Department of Internal Medicine III, University Hospital of Ulm, Ulm, Germany
| | | | | | | | - Francis Lacombe
- Hematology Biology, Flow Cytometry, Bordeaux University Hospital, Pessac, France
| | | | - Agata Majchrzak
- Department of Experimental Hematology, Copernicus Memorial Hospital, Lodz, Poland
| | - Luca Maurillo
- Department of Biomedicine and Prevention, Hematology, University Tor Vergata, Rome, Italy
| | - Yishai Ofran
- Department of Hematology, Shaare Zedek Medical Center Faculty of Medicine Hebrew University, Jerusalem Israel
| | - Jan Philippe
- Department of Diagnostic Sciences, Faculty of Medicine and Health Sciences, Ghent University
| | - Adriana Plesa
- Department of Hematology Laboratory, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Lyon, France
| | | | | | | | - Marion Subklewe
- Department of Medicine III, University Hospital, Ludwig Maximilian University Munich, Munich, Germany
| | - Felicitas Thol
- Department of Hematology, Hemostasis, Oncology, and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany
| | - Arjan A van de Loosdrecht
- Department of Hematology, Amsterdam University Medical Center (UMC), Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Bert A van der Reijden
- Department of Laboratory Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Adriano Venditti
- Department of Biomedicine and Prevention, Hematology, University Tor Vergata, Rome, Italy
| | | | - Peter J M Valk
- Department of Hematology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Brent L Wood
- Department of Hematopathology, Children's Hospital Los Angeles, CA
| | - Roland B Walter
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Christian Thiede
- Department of Medicine I, University Hospital Carl Gustav Carus, Dresden, Germany; and
- AgenDix GmbH, Dresden, Germany
| | - Konstanze Döhner
- Department of Internal Medicine III, University Hospital of Ulm, Ulm, Germany
| | - Gail J Roboz
- Department of Medicine, Division of Hematology and Oncology, Weill Cornell Medicine, New York, NY
| | - Jacqueline Cloos
- Department of Hematology, Amsterdam University Medical Center (UMC), Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands
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11
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[Chinese consensus on minimal residual disease detection and interpretation of patients with acute myeloid leukemia (2021)]. ZHONGHUA XUE YE XUE ZA ZHI = ZHONGHUA XUEYEXUE ZAZHI 2021; 42:889-897. [PMID: 35045649 PMCID: PMC8763587 DOI: 10.3760/cma.j.issn.0253-2727.2021.11.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [MESH Headings] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Indexed: 12/02/2022]
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12
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Béné MC, Lacombe F, Porwit A. Unsupervised flow cytometry analysis in hematological malignancies: A new paradigm. Int J Lab Hematol 2021; 43 Suppl 1:54-64. [PMID: 34288436 DOI: 10.1111/ijlh.13548] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 03/13/2021] [Accepted: 03/28/2021] [Indexed: 01/10/2023]
Abstract
Ever since hematopoietic cells became "events" enumerated and characterized in suspension by cell counters or flow cytometers, researchers and engineers have strived to refine the acquisition and display of the electronic signals generated. A large array of solutions was then developed to identify at best the numerous cell subsets that can be delineated, notably among hematopoietic cells. As instruments became more and more stable and robust, the focus moved to analytic software. Almost concomitantly, the capacity increased to use large panels (both with mass and classical cytometry) and to apply artificial intelligence/machine learning for their analysis. The combination of these concepts raised new analytical possibilities, opening an unprecedented field of subtle exploration for many conditions, including hematopoiesis and hematological disorders. In this review, the general concepts and progress achieved in the development of new analytical approaches for exploring high-dimensional data sets at the single-cell level will be described as they appeared over the past few years. A larger and more practical part will detail the various steps that need to be mastered, both in data acquisition and in the preanalytical check of data files. Finally, a step-by-step explanation of the solution in development to combine the Bioconductor clustering algorithm FlowSOM and the popular and widely used software Kaluza® (Beckman Coulter) will be presented. The aim of this review was to point out that the day when these progresses will reach routine hematology laboratories does not seem so far away.
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Affiliation(s)
- Marie C Béné
- Hematology Biology, Nantes University Hospital, Nantes, France.,CRCINA Inserm, Nantes, France
| | - Francis Lacombe
- Hematology Biology, Cytometry Department, Bordeaux University Hospital, Bordeaux, France
| | - Anna Porwit
- Department of Clinical Sciences, Oncology and Pathology, Faculty of Medicine, Lund University, Lund, Sweden.,Department of Clinical Genetics and Pathology, Skåne University Hospital, Lund, Sweden
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13
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Hanekamp D, Tettero JM, Ossenkoppele GJ, Kelder A, Cloos J, Schuurhuis GJ. AML/Normal Progenitor Balance Instead of Total Tumor Load (MRD) Accounts for Prognostic Impact of Flowcytometric Residual Disease in AML. Cancers (Basel) 2021; 13:2597. [PMID: 34073205 PMCID: PMC8198261 DOI: 10.3390/cancers13112597] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 05/20/2021] [Accepted: 05/25/2021] [Indexed: 12/11/2022] Open
Abstract
Measurable residual disease (MRD) in AML, assessed by multicolor flow cytometry, is an important prognostic factor. Progenitors are key populations in defining MRD, and cases of MRD involving these progenitors are calculated as percentage of WBC and referred to as white blood cell MRD (WBC-MRD). Two main compartments of WBC-MRD can be defined: (1) the AML part of the total primitive/progenitor (CD34+, CD117+, CD133+) compartment (referred to as primitive marker MRD; PM-MRD) and (2) the total progenitor compartment (% of WBC, referred to as PM%), which is the main quantitative determinant of WBC-MRD. Both are related as follows: WBC-MRD = PM-MRD × PM%. We explored the relative contribution of each parameter to the prognostic impact. In the HOVON/SAKK study H102 (300 patients), based on two objectively assessed cut-off points (2.34% and 10%), PM-MRD was found to offer an independent prognostic parameter that was able to identify three patient groups with different prognoses with larger discriminative power than WBC-MRD. In line with this, the PM% parameter itself showed no prognostic impact, implying that the prognostic impact of WBC-MRD results from the PM-MRD parameter it contains. Moreover, the presence of the PM% parameter in WBC-MRD may cause WBC-MRD false positivity and WBC-MRD false negativity. For the latter, at present, it is clinically relevant that PM-MRD ≥ 10% identifies a patient sub-group with a poor prognosis that is currently classified as good prognosis MRDnegative using the European LeukemiaNet 0.1% consensus MRD cut-off value. These observations suggest that residual disease analysis using PM-MRD should be conducted.
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Affiliation(s)
- Diana Hanekamp
- Department of Hematology, Amsterdam University Medical Centers, Cancer Center VU University Medical Center, 1081 HV Amsterdam, The Netherlands; (D.H.); (J.M.T.); (G.J.O.); (A.K.); (J.C.)
- Department of Hematology, Erasmus MC, NL-3000 CA Rotterdam, The Netherlands
| | - Jesse M. Tettero
- Department of Hematology, Amsterdam University Medical Centers, Cancer Center VU University Medical Center, 1081 HV Amsterdam, The Netherlands; (D.H.); (J.M.T.); (G.J.O.); (A.K.); (J.C.)
| | - Gert J. Ossenkoppele
- Department of Hematology, Amsterdam University Medical Centers, Cancer Center VU University Medical Center, 1081 HV Amsterdam, The Netherlands; (D.H.); (J.M.T.); (G.J.O.); (A.K.); (J.C.)
| | - Angèle Kelder
- Department of Hematology, Amsterdam University Medical Centers, Cancer Center VU University Medical Center, 1081 HV Amsterdam, The Netherlands; (D.H.); (J.M.T.); (G.J.O.); (A.K.); (J.C.)
| | - Jacqueline Cloos
- Department of Hematology, Amsterdam University Medical Centers, Cancer Center VU University Medical Center, 1081 HV Amsterdam, The Netherlands; (D.H.); (J.M.T.); (G.J.O.); (A.K.); (J.C.)
| | - Gerrit Jan Schuurhuis
- Department of Hematology, Amsterdam University Medical Centers, Cancer Center VU University Medical Center, 1081 HV Amsterdam, The Netherlands; (D.H.); (J.M.T.); (G.J.O.); (A.K.); (J.C.)
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14
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Vial JP, Lechevalier N, Lacombe F, Dumas PY, Bidet A, Leguay T, Vergez F, Pigneux A, Béné MC. Unsupervised Flow Cytometry Analysis Allows for an Accurate Identification of Minimal Residual Disease Assessment in Acute Myeloid Leukemia. Cancers (Basel) 2021; 13:629. [PMID: 33562525 PMCID: PMC7914957 DOI: 10.3390/cancers13040629] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 02/01/2021] [Accepted: 02/02/2021] [Indexed: 11/16/2022] Open
Abstract
The assessment of minimal residual disease (MRD) is increasingly considered to monitor response to therapy in hematological malignancies. In acute myeloblastic leukemia (AML), molecular MRD (mMRD) is possible for about half the patients while multiparameter flow cytometry (MFC) is more broadly available. However, MFC analysis strategies are highly operator-dependent. Recently, new tools have been designed for unsupervised MFC analysis, segregating cell-clusters with the same immunophenotypic characteristics. Here, the Flow-Self-Organizing-Maps (FlowSOM) tool was applied to assess MFC-MRD in 96 bone marrow (BM) follow-up (FU) time-points from 40 AML patients with available mMRD. A reference FlowSOM display was built from 19 healthy/normal BM samples (NBM), then simultaneously compared to the patient's diagnosis and FU samples at each time-point. MRD clusters were characterized individually in terms of cell numbers and immunophenotype. This strategy disclosed subclones with varying immunophenotype within single diagnosis and FU samples including populations absent from NBM. Detectable MRD was as low as 0.09% in MFC and 0.051% for mMRD. The concordance between mMRD and MFC-MRD was 80.2%. MFC yielded 85% specificity and 69% sensitivity compared to mMRD. Unsupervised MFC is shown here to allow for an easy and robust assessment of MRD, applicable also to AML patients without molecular markers.
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Affiliation(s)
- Jean Philippe Vial
- Hematology Biology, Flow Cytometry, Bordeaux University Hospital, 33600 Pessac, France; (J.P.V.); (N.L.); (F.L.)
| | - Nicolas Lechevalier
- Hematology Biology, Flow Cytometry, Bordeaux University Hospital, 33600 Pessac, France; (J.P.V.); (N.L.); (F.L.)
| | - Francis Lacombe
- Hematology Biology, Flow Cytometry, Bordeaux University Hospital, 33600 Pessac, France; (J.P.V.); (N.L.); (F.L.)
| | - Pierre-Yves Dumas
- Service d’Hématologie Clinique et de Thérapie Cellulaire, Bordeaux University Hospital, 33600 Pessac, France; (P.-Y.D.); (T.L.); (A.P.)
| | - Audrey Bidet
- Hematology Biology, Molecular Hematology, Bordeaux University Hospital, 33600 Pessac, France;
| | - Thibaut Leguay
- Service d’Hématologie Clinique et de Thérapie Cellulaire, Bordeaux University Hospital, 33600 Pessac, France; (P.-Y.D.); (T.L.); (A.P.)
| | - François Vergez
- Hematology Biology, IUCT Oncopôle, Toulouse University Hospital, 31000 Toulouse, France;
| | - Arnaud Pigneux
- Service d’Hématologie Clinique et de Thérapie Cellulaire, Bordeaux University Hospital, 33600 Pessac, France; (P.-Y.D.); (T.L.); (A.P.)
| | - Marie C. Béné
- Hematology Biology, Nantes University Hospital, 44000 Nantes, France
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15
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Definition of Erythroid Differentiation Subsets in Normal Human Bone Marrow Using FlowSOM Unsupervised Cluster Analysis of Flow Cytometry Data. Hemasphere 2020; 5:e512. [PMID: 33364551 PMCID: PMC7755522 DOI: 10.1097/hs9.0000000000000512] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Accepted: 10/09/2020] [Indexed: 11/26/2022] Open
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16
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Gupta M, Jafari K, Rajab A, Wei C, Mazur J, Tierens A, Hyjek E, Musani R, Porwit A. Radar plots facilitate differential diagnosis of acute promyelocytic leukemia and NPM1+ acute myeloid leukemia by flow cytometry. CYTOMETRY PART B-CLINICAL CYTOMETRY 2020; 100:409-420. [PMID: 33301193 PMCID: PMC8359362 DOI: 10.1002/cyto.b.21979] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 11/09/2020] [Accepted: 11/24/2020] [Indexed: 12/30/2022]
Abstract
BACKGROUND Acute promyelocytic leukemia (APL) is one of the most life-threatening hematological emergencies and requires a prompt correct diagnosis by cytomorphology and flow cytometry (FCM) with later confirmation by cytogenetics/molecular genetics. However, nucleophosmin 1 muted acute myeloid leukemia (NPM1+ AML) can mimic APL, especially the hypogranular variant of APL. Our study aimed to develop a novel, Radar plot-based FCM strategy to distinguish APLs and NPM1+ AMLs quickly and accurately. METHOD Diagnostic samples from 52 APL and 32 NPM1+ AMLs patients were analyzed by a 3-tube panel of 10-color FCM. Radar plots combining all markers were constructed for each tube. Percentages of positive leukemic cells and mean fluorescence intensity were calculated for all the markers. RESULTS APL showed significantly higher expression of CD64, CD2, and CD13, whereas more leukemic cells were positive for CD11b, CD11c, CD15, CD36, and HLA-DR in NPM1+ AMLs. Radar plots featured CD2 expression, a lack of a monocytic component, lack of expression of HLA-DR and CD15, and a lack of a prominent CD11c+ population as recurring characteristics of APL. The presence of blasts with low SSC, presence of at least some monocytes, some expression of HLA-DR and/or CD15, and a prominent CD11c population were recurrent characteristics of NPM1+ AMLs. Radar plot analysis could confidently separate all hypergranular APL cases from any NPM1+ AML and in 90% of cases between variant APL and blastic NPM1+ AML. CONCLUSION Radar plots can potentially add to differential diagnostics as they exhibit characteristic patterns distinguishing APL and different types of NPM1+ AMLs.
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Affiliation(s)
- Monali Gupta
- Immunophenotyping Laboratory, Viapath Analytics LLP, Department of Hematology, Kings College Hospital, London, UK.,Department of Pathobiology and Laboratory Medicine, Division of Hematopathology, University Health Network, Toronto, Ontario, Canada
| | - Katayoon Jafari
- Department of Pathobiology and Laboratory Medicine, Division of Hematopathology, University Health Network, Toronto, Ontario, Canada.,Department of Pathology and Laboratory Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Amr Rajab
- Department of Pathobiology and Laboratory Medicine, Division of Hematopathology, University Health Network, Toronto, Ontario, Canada.,Medical-Scientific Department, Lifelabs Medical Laboratory Services, Toronto, Ontario, Canada
| | - Cuihong Wei
- Department of Pathobiology and Laboratory Medicine, Division of Hematopathology, University Health Network, Toronto, Ontario, Canada.,Department of Pathology and Laboratory Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Joanna Mazur
- Department of Humanization of Medicine and Sexology, Collegium Medicum, University of Zielona Gora, Zielona Gora, Poland.,Department of Child and Adolescent Health, Institute of Mother and Child, Warsaw, Poland
| | - Anne Tierens
- Department of Pathobiology and Laboratory Medicine, Division of Hematopathology, University Health Network, Toronto, Ontario, Canada
| | - Elizabeth Hyjek
- Department of Pathobiology and Laboratory Medicine, Division of Hematopathology, University Health Network, Toronto, Ontario, Canada.,Department of Pathology, University of Chicago, Chicago, Illinois, USA
| | - Rumina Musani
- Department of Pathobiology and Laboratory Medicine, Division of Hematopathology, University Health Network, Toronto, Ontario, Canada
| | - Anna Porwit
- Department of Pathobiology and Laboratory Medicine, Division of Hematopathology, University Health Network, Toronto, Ontario, Canada.,Faculty of Medicine, Department of Clinical Sciences, Division of Oncology and Pathology, Lund University, Lund, Sweden
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17
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Zerkalenkova E, Mikhaylova E, Lebedeva S, Illarionova O, Baidun L, Kashpor S, Osipova E, Maschan M, Maschan A, Novichkova G, Olshanskaya Y, Popov A. Quantification of
NG2
‐positivity for the precise prediction of
KMT2A
gene rearrangements in childhood acute leukemia. Genes Chromosomes Cancer 2020; 60:88-99. [DOI: 10.1002/gcc.22915] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 10/26/2020] [Accepted: 10/27/2020] [Indexed: 01/19/2023] Open
Affiliation(s)
- Elena Zerkalenkova
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology Moscow Russia
| | - Ekaterina Mikhaylova
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology Moscow Russia
| | - Svetlana Lebedeva
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology Moscow Russia
| | - Olga Illarionova
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology Moscow Russia
| | | | - Svetlana Kashpor
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology Moscow Russia
| | - Elena Osipova
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology Moscow Russia
| | - Michael Maschan
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology Moscow Russia
| | - Alexey Maschan
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology Moscow Russia
| | - Galina Novichkova
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology Moscow Russia
| | - Yulia Olshanskaya
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology Moscow Russia
| | - Alexander Popov
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology Moscow Russia
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18
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Cabanski M, Oldaker T, Stewart JJ, Selliah N, Eck S, Green C, Litwin V, Vitaliti A. Flow cytometric method transfer: Recommendations for best practice. CYTOMETRY PART B-CLINICAL CYTOMETRY 2020; 100:52-62. [PMID: 33207038 DOI: 10.1002/cyto.b.21971] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 10/09/2020] [Accepted: 11/06/2020] [Indexed: 01/12/2023]
Abstract
As with many aspects of the validation and monitoring of flow cytometric methods, the method transfer processes and acceptance criteria described for other technologies are not fully applicable. This is due to the complexity of the highly configurable instrumentation, the complexity of cellular measurands, the lack of qualified reference materials for most assays, and limited specimen stability. There are multiple reasons for initiating a method transfer, multiple regulatory settings, and multiple context of use. All of these factors influence the specific requirements for the method transfer. This recommendation paper describes the considerations and best practices for the transfer of flow cytometric methods and provides individual case studies as examples. In addition, the manuscript emphasizes the importance of appropriately conducting a method transfer on data reliability.
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Affiliation(s)
- Maciej Cabanski
- Novartis Institutes for Biomedical Research, Novartis Pharma AG, Basel, Switzerland
| | - Teri Oldaker
- Oldaker Consulting (LLC), San Clemente, California, USA
| | | | | | - Steve Eck
- AstraZeneca, Integrated Bioanalysis, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Gaithersburg, Maryland, USA
| | - Cherie Green
- Department of Development Sciences, Genentech, Inc., A Member of Roche Group, South San Francisco, California, USA
| | | | - Alessandra Vitaliti
- Novartis Institutes for Biomedical Research, Novartis Pharma AG, Basel, Switzerland
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19
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Illingworth A, Johansson U, Huang S, Horna P, Wang SA, Almeida J, Wolniak KL, Psarra K, Torres R, Craig FE. International guidelines for the flow cytometric evaluation of peripheral blood for suspected Sézary syndrome or mycosis fungoides: Assay development/optimization, validation, and ongoing quality monitors. CYTOMETRY PART B-CLINICAL CYTOMETRY 2020; 100:156-182. [PMID: 33112044 DOI: 10.1002/cyto.b.21963] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 09/14/2020] [Accepted: 09/22/2020] [Indexed: 12/23/2022]
Abstract
Introducing a sensitive and specific peripheral blood flow cytometric assay for Sézary syndrome and mycosis fungoides (SS/MF) requires careful selection of assay design characteristics, and translation into a laboratory developed assay through development/optimization, validation, and continual quality monitoring. As outlined in a previous article in this series, the recommended design characteristics of this assay include at a minimum, evaluation of CD7, CD3, CD4, CD8, CD26, and CD45, analyzed simultaneously, requiring at least a 6 color flow cytometry system, with both quantitative and qualitative components. This article provides guidance from an international group of cytometry specialists in implementing an assay to those design specifications, outlining specific considerations, and best practices. Key points presented in detail are: (a) Pre-analytic components (reagents, specimen processing, and acquisition) must be optimized to: (i) identify and characterize an abnormal population of T-cells (qualitative component) and (ii) quantitate the abnormal population (semi/quasi-quantitative component). (b)Analytic components (instrument set-up/acquisition/analysis strategy and interpretation) must be optimized for the identification of SS/MF populations, which can vary widely in phenotype. Comparison with expert laboratories is strongly encouraged in order to establish competency. (c) Assay performance must be validated and documented through a validation plan and report, which covers both qualitative and semi/quasi-quantitative assay components (example template provided). (d) Ongoing assay-specific quality monitoring should be performed to ensure consistency.
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Affiliation(s)
- Andrea Illingworth
- Flow Cytometry Division, Dahl-Chase Diagnostic Services, Bangor, Maine, USA
| | - Ulrika Johansson
- SI-HMDS, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | | | - Pedro Horna
- Division of Hematopathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Sa A Wang
- Department of Hematopathology, MD Anderson Cancer Center, Houston, Texas, USA
| | - Julia Almeida
- Cancer Research Center (IBMCC-CSIC/USAL-IBSAL); Cytometry Service (NUCLEUS) and Department of Medicine, IBSAL and CIBERONC, University of Salamanca, Salamanca, Spain
| | - Kristy L Wolniak
- Division of Hematopathology, Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Katherina Psarra
- Department of Immunology - Histocompatibility, "Evangelismos" Hospital, Athens, Greece
| | - Richard Torres
- Department of Laboratory Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Fiona E Craig
- Division of Hematopathology, Mayo Clinic Arizona, Phoenix, Arizona, USA
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20
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Espasa A, Torrents S, Morales‐Indiano C, Rico LG, Bardina J, Ancochea A, Bistué‐Rovira À, Linio R, Raya M, Vergara S, Juncà J, Grifols J, Petriz J, Soria M, Sorigue M. Diagnostic performance of the ClearLLab 10C B cell tube. CYTOMETRY PART B-CLINICAL CYTOMETRY 2020; 100:519-530. [DOI: 10.1002/cyto.b.21955] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 09/03/2020] [Accepted: 09/07/2020] [Indexed: 12/20/2022]
Affiliation(s)
- Andrea Espasa
- Hematology Laboratory Institut Català d'Oncologia, Hospital Germans Trias i Pujol, Functional cytomics‐IJC, Universitat Autònoma de Barcelona Badalona Spain
| | | | - Cristian Morales‐Indiano
- Clinical Laboratory ICS‐Metropolitana Nord, Core‐Hematology Department Hospital Germans Trias i Pujol Badalona Spain
| | - Laura G. Rico
- Functional Cytomics, Josep Carreras Leukaemia Research Institute (IJC), Universitat Autònoma de Barcelona, Badalona Barcelona Spain
| | - Jorge Bardina
- Functional Cytomics, Josep Carreras Leukaemia Research Institute (IJC), Universitat Autònoma de Barcelona, Badalona Barcelona Spain
| | - Agueda Ancochea
- Banc de Sang i Teixits Hospital Germans Trias i Pujol Badalona Spain
| | - Àngel Bistué‐Rovira
- Functional Cytomics, Josep Carreras Leukaemia Research Institute (IJC), Universitat Autònoma de Barcelona, Badalona Barcelona Spain
| | - Rosa Linio
- Banc de Sang i Teixits Hospital Germans Trias i Pujol Badalona Spain
| | - Minerva Raya
- Hematology Laboratory Institut Català d'Oncologia, Hospital Germans Trias i Pujol, Functional cytomics‐IJC, Universitat Autònoma de Barcelona Badalona Spain
| | - Sara Vergara
- Hematology Laboratory Institut Català d'Oncologia, Hospital Germans Trias i Pujol, Functional cytomics‐IJC, Universitat Autònoma de Barcelona Badalona Spain
| | - Jordi Juncà
- Hematology Laboratory Institut Català d'Oncologia, Hospital Germans Trias i Pujol, Functional cytomics‐IJC, Universitat Autònoma de Barcelona Badalona Spain
- Functional Cytomics, Josep Carreras Leukaemia Research Institute (IJC), Universitat Autònoma de Barcelona, Badalona Barcelona Spain
| | | | - Jordi Petriz
- Functional Cytomics, Josep Carreras Leukaemia Research Institute (IJC), Universitat Autònoma de Barcelona, Badalona Barcelona Spain
| | | | - Marc Sorigue
- Hematology Laboratory Institut Català d'Oncologia, Hospital Germans Trias i Pujol, Functional cytomics‐IJC, Universitat Autònoma de Barcelona Badalona Spain
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21
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Hanekamp D, Snel AN, Kelder A, Scholten WJ, Khan N, Metzner M, Irno-Consalvo M, Sugita M, de Jong A, Oude Alink S, Eidhof H, Wilhelm M, Feuring-Buske M, Slomp J, van der Velden VHJ, Sonneveld E, Guzman M, Roboz GJ, Buccisano F, Vyas P, Freeman S, Bachas C, Ossenkoppele GJ, Schuurhuis GJ, Cloos J. Applicability and reproducibility of acute myeloid leukaemia stem cell assessment in a multi-centre setting. Br J Haematol 2020; 190:891-900. [PMID: 32239670 PMCID: PMC7540683 DOI: 10.1111/bjh.16594] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Accepted: 03/02/2020] [Indexed: 01/01/2023]
Abstract
Leukaemic stem cells (LSC) have been experimentally defined as the leukaemia‐propagating population and are thought to be the cellular reservoir of relapse in acute myeloid leukaemia (AML). Therefore, LSC measurements are warranted to facilitate accurate risk stratification. Previously, we published the composition of a one‐tube flow cytometric assay, characterised by the presence of 13 important membrane markers for LSC detection. Here we present the validation experiments of the assay in several large AML research centres, both in Europe and the United States. Variability within instruments and sample processing showed high correlations between different instruments (Rpearson > 0·91, P < 0·001). Multi‐centre testing introduced variation in reported LSC percentages but was found to be below the clinical relevant threshold. Clear gating protocols resulted in all laboratories being able to perform LSC assessment of the validation set. Participating centres were nearly unanimously able to distinguish LSChigh (>0·03% LSC) from LSClow (<0·03% LSC) despite inter‐laboratory variation in reported LSC percentages. This study proves that the LSC assay is highly reproducible. These results together with the high prognostic impact of LSC load at diagnosis in AML patients render the one‐tube LSC assessment a good marker for future risk classification.
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Affiliation(s)
- Diana Hanekamp
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Alexander N Snel
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Angèle Kelder
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Willemijn J Scholten
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Naeem Khan
- Institute of Immunology and Immunotherapy, Department of Clinical Immunology, University of Birmingham, Birmingham, United Kingdom
| | - Marlen Metzner
- Medical Research Council Molecular Hematology Unit, Oxford Centre for Hematology, Oxford BRC, University of Oxford and Oxford University Hospitals National Health Service Trust, Oxford, United Kingdom
| | - Maria Irno-Consalvo
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
| | - Mayumi Sugita
- Division of Hematology and Oncology, Department of Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Anja de Jong
- Dutch Childhood Oncology Group, Utrecht, the Netherlands
| | - Sjoerd Oude Alink
- Department of Immunology, Laboratory Medical Immunology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Harrie Eidhof
- Department of Clinical Chemistry, Medisch Spectrum Twente/Medlon, Enschede, the Netherlands
| | - Miriam Wilhelm
- Department of Internal Medicine III, University Hospital Ulm, Ulm, Germany
| | | | - Jennichjen Slomp
- Department of Clinical Chemistry, Medisch Spectrum Twente/Medlon, Enschede, the Netherlands
| | - Vincent H J van der Velden
- Department of Immunology, Laboratory Medical Immunology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | | | - Monica Guzman
- Division of Hematology and Oncology, Department of Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Gail J Roboz
- Division of Hematology and Oncology, Department of Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Francesco Buccisano
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
| | - Paresh Vyas
- Medical Research Council Molecular Hematology Unit, Oxford Centre for Hematology, Oxford BRC, University of Oxford and Oxford University Hospitals National Health Service Trust, Oxford, United Kingdom
| | - Sylvie Freeman
- Institute of Immunology and Immunotherapy, Department of Clinical Immunology, University of Birmingham, Birmingham, United Kingdom
| | - Costa Bachas
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Gert J Ossenkoppele
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Gerrit J Schuurhuis
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Jacqueline Cloos
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, the Netherlands
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22
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Kalina T. Reproducibility of Flow Cytometry Through Standardization: Opportunities and Challenges. Cytometry A 2019; 97:137-147. [DOI: 10.1002/cyto.a.23901] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2019] [Revised: 09/04/2019] [Accepted: 09/11/2019] [Indexed: 12/21/2022]
Affiliation(s)
- Tomas Kalina
- CLIP‐Childhood Leukemia Investigation Prague, Department of Pediatric Hematology and Oncology2nd Medical School, Charles University and University Hospital Motol Prague Czech Republic
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23
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Lacombe F, Lechevalier N, Vial JP, Béné MC. An R-Derived FlowSOM Process to Analyze Unsupervised Clustering of Normal and Malignant Human Bone Marrow Classical Flow Cytometry Data. Cytometry A 2019; 95:1191-1197. [PMID: 31577391 DOI: 10.1002/cyto.a.23897] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2019] [Revised: 08/19/2019] [Accepted: 08/20/2019] [Indexed: 01/14/2023]
Abstract
Multiparameter flow cytometry (MFC) is a powerful and versatile tool to accurately analyze cell subsets, notably to explore normal and pathological hematopoiesis. Yet, mostly supervised subjective strategies are used to identify cell subsets in this complex tissue. In the past few years, the implementation of mass cytometry and the big data generated have led to a blossoming of new software solutions. Their application to classical MFC in hematology is however still seldom reported. Here, we show how one of these new tools, the FlowSOM R solution, can be applied, together with the Kaluza® software, to a new delineation of hematopoietic subsets in normal human bone marrow (BM). We thus combined the unsupervised discrimination of cell subsets provided by FlowSOM and their expert-driven node-by-node assignment to known or new hematopoietic subsets. We also show how this new tool could modify the MFC exploration of hematological malignancies both at diagnosis (Dg) and follow-up (FU). This can be achieved by direct comparison of merged listmodes of reference normal BM, Dg, and FU samples of a representative acute myeloblastic case tested with the same immunophenotyping panel. This provides an immediate unsupervised evaluation of minimal residual disease. © 2019 International Society for Advancement of Cytometry.
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Affiliation(s)
- Francis Lacombe
- Flow cytometry department, Hematology Laboratory, Bordeaux University Hospital, Pessac, France
| | - Nicolas Lechevalier
- Flow cytometry department, Hematology Laboratory, Bordeaux University Hospital, Pessac, France
| | - Jean Philippe Vial
- Flow cytometry department, Hematology Laboratory, Bordeaux University Hospital, Pessac, France
| | - Marie C Béné
- Hematology Biology, Nantes University Hospital, CRCINA, Nantes, France
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24
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Barreau S, Green AS, Dussiau C, Alary A, Raimbault A, Mathis S, Willems L, Bouscary D, Kosmider O, Bardet V, Fontenay M, Chapuis N. Phenotypic landscape of granulocytes and monocytes by multiparametric flow cytometry: A prospective study of a 1‐tube panel strategy for diagnosis and prognosis of patients with MDS. CYTOMETRY PART B-CLINICAL CYTOMETRY 2019; 98:226-237. [DOI: 10.1002/cyto.b.21843] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Revised: 08/02/2019] [Accepted: 08/19/2019] [Indexed: 11/09/2022]
Affiliation(s)
- Sylvain Barreau
- Assistance Publique‐Hôpitaux de Paris, Hôpitaux Universitaires Paris CentreService d'Hématologie Biologique Paris France
- Université de Paris, Institut Cochin, CNRS UMR8104INSERM U1016 Paris France
| | - Alexa S. Green
- Assistance Publique‐Hôpitaux de Paris, Hôpitaux Universitaires Paris CentreService d'Hématologie Biologique Paris France
| | - Charles Dussiau
- Assistance Publique‐Hôpitaux de Paris, Hôpitaux Universitaires Paris CentreService d'Hématologie Biologique Paris France
- Université de Paris, Institut Cochin, CNRS UMR8104INSERM U1016 Paris France
| | - Anne‐Sophie Alary
- Assistance Publique‐Hôpitaux de Paris, Hôpitaux Universitaires Paris CentreService d'Hématologie Biologique Paris France
- Université de Paris, Institut Cochin, CNRS UMR8104INSERM U1016 Paris France
| | - Anna Raimbault
- Assistance Publique‐Hôpitaux de Paris, Hôpitaux Universitaires Paris CentreService d'Hématologie Biologique Paris France
- Université de Paris, Institut Cochin, CNRS UMR8104INSERM U1016 Paris France
| | - Stephanie Mathis
- Assistance Publique‐Hôpitaux de Paris, Hôpitaux Universitaires Paris CentreService d'Hématologie Biologique Paris France
- Université de Paris, Institut Cochin, CNRS UMR8104INSERM U1016 Paris France
| | - Lise Willems
- Assistance Publique‐Hôpitaux de ParisHôpitaux Universitaires Paris Centre, Service d'Hématologie Clinique Paris France
| | - Didier Bouscary
- Université de Paris, Institut Cochin, CNRS UMR8104INSERM U1016 Paris France
- Assistance Publique‐Hôpitaux de ParisHôpitaux Universitaires Paris Centre, Service d'Hématologie Clinique Paris France
| | - Olivier Kosmider
- Assistance Publique‐Hôpitaux de Paris, Hôpitaux Universitaires Paris CentreService d'Hématologie Biologique Paris France
- Université de Paris, Institut Cochin, CNRS UMR8104INSERM U1016 Paris France
| | - Valerie Bardet
- Assistance Publique‐Hôpitaux de ParisHôpitaux Universitaires Paris Ile de France Ouest, Service d'Hématologie‐Immunologie‐Transfusion Boulogne France
- INSERM U1173Université Versailles Saint Quentin en Yvelines France
| | - Michaela Fontenay
- Assistance Publique‐Hôpitaux de Paris, Hôpitaux Universitaires Paris CentreService d'Hématologie Biologique Paris France
- Université de Paris, Institut Cochin, CNRS UMR8104INSERM U1016 Paris France
| | - Nicolas Chapuis
- Assistance Publique‐Hôpitaux de Paris, Hôpitaux Universitaires Paris CentreService d'Hématologie Biologique Paris France
- Université de Paris, Institut Cochin, CNRS UMR8104INSERM U1016 Paris France
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25
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Reiter M, Diem M, Schumich A, Maurer-Granofszky M, Karawajew L, Rossi JG, Ratei R, Groeneveld-Krentz S, Sajaroff EO, Suhendra S, Kampel M, Dworzak MN. Automated Flow Cytometric MRD Assessment in Childhood Acute B- Lymphoblastic Leukemia Using Supervised Machine Learning. Cytometry A 2019; 95:966-975. [PMID: 31282025 DOI: 10.1002/cyto.a.23852] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Revised: 04/30/2019] [Accepted: 05/28/2019] [Indexed: 12/22/2022]
Abstract
Minimal residual disease (MRD) as measured by multiparameter flow cytometry (FCM) is an independent and strong prognostic factor in B-cell acute lymphoblastic leukemia (B-ALL). However, reliable flow cytometric detection of MRD strongly depends on operator skills and expert knowledge. Hence, an objective, automated tool for reliable FCM-MRD quantification, able to overcome the technical diversity and analytical subjectivity, would be most helpful. We developed a supervised machine learning approach using a combination of multiple Gaussian Mixture Models (GMM) as a parametric density model. The approach was used for finding the weights of a linear combination of multiple GMMs to represent new, "unseen" samples by an interpolation of stored samples. The experimental data set contained FCM-MRD data of 337 bone marrow samples collected at day 15 of induction therapy in three different laboratories from pediatric patients with B-ALL for which accurate, expert-set gates existed. We compared MRD quantification by our proposed GMM approach to operator assessments, its performance on data from different laboratories, as well as to other state-of-the-art automated read-out methods. Our proposed GMM-combination approach proved superior over support vector machines, deep neural networks, and a single GMM approach in terms of precision and average F 1 -scores. A high correlation of expert operator-based and automated MRD assessment was achieved with reliable automated MRD quantification (F 1 -scores >0.5 in more than 95% of samples) in the clinically relevant range. Although best performance was found, if test and training samples were from the same system (i.e., flow cytometer and staining panel; lowest median F 1 -score 0.92), cross-system performance remained high with a median F 1 -score above 0.85 in all settings. In conclusion, our proposed automated approach could potentially be used to assess FCM-MRD in B-ALL in an objective and standardized manner across different laboratories. © 2019 International Society for Advancement of Cytometry.
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Affiliation(s)
- Michael Reiter
- Immunological Diagnostics, Children's Cancer Research Institute, Vienna, Austria.,Computer Vision Lab, Faculty of Informatics, Technical University of Vienna, Vienna, Austria
| | - Markus Diem
- Immunological Diagnostics, Children's Cancer Research Institute, Vienna, Austria.,Computer Vision Lab, Faculty of Informatics, Technical University of Vienna, Vienna, Austria
| | - Angela Schumich
- Immunological Diagnostics, Children's Cancer Research Institute, Vienna, Austria
| | | | - Leonid Karawajew
- Department of Pediatric Oncology/Hematology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Jorge G Rossi
- Cellular Immunology Laboratory, Hospital de Pediatria "Dr. Juan P. Garrahan", Buenos Aires, Argentina
| | - Richard Ratei
- Department of Hematology, Oncology and Tumor Immunology, HELIOS Klinikum Berlin-Buch, Berlin, Germany
| | | | - Elisa O Sajaroff
- Cellular Immunology Laboratory, Hospital de Pediatria "Dr. Juan P. Garrahan", Buenos Aires, Argentina
| | | | - Martin Kampel
- Computer Vision Lab, Faculty of Informatics, Technical University of Vienna, Vienna, Austria
| | - Michael N Dworzak
- Immunological Diagnostics, Children's Cancer Research Institute, Vienna, Austria.,Labdia Labordiagnostik GmbH, Vienna, Austria
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26
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Innovation in Flow Cytometry Analysis: A New Paradigm Delineating Normal or Diseased Bone Marrow Subsets Through Machine Learning. Hemasphere 2019; 3:e173. [PMID: 31723814 PMCID: PMC6746040 DOI: 10.1097/hs9.0000000000000173] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2018] [Accepted: 12/26/2018] [Indexed: 11/25/2022] Open
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27
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Buldini B, Maurer-Granofszky M, Varotto E, Dworzak MN. Flow-Cytometric Monitoring of Minimal Residual Disease in Pediatric Patients With Acute Myeloid Leukemia: Recent Advances and Future Strategies. Front Pediatr 2019; 7:412. [PMID: 31681710 PMCID: PMC6798174 DOI: 10.3389/fped.2019.00412] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Accepted: 09/25/2019] [Indexed: 01/10/2023] Open
Abstract
Minimal residual disease (MRD) by multiparametric flow cytometry (MFC) has been recently shown as a strong and independent prognostic marker of relapse in pediatric AML (pedAML) when measured at specific time points during Induction and/or Consolidation therapy. Hence, MFC-MRD has the potential to refine the current strategies of pedAML risk stratification, traditionally based on the cytogenetic and molecular genetic aberrations at diagnosis. Consequently, it may guide the modulation of therapy intensity and clinical decision making. However, the use of non-standardized protocols, including different staining panels, analysis, and gating strategies, may hamper a broad implementation of MFC-MRD monitoring in clinical routine. Besides, the thresholds of MRD positivity still need to be validated in large, prospective and multi-center clinical studies, as well as optimal time points of MRD assessment during therapy, to better discriminate patients with different prognosis. In the present review, we summarize the most relevant findings on MFC-MRD testing in pedAML. We examine the clinical significance of MFC-MRD and the recent advances in its standardization, including innovative approaches with an automated analysis of MFC-MRD data. We also touch upon other technologies for MRD assessment in AML, such as quantitative genomic breakpoint PCR, current challenges and future strategies to enable full incorporation of MFC-MRD into clinical practice.
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Affiliation(s)
- Barbara Buldini
- Laboratory of Hematology-Oncology, Department of Woman's and Child's Health, University of Padova, Padova, Italy
| | | | - Elena Varotto
- Laboratory of Hematology-Oncology, Department of Woman's and Child's Health, University of Padova, Padova, Italy
| | - Michael N Dworzak
- Children's Cancer Research Institute (CCRI), St. Anna Kinderkrebsforschung, Vienna, Austria
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28
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Acceptable “Real‐Life” Variability for Lymphocyte Counts by Flow Cytometry. CYTOMETRY PART B-CLINICAL CYTOMETRY 2018; 96:379-388. [DOI: 10.1002/cyto.b.21751] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 10/09/2018] [Accepted: 10/23/2018] [Indexed: 11/07/2022]
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29
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Béné MC, Eveillard M. Evaluation of minimal residual disease in childhood ALL. Int J Lab Hematol 2018; 40 Suppl 1:104-108. [DOI: 10.1111/ijlh.12835] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Accepted: 04/04/2018] [Indexed: 11/26/2022]
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30
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Daix T, Guerin E, Tavernier E, Mercier E, Gissot V, Hérault O, Mira JP, Dumas F, Chapuis N, Guitton C, Béné MC, Quenot JP, Tissier C, Guy J, Piton G, Roggy A, Muller G, Legac É, de Prost N, Khellaf M, Wagner-Ballon O, Coudroy R, Dindinaud E, Uhel F, Roussel M, Lafon T, Jeannet R, Vargas F, Fleureau C, Roux M, Allou K, Vignon P, Feuillard J, François B. Multicentric Standardized Flow Cytometry Routine Assessment of Patients With Sepsis to Predict Clinical Worsening. Chest 2018; 154:617-627. [PMID: 29705219 DOI: 10.1016/j.chest.2018.03.058] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Revised: 02/21/2018] [Accepted: 03/19/2018] [Indexed: 10/17/2022] Open
Abstract
BACKGROUND In this study, we primarily sought to assess the ability of flow cytometry to predict early clinical deterioration and overall survival in patients with sepsis admitted in the ED and ICU. METHODS Patients admitted for community-acquired acute sepsis from 11 hospital centers were eligible. Early (day 7) and late (day 28) deaths were notified. Levels of CD64pos granulocytes, CD16pos monocytes, CD16dim immature granulocytes (IGs), and T and B lymphocytes were assessed by flow cytometry using an identical, cross-validated, robust, and simple consensus standardized protocol in each center. RESULTS Among 1,062 patients screened, 781 patients with confirmed sepsis were studied (age, 67 ± 48 years; Simplified Acute Physiology Score II, 36 ± 17; Sequential Organ Failure Assessment, 5 ± 4). Patients were divided into three groups (sepsis, severe sepsis, and septic shock) on day 0 and on day 2. On day 0, patients with sepsis exhibited increased levels of CD64pos granulocytes, CD16pos monocytes, and IGs with T-cell lymphopenia. Clinical severity was associated with higher percentages of IGs and deeper T-cell lymphopenia. IG percentages tended to be higher in patients whose clinical status worsened on day 2 (35.1 ± 35.6 vs 43.5 ± 35.2, P = .07). Increased IG percentages were also related to occurrence of new organ failures on day 2. Increased IG percentages, especially when associated with T-cell lymphopenia, were independently associated with early (P < .01) and late (P < .01) death. CONCLUSIONS Increased circulating IGs at the acute phase of sepsis are linked to clinical worsening, especially when associated with T-cell lymphopenia. Early flow cytometry could help clinicians to target patients at high risk of clinical deterioration. TRIAL REGISTRY ClinicalTrials.gov; No.: NCT01995448; URL: www.clinicaltrials.gov.
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Affiliation(s)
- Thomas Daix
- Réanimation Polyvalente, CHU Dupuytren, Limoges, France; Inserm CIC1435, CHU Dupuytren, Limoges, France
| | - Estelle Guerin
- Hématologie Biologique, CHU Dupuytren, Limoges, France; CNRS UMR 7276, Université de Limoges, Limoges, France
| | - Elsa Tavernier
- Inserm CIC1415, CHRU and Université François Rabelais, Tours, France
| | | | - Valérie Gissot
- Inserm CIC1415, CHRU and Université François Rabelais, Tours, France
| | | | - Jean-Paul Mira
- Réanimation Médicale Polyvalente, Hôpital Cochin, Assistance Publique des Hôpitaux de Paris, Paris, France
| | - Florence Dumas
- Urgences, Hôpital Cochin/Hôtel-Dieu, Assistance Publique des Hôpitaux de Paris and Inserm UMR 970, Université Paris Descartes, Paris, France
| | - Nicolas Chapuis
- Hématologie Biologique, Hôpital Cochin, Assistance Publique des Hôpitaux de Paris, Paris, France
| | | | - Marie C Béné
- Hématologie Biologique, CHU de Nantes, Nantes, France
| | - Jean-Pierre Quenot
- Réanimation Polyvalente, CHU François Mitterrand and Lipness Team, Centre de Recherche Inserm LNC-UMR1231 and LabExLipSTIC and Inserm CIC 1432, Epidémiologie Clinique, Université de Bourgogne, Dijon, France
| | | | - Julien Guy
- Hématologie Biologique, CHU de Dijon, Dijon, France
| | - Gaël Piton
- Réanimation Médicale, CHRU de Besançon, Université de Franche Comte, UFR SMP, EA3920, Besançon, France
| | - Anne Roggy
- Inserm UMR1098 and Laboratoire d'Immunologie, EFS BFC, Besançon, France
| | | | - Éric Legac
- Hématologie Biologique, CHR d'Orléans, Orléans, France
| | - Nicolas de Prost
- Réanimation Médicale, CHU Henri Mondor, Assistance Publique-Hôpitaux de Paris, DHU A-TVB, and Université Paris Est Créteil, Faculté de Médecine de Créteil, Groupe de Recherche CARMAS, Créteil, France
| | - Mehdi Khellaf
- Urgences, Assistance Publique-Hôpitaux de Paris, CHU Henri Mondor, Créteil, France
| | - Orianne Wagner-Ballon
- Hématologie et Immunologie Biologiques, Assistance Publique-Hôpitaux de Paris, CHU Henri Mondor and Université Paris-Est Créteil, Inserm UMR 955, Créteil, France
| | - Rémi Coudroy
- Réanimation Médicale, CHU de Poitiers, Poitiers, France
| | | | - Fabrice Uhel
- Réanimation Médicale and Inserm CIC1414, CHU de Rennes, and Inserm UMR 917, Université de Rennes, Rennes, France
| | - Mikaël Roussel
- Hématologie Biologique and Inserm UMR 1236, CHU Pontchaillou, Rennes, France
| | - Thomas Lafon
- Inserm CIC1435, CHU Dupuytren, Limoges, France; Urgences, CHU Dupuytren, Limoges, France
| | - Robin Jeannet
- Hématologie Biologique, CHU Dupuytren, Limoges, France
| | | | | | | | - Kaoutar Allou
- Hématologie Biologique, CHU de Bordeaux, Bordeaux, France
| | - Philippe Vignon
- Réanimation Polyvalente, CHU Dupuytren, Limoges, France; Inserm CIC1435, CHU Dupuytren, Limoges, France; Inserm UMR 1092, Université de Limoges, Limoges, France
| | - Jean Feuillard
- Hématologie Biologique, CHU Dupuytren, Limoges, France; CNRS UMR 7276, Université de Limoges, Limoges, France
| | - Bruno François
- Réanimation Polyvalente, CHU Dupuytren, Limoges, France; Inserm CIC1435, CHU Dupuytren, Limoges, France; Inserm UMR 1092, Université de Limoges, Limoges, France.
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31
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Schuurhuis GJ, Heuser M, Freeman S, Béné MC, Buccisano F, Cloos J, Grimwade D, Haferlach T, Hills RK, Hourigan CS, Jorgensen JL, Kern W, Lacombe F, Maurillo L, Preudhomme C, van der Reijden BA, Thiede C, Venditti A, Vyas P, Wood BL, Walter RB, Döhner K, Roboz GJ, Ossenkoppele GJ. Minimal/measurable residual disease in AML: a consensus document from the European LeukemiaNet MRD Working Party. Blood 2018; 131:1275-1291. [PMID: 29330221 PMCID: PMC5865231 DOI: 10.1182/blood-2017-09-801498] [Citation(s) in RCA: 771] [Impact Index Per Article: 128.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2017] [Accepted: 01/03/2018] [Indexed: 12/13/2022] Open
Abstract
Measurable residual disease (MRD; previously termed minimal residual disease) is an independent, postdiagnosis, prognostic indicator in acute myeloid leukemia (AML) that is important for risk stratification and treatment planning, in conjunction with other well-established clinical, cytogenetic, and molecular data assessed at diagnosis. MRD can be evaluated using a variety of multiparameter flow cytometry and molecular protocols, but, to date, these approaches have not been qualitatively or quantitatively standardized, making their use in clinical practice challenging. The objective of this work was to identify key clinical and scientific issues in the measurement and application of MRD in AML, to achieve consensus on these issues, and to provide guidelines for the current and future use of MRD in clinical practice. The work was accomplished over 2 years, during 4 meetings by a specially designated MRD Working Party of the European LeukemiaNet. The group included 24 faculty with expertise in AML hematopathology, molecular diagnostics, clinical trials, and clinical medicine, from 19 institutions in Europe and the United States.
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Affiliation(s)
- Gerrit J Schuurhuis
- Department of Hematology, VU University Medical Center, Amsterdam, The Netherlands
| | - Michael Heuser
- Department of Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany
| | - Sylvie Freeman
- Department of Clinical Immunology, Institute of Immunology and Immunotherapy, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
| | | | - Francesco Buccisano
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
| | - Jacqueline Cloos
- Department of Hematology, VU University Medical Center, Amsterdam, The Netherlands
- Department of Pediatric Oncology, VU University Medical Center, Amsterdam, The Netherlands
| | - David Grimwade
- Division of Genetics & Molecular Medicine, King's College, London, United Kingdom
| | | | - Robert K Hills
- Centre for Trials Research, Cardiff University, Cardiff, United Kingdom
| | | | - Jeffrey L Jorgensen
- Division of Pathology/Laboratory Medicine, Department of Hematopathology, MD Anderson Cancer Center, Houston, TX
| | | | - Francis Lacombe
- Flow Cytometry Platform, University Hospital, Bordeaux, France
| | - Luca Maurillo
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
| | - Claude Preudhomme
- Center of Pathology, Laboratory of Hematology, University Hospital of Lille, Lille, France
| | - Bert A van der Reijden
- Department of Laboratory Medicine, Laboratory of Hematology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Christian Thiede
- Universitätsklinikum Carl Gustav Garus an der Technischen Universität Dresden, Dresden, Germany
| | - Adriano Venditti
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
| | - Paresh Vyas
- Medical Research Council Molecular Haematology Unit, Oxford Centre for Haematology, University of Oxford and Oxford University Hospitals National Health Service Trust, Oxford, United Kingdom
| | - Brent L Wood
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA
- Department of Laboratory Medicine and
| | - Roland B Walter
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA
- Division of Hematology, Department of Medicine, University of Washington, Seattle, WA
| | - Konstanze Döhner
- Department of Internal Medicine III, University Hospital of Ulm, Ulm, Germany; and
| | - Gail J Roboz
- Weill Cornell Medicine and New York Presbyterian Hospital, New York, NY
| | - Gert J Ossenkoppele
- Department of Hematology, VU University Medical Center, Amsterdam, The Netherlands
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Hehlmann R. Advancing a field by building consortia: The example of the European LeukemiaNet. Cancer 2018; 124:1100-1104. [PMID: 29451688 DOI: 10.1002/cncr.31199] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2017] [Revised: 11/13/2017] [Accepted: 11/16/2017] [Indexed: 11/07/2022]
Affiliation(s)
- Rüdiger Hehlmann
- European LeukemiaNet Foundation, Weinheim, Germany
- Mannheim Medical Faculty, Heidelberg University, Mannheim, Germany
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Sutherland DR, Illingworth A, Marinov I, Ortiz F, Andreasen J, Payne D, Wallace PK, Keeney M. ICCS/ESCCA Consensus Guidelines to detect GPI-deficient cells in Paroxysmal Nocturnal Hemoglobinuria (PNH) and related Disorders Part 2 - Reagent Selection and Assay Optimization for High-Sensitivity Testing. CYTOMETRY PART B-CLINICAL CYTOMETRY 2018; 94:23-48. [DOI: 10.1002/cyto.b.21610] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Revised: 12/07/2017] [Accepted: 12/11/2017] [Indexed: 11/11/2022]
Affiliation(s)
| | | | - Iuri Marinov
- Institute of Hematology and Blood Transfusion; Prague Czech Republic
| | - Fernando Ortiz
- University Health Network, Toronto General Hospital; Ontario M5G2C4 Canada
| | - John Andreasen
- Immunologic Flow Cytometry; ARUP Laboratories, Inc; Salt Lake City Utah
| | - Dan Payne
- HMDL and Immunology Flow Cytometry Service; Leicester Royal Infirmary UHL NHS Trust; Leicester United Kingdom
| | - Paul K. Wallace
- Department of Flow and Image Cytometry; Roswell Park Cancer Institute; Buffalo New York
| | - Michael Keeney
- Department of Hematology/Flow Cytometry London Health Sciences Centre; London Ontario Canada
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Panel proposal for the immunophenotypic diagnosis of hematological malignancies. A collaborative consensus from the groupe d'Etude Immunologique des Leucémies (GEIL). CYTOMETRY PART B-CLINICAL CYTOMETRY 2017; 94:542-547. [DOI: 10.1002/cyto.b.21602] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2017] [Revised: 11/11/2017] [Accepted: 11/20/2017] [Indexed: 11/09/2022]
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35
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Lacombe F, Campos L, Allou K, Arnoulet C, Delabarthe A, Dumezy F, Feuillard J, Geneviève F, Guérin E, Guy J, Jouault H, Lepelley P, Maynadié M, Solly F, Ballon OW, Preudhomme C, Baruchel A, Dombret H, Ifrah N, Béné MC. Prognostic value of multicenter flow cytometry harmonized assessment of minimal residual disease in acute myeloblastic leukemia. Hematol Oncol 2017; 36:422-428. [DOI: 10.1002/hon.2488] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2017] [Revised: 10/13/2017] [Accepted: 11/06/2017] [Indexed: 01/17/2023]
Affiliation(s)
| | - Lydia Campos
- Hematology Biology; University Hospital; Saint Etienne France
| | - Kaoutar Allou
- Hematology Biology; University Hospital; Bordeaux France
| | | | | | | | | | | | | | - Julien Guy
- Hematology Biology; University Hospital; Dijon France
| | | | | | - Marc Maynadié
- Hematology Biology; University Hospital; Dijon France
| | - Françoise Solly
- Hematology Biology; University Hospital; Saint Etienne France
| | | | | | - André Baruchel
- Hematology Department; Hôpital Robert Debré; Paris France
| | - Hervé Dombret
- Hematology Department; Hôpital Saint Louis; Paris France
| | - Norbert Ifrah
- Hematology Department; University Hospital; Angers France
| | - Marie C. Béné
- Hematology Biology; University Hospital; Nantes France
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Rajab A, Axler O, Leung J, Wozniak M, Porwit A. Ten-color 15-antibody flow cytometry panel for immunophenotyping of lymphocyte population. Int J Lab Hematol 2017; 39 Suppl 1:76-85. [DOI: 10.1111/ijlh.12678] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2017] [Accepted: 03/08/2017] [Indexed: 01/13/2023]
Affiliation(s)
- A. Rajab
- Hematology Department; LifeLabs; Toronto ON Canada
| | - O. Axler
- Klinisk patologi, Labmedicin; Medicinsk Service, Region Skåne; Lunds Universitetsjukhus; Lund Sweden
| | - J. Leung
- Flow Cytometry Laboratory; Laboratory Medicine Program; University Health Network; Toronto ON Canada
| | - M. Wozniak
- Hematology Department; LifeLabs; Toronto ON Canada
| | - A. Porwit
- Division for Oncology and Pathology; Department of Clinical Sciences Lund; Faculty of Medicine; Lund University; Lund Sweden
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37
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Diagnostic Utility of Flow Cytometry in Myelodysplastic Syndromes. Mediterr J Hematol Infect Dis 2017; 9:e2017017. [PMID: 28293405 PMCID: PMC5333741 DOI: 10.4084/mjhid.2017.017] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2016] [Accepted: 01/20/2017] [Indexed: 12/19/2022] Open
Abstract
The pathological hallmark of myelodysplastic syndromes (MDS) is marrow dysplasia, which represents the basis of the WHO classification of these disorders. This classification provides clinicians with a useful tool for defining the different subtypes of MDS and individual prognosis. The WHO proposal has raised some concern regarding minimal diagnostic criteria particularly in patients with normal karyotype without robust morphological markers of dysplasia (such as ring sideroblasts or excess of blasts). Therefore, there is clearly need to refine the accuracy to detect marrow dysplasia. Flow cytometry (FCM) immunophenotyping has been proposed as a tool to improve the evaluation of marrow dysplasia. The rationale for the application of FCM in the diagnostic work up of MDS is that immunophenotyping is an accurate method for quantitative and qualitative evaluation of hematopoietic cells and that MDS have been found to have abnormal expression of several cellular antigens. To become applicable in clinical practice, FCM analysis should be based on parameters with sufficient specificity and sensitivity, data should be reproducible between different operators, and the results should be easily understood by clinicians. In this review, we discuss the most relevant progresses in detection of marrow dysplasia by FCM in MDS
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