1
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Della Porta MG, Bewersdorf JP, Wang YH, Hasserjian RP. Future directions in myelodysplastic syndromes/neoplasms and acute myeloid leukaemia classification: from blast counts to biology. Histopathology 2024. [PMID: 39450427 DOI: 10.1111/his.15353] [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: 08/14/2024] [Revised: 10/01/2024] [Accepted: 10/03/2024] [Indexed: 10/26/2024]
Abstract
Myelodysplastic syndromes/neoplasms (MDS) and acute myeloid leukaemia (AML) are neoplastic haematopoietic cell proliferations that are diagnosed and classified based on a combination of morphological, clinical and genetic features. Specifically, the percentage of myeloblasts in the blood and bone marrow is a key feature that has historically separated MDS from AML and, together with several other morphological parameters, defines distinct disease entities within MDS. Both MDS and AML have recurrent genetic abnormalities that are increasingly influencing their definitions and subclassification. For example, in 2022, two new MDS entities were recognised based on the presence of SF3B1 mutation or bi-allelic TP53 abnormalities. Genomic information is more objective and reproducible than morphological analyses, which are subject to interobserver variability and arbitrary numeric cut-offs. Nevertheless, the integration of genomic data with traditional morphological features in myeloid neoplasm classification has proved challenging by virtue of its sheer complexity; gene expression and methylation profiling also can provide information regarding disease pathogenesis, adding to the complexity. New machine-learning technologies have the potential to effectively integrate multiple diagnostic modalities and improve on historical classification systems. Going forward, the application of machine learning and advanced statistical methods to large patient cohorts can refine future classifications by advancing unbiased and robust previously unrecognised disease subgroups. Future classifications will probably incorporate these newer technologies and higher-level analyses that emphasise genomic disease entities over traditional morphologically defined entities, thus promoting more accurate diagnosis and patient risk stratification.
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Affiliation(s)
- Matteo G Della Porta
- Comprehensive Cancer Center, IRCCS Humanitas Clinical and Research Center and Humanitas University, Milan, Italy
| | - Jan Philipp Bewersdorf
- Department of Internal Medicine, Section of Hematology, Yale University and Yale Cancer Center, New Haven, CT, USA
| | - Yu-Hung Wang
- Epigenetics of Haematopoiesis Laboratory, Division of Cancer Sciences, The University of Manchester, Manchester, UK
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan
| | - Robert P Hasserjian
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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2
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Gonsalves M, Escobar A, Altarabishi AD, Xu CQ. Advances in Microflow Cytometry-Based Molecular Detection Methods for Improved Future MDS Cancer Diagnosis. Curr Issues Mol Biol 2024; 46:8053-8070. [PMID: 39194693 DOI: 10.3390/cimb46080476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2024] [Revised: 07/19/2024] [Accepted: 07/24/2024] [Indexed: 08/29/2024] Open
Abstract
Myelodysplastic syndromes (MDS) are a rare form of early-stage blood cancer that typically leads to leukemia and other deadly complications. The typical diagnosis for MDS involves a mixture of blood tests, a bone marrow biopsy, and genetic analysis. Flow cytometry has commonly been used to analyze these types of samples, yet there still seems to be room for advancement in several areas, such as the limit of detection, turnaround time, and cost. This paper explores recent advancements in microflow cytometry technology and how it may be used to supplement conventional methods of diagnosing blood cancers, such as MDS and leukemia, through flow cytometry. Microflow cytometry, a more recent adaptation of the well-researched and conventional flow cytometry techniques, integrated with microfluidics, demonstrates significant potential in addressing many of the shortcomings flow cytometry faces when diagnosing a blood-related disease such as MDS. The benefits that this platform brings, such as portability, processing speed, and operating cost, exemplify the importance of exploring microflow cytometry as a point-of-care (POC) diagnostic device for MDS and other forms of blood cancer.
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Affiliation(s)
- Marc Gonsalves
- Department of Engineering Physics, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4L8, Canada
- Faculty of Health Sciences, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4L8, Canada
| | - Andres Escobar
- School of Biomedical Engineering, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4L8, Canada
| | - Ahmad Diaa Altarabishi
- School of Biomedical Engineering, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4L8, Canada
| | - Chang-Qing Xu
- Department of Engineering Physics, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4L8, Canada
- School of Biomedical Engineering, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4L8, Canada
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3
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Ng DP, Simonson PD, Tarnok A, Lucas F, Kern W, Rolf N, Bogdanoski G, Green C, Brinkman RR, Czechowska K. Recommendations for using artificial intelligence in clinical flow cytometry. CYTOMETRY. PART B, CLINICAL CYTOMETRY 2024; 106:228-238. [PMID: 38407537 DOI: 10.1002/cyto.b.22166] [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: 08/13/2023] [Revised: 01/16/2024] [Accepted: 02/06/2024] [Indexed: 02/27/2024]
Abstract
Flow cytometry is a key clinical tool in the diagnosis of many hematologic malignancies and traditionally requires close inspection of digital data by hematopathologists with expert domain knowledge. Advances in artificial intelligence (AI) are transferable to flow cytometry and have the potential to improve efficiency and prioritization of cases, reduce errors, and highlight fundamental, previously unrecognized associations with underlying biological processes. As a multidisciplinary group of stakeholders, we review a range of critical considerations for appropriately applying AI to clinical flow cytometry, including use case identification, low and high risk use cases, validation, revalidation, computational considerations, and the present regulatory frameworks surrounding AI in clinical medicine. In particular, we provide practical guidance for the development, implementation, and suggestions for potential regulation of AI-based methods in the clinical flow cytometry laboratory. We expect these recommendations to be a helpful initial framework of reference, which will also require additional updates as the field matures.
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Affiliation(s)
- David P Ng
- Department of Pathology, University of Utah, Salt Lake City, Utah, USA
| | - Paul D Simonson
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York, USA
| | - Attila Tarnok
- Department of Preclinical Development and Validation, Fraunhofer Institute for Cell Therapy and Immunology, IZI, Leipzig, Germany
| | - Fabienne Lucas
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA
| | - Wolfgang Kern
- MLL Munich Leukemia Laboratory GmbH, Munich, Germany
| | - Nina Rolf
- BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada
| | - Goce Bogdanoski
- Clinical Development & Operations Quality, R&D Quality, Bristol Myers Squibb, Princeton, New Jersey, USA
| | - Cherie Green
- Translational Science, Ozette Technologies, Seattle, Washington, USA
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4
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Zhang L, Deeb G, Deeb KK, Vale C, Peker Barclift D, Papadantonakis N. Measurable (Minimal) Residual Disease in Myelodysplastic Neoplasms (MDS): Current State and Perspectives. Cancers (Basel) 2024; 16:1503. [PMID: 38672585 PMCID: PMC11048433 DOI: 10.3390/cancers16081503] [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: 02/17/2024] [Revised: 04/08/2024] [Accepted: 04/10/2024] [Indexed: 04/28/2024] Open
Abstract
Myelodysplastic Neoplasms (MDS) have been traditionally studied through the assessment of blood counts, cytogenetics, and morphology. In recent years, the introduction of molecular assays has improved our ability to diagnose MDS. The role of Measurable (minimal) Residual Disease (MRD) in MDS is evolving, and molecular and flow cytometry techniques have been used in several studies. In this review, we will highlight the evolving concept of MRD in MDS, outline the various techniques utilized, and provide an overview of the studies reporting MRD and the correlation with outcomes.
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Affiliation(s)
- Linsheng Zhang
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - George Deeb
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Kristin K. Deeb
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Colin Vale
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory University, Atlanta, GA 30322, USA
| | - Deniz Peker Barclift
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Nikolaos Papadantonakis
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory University, Atlanta, GA 30322, USA
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5
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van de Loosdrecht AA, Cremers EMP, Alhan C, Duetz C, In 't Hout FEM, Visser-Wisselaar HA, Chitu DA, Verbrugge A, Cunha SM, Ossenkoppele GJ, Janssen JJWM, Klein SK, Vellenga E, Huls GA, Muus P, Langemeijer SMC, de Greef GE, Te Boekhorst PAW, Raaijmakers MHG, van Marwijk Kooy M, Legdeur MC, Wegman JJ, Deenik W, de Weerdt O, van Maanen-Lamme TM, Jobse P, van Kampen RJW, Beeker A, Wijermans PW, Biemond BJ, Tanis BC, van Esser JWJ, Schaar CG, Noordzij-Nooteboom HS, Jacobs EMG, de Graaf AO, Jongen-Lavrencic M, Stevens-Kroef MJPL, Westers TM, Jansen JH. Determinants of lenalidomide response with or without erythropoiesis-stimulating agents in myelodysplastic syndromes: the HOVON89 trial. Leukemia 2024; 38:840-850. [PMID: 38297135 PMCID: PMC10997501 DOI: 10.1038/s41375-024-02161-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 01/11/2024] [Accepted: 01/17/2024] [Indexed: 02/02/2024]
Abstract
A randomized phase-II study was performed in low/int-1 risk MDS (IPSS) to study efficacy and safety of lenalidomide without (arm A) or with (arm B) ESA/G-CSF. In arm B, patients without erythroid response (HI-E) after 4 cycles received ESA; G-CSF was added if no HI-E was obtained by cycle 9. HI-E served as primary endpoint. Flow cytometry and next-generation sequencing were performed to identify predictors of response. The final evaluation comprised 184 patients; 84% non-del(5q), 16% isolated del(5q); median follow-up: 70.7 months. In arm A and B, 39 and 41% of patients achieved HI-E; median time-to-HI-E: 3.2 months for both arms, median duration of-HI-E: 9.8 months. HI-E was significantly lower in non-del(5q) vs. del(5q): 32% vs. 80%. The same accounted for transfusion independency-at-week 24 (16% vs. 67%), but similar in both arms. Apart from presence of del(5q), high percentages of bone marrow lymphocytes and progenitor B-cells, a low number of mutations, absence of ring sideroblasts, and SF3B1 mutations predicted HI-E. In conclusion, lenalidomide induced HI-E in patients with non-del(5q) and del(5q) MDS without additional effect of ESA/G-CSF. The identified predictors of response may guide application of lenalidomide in lower-risk MDS in the era of precision medicine. (EudraCT 2008-002195-10).
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Affiliation(s)
- A A van de Loosdrecht
- Department of Hematology, Amsterdam UMC, location VUmc, Cancer Center Amsterdam, Amsterdam, The Netherlands.
| | - E M P Cremers
- Department of Hematology, Amsterdam UMC, location VUmc, Cancer Center Amsterdam, Amsterdam, The Netherlands
- Department of Laboratory Medicine - Laboratory of Hematology, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Hematology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - C Alhan
- Department of Hematology, Amsterdam UMC, location VUmc, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - C Duetz
- Department of Hematology, Amsterdam UMC, location VUmc, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - F E M In 't Hout
- Department of Laboratory Medicine - Laboratory of Hematology, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Hematology, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - D A Chitu
- HOVON Foundation, Rotterdam, The Netherlands
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - A Verbrugge
- HOVON Foundation, Rotterdam, The Netherlands
| | - S M Cunha
- HOVON Foundation, Rotterdam, The Netherlands
| | - G J Ossenkoppele
- Department of Hematology, Amsterdam UMC, location VUmc, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - J J W M Janssen
- Department of Hematology, Amsterdam UMC, location VUmc, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - S K Klein
- Department of Hematology, Meander Medisch Centrum, Amersfoort, The Netherlands
- Department of Hematology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - E Vellenga
- Department of Hematology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - G A Huls
- Department of Hematology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - P Muus
- Department of Hematology, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Haematology, St. James University Hospital, Leeds, UK
| | - S M C Langemeijer
- Department of Laboratory Medicine - Laboratory of Hematology, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Hematology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - G E de Greef
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - P A W Te Boekhorst
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - M H G Raaijmakers
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | | | - M C Legdeur
- Department of Hematology, Medisch Spectrum Twente, Enschede, The Netherlands
| | - J J Wegman
- Department of Hematology, Deventer Ziekenhuis, Deventer, The Netherlands
- Department of Hematology, Amsterdam UMC, location AMC, Amsterdam, The Netherlands
| | - W Deenik
- Department of Internal Medicine, Tergooi Ziekenhuis, Hilversum, The Netherlands
- Department of Internal Medicine, Rijnstate, Arnhem, the Netherlands
| | - O de Weerdt
- Department of Internal Medicine, St. Antonius Ziekenhuis, Nieuwegein, The Netherlands
| | | | - P Jobse
- Department of Internal Medicine, Admiraal de Ruyter Ziekenhuis, Goes, The Netherlands
| | - R J W van Kampen
- Department of Internal Medicine, Zuyderland Ziekenhuis, Geleen, The Netherlands
| | - A Beeker
- Department of Hematology, Spaarne Gasthuis, Hoofddorp, The Netherlands
| | - P W Wijermans
- Department of Hematology, Haaglanden Ziekenhuis, Den Haag, The Netherlands
| | - B J Biemond
- Department of Hematology, Amsterdam UMC, location AMC, Amsterdam, The Netherlands
| | - B C Tanis
- Department of Internal Medicine, Groene Hart Ziekenhuis, Gouda, The Netherlands
- Department of General Practice Erasmus MC, Rotterdam, The Netherlands
| | - J W J van Esser
- Department of Internal Medicine, Amphia Ziekenhuis, Breda, The Netherlands
| | - C G Schaar
- Department of Internal Medicine, Gelre Ziekenhuis, Apeldoorn, The Netherlands
| | - H S Noordzij-Nooteboom
- Department of Internal Medicine, Van Weel Bethesda Ziekenhuis, Dirksland, The Netherlands
| | - E M G Jacobs
- Department of Internal Medicine, Elkerliek Ziekenhuis, Helmond, The Netherlands
| | - A O de Graaf
- Department of Laboratory Medicine - Laboratory of Hematology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - M Jongen-Lavrencic
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - M J P L Stevens-Kroef
- Department of human genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - T M Westers
- Department of Hematology, Amsterdam UMC, location VUmc, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - J H Jansen
- Department of Laboratory Medicine - Laboratory of Hematology, Radboud University Medical Center, Nijmegen, The Netherlands
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6
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Dimitriou M, Mortera-Blanco T, Tobiasson M, Mazzi S, Lehander M, Högstrand K, Karimi M, Walldin G, Jansson M, Vonlanthen S, Ljungman P, Langemeijer S, Yoshizato T, Hellström-Lindberg E, Woll PS, Jacobsen SEW. Identification and surveillance of rare relapse-initiating stem cells during complete remission after transplantation. Blood 2024; 143:953-966. [PMID: 38096358 PMCID: PMC10950475 DOI: 10.1182/blood.2023022851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 12/04/2023] [Accepted: 12/05/2023] [Indexed: 02/29/2024] Open
Abstract
ABSTRACT Relapse after complete remission (CR) remains the main cause of mortality after allogeneic stem cell transplantation for hematological malignancies and, therefore, improved biomarkers for early prediction of relapse remains a critical goal toward development and assessment of preemptive relapse treatment. Because the significance of cancer stem cells as a source of relapses remains unclear, we investigated whether mutational screening for persistence of rare cancer stem cells would enhance measurable residual disease (MRD) and early relapse prediction after transplantation. In a retrospective study of patients who relapsed and patients who achieved continuous-CR with myelodysplastic syndromes and related myeloid malignancies, combined flow cytometric cell sorting and mutational screening for persistence of rare relapse-initiating stem cells was performed in the bone marrow at multiple CR time points after transplantation. In 25 CR samples from 15 patients that later relapsed, only 9 samples were MRD-positive in mononuclear cells (MNCs) whereas flowcytometric-sorted hematopoietic stem and progenitor cells (HSPCs) were MRD-positive in all samples, and always with a higher variant allele frequency than in MNCs (mean, 97-fold). MRD-positivity in HSPCs preceded MNCs in multiple sequential samples, in some cases preceding relapse by >2 years. In contrast, in 13 patients in long-term continuous-CR, HSPCs remained MRD-negative. Enhanced MRD sensitivity was also observed in total CD34+ cells, but HSPCs were always more clonally involved (mean, 8-fold). In conclusion, identification of relapse-initiating cancer stem cells and mutational MRD screening for their persistence consistently enhances MRD sensitivity and earlier prediction of relapse after allogeneic stem cell transplantation.
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Affiliation(s)
- Marios Dimitriou
- Department of Medicine Huddinge, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Teresa Mortera-Blanco
- Department of Medicine Huddinge, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Magnus Tobiasson
- Department of Medicine Huddinge, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Stefania Mazzi
- Department of Medicine Huddinge, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Madeleine Lehander
- Department of Medicine Huddinge, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Kari Högstrand
- Department of Medicine Huddinge, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Mohsen Karimi
- Department of Medicine Huddinge, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
- Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment, Swedish Neuroscience Institute, Seattle, WA
| | - Gunilla Walldin
- Department of Medicine Huddinge, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Monika Jansson
- Department of Medicine Huddinge, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Sofie Vonlanthen
- Department of Clinical Immunology and Transfusion Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Per Ljungman
- Division of Hematology, Department of Medicine, Department of Cellular Therapy and Allogeneic Stem Cell Transplantation, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
- Karolinska Comprehensive Cancer Center, Stockholm, Sweden
| | - Saskia Langemeijer
- Department of Hematology, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Tetsuichi Yoshizato
- Department of Medicine Huddinge, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Eva Hellström-Lindberg
- Department of Medicine Huddinge, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Petter S. Woll
- Department of Medicine Huddinge, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Sten Eirik W. Jacobsen
- Department of Medicine Huddinge, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, Sweden
- Haematopoietic Stem Cell Biology Laboratory and MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
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7
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Oelschlaegel U, Winter S, Sockel K, Epp K, Schadt J, Röhnert MA, Krüger T, Ruhnke L, Bornhäuser M, Platzbecker U, Kroschinsky F, von Bonin M. MDS-PB13 Score - Blood based detection of aberrancies by flow cytometry in patients with suspected and confirmed Myelodysplastic Neoplasms. Leukemia 2024; 38:446-450. [PMID: 38228682 PMCID: PMC10844065 DOI: 10.1038/s41375-024-02141-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 01/03/2024] [Accepted: 01/05/2024] [Indexed: 01/18/2024]
Affiliation(s)
- Uta Oelschlaegel
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Dresden, Germany.
| | - Susann Winter
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Dresden, Germany
| | - Katja Sockel
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Dresden, Germany
| | - Katharina Epp
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Dresden, Germany
| | - Jonas Schadt
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Dresden, Germany
| | - Maximilian A Röhnert
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Dresden, Germany
| | - Thomas Krüger
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Dresden, Germany
| | - Leo Ruhnke
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Dresden, Germany
| | - Martin Bornhäuser
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Dresden, Germany
- National Center for Tumor Diseases (NCT), Dresden, Germany
| | - Uwe Platzbecker
- Clinic and Policlinic for Hematology, Cellular Therapy Hemostaseology and Infectiology, University Hospital Leipzig, Leipzig, Germany
| | - Frank Kroschinsky
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Dresden, Germany
| | - Malte von Bonin
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Dresden, Germany
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8
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Hasserjian RP, Germing U, Malcovati L. Diagnosis and classification of myelodysplastic syndromes. Blood 2023; 142:2247-2257. [PMID: 37774372 DOI: 10.1182/blood.2023020078] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 09/08/2023] [Accepted: 09/25/2023] [Indexed: 10/01/2023] Open
Abstract
ABSTRACT Myelodysplastic syndromes (MDSs) are neoplastic myeloid proliferations characterized by ineffective hematopoiesis resulting in peripheral blood cytopenias. MDS is distinguished from nonneoplastic clonal myeloid proliferations by the presence of morphologic dysplasia and from acute myeloid leukemia by a blast threshold of 20%. The diagnosis of MDS can be challenging because of the myriad other causes of cytopenias: accurate diagnosis requires the integration of clinical features with bone marrow and peripheral blood morphology, immunophenotyping, and genetic testing. MDS has historically been subdivided into several subtypes by classification schemes, the most recent of which are the International Consensus Classification and World Health Organization Classification (fifth edition), both published in 2022. The aim of MDS classification is to identify entities with shared genetic underpinnings and molecular pathogenesis, and the specific subtype can inform clinical decision-making alongside prognostic risk categorization. The current MDS classification schemes incorporate morphologic features (bone marrow and blood blast percentage, degree of dysplasia, ring sideroblasts, bone marrow fibrosis, and bone marrow hypocellularity) and also recognize 3 entities defined by genetics: isolated del(5q) cytogenetic abnormality, SF3B1 mutation, and TP53 mutation. It is anticipated that with advancing understanding of the genetic basis of MDS pathogenesis, future MDS classification will be based increasingly on genetic classes. Nevertheless, morphologic features in MDS reflect the phenotypic expression of the underlying abnormal genetic pathways and will undoubtedly retain importance to inform prognosis and guide treatment.
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Affiliation(s)
| | - Ulrich Germing
- Department of Hematology, Oncology, and Clinical Immunology, Heinrich-Heine University, Dusseldorf, Germany
| | - Luca Malcovati
- Department of Molecular Medicine, University of Pavia, Pavia, Italy
- Department of Hematology, Fondazione IRCCS Policlinico S. Matteo, Pavia, Italy
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9
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Abstract
Myelodysplastic syndromes/neoplasms (MDS) are a heterogeneous class of hematopoietic stem cell neoplasms characterized by ineffective hematopoiesis leading to peripheral cytopenias. This group of diseases is typically diagnosed using a combination of clinical, morphologic, and genetic criteria. Many studies have described the value of multiparametric flow cytometry (MFC) in the diagnosis, classification, and prognostication of MDS. This review summarizes the approach to MDS diagnosis and immunophenotypic characterization using MFC and describes the current state while highlighting future opportunities and potential pitfalls.
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Affiliation(s)
- Xueyan Chen
- Translational Science and Therapeutics Division, Fred Hutch Cancer Center, Seattle, WA, USA; Department of Laboratory Medicine and Pathology, University of Washington, 825 Eastlake Avenue East, Seattle, WA 98109, USA
| | - Ulrika Johansson
- SI-HMDS, Haematology, UHBW NHS Foundation Trust, Bristol Royal Infirmary, Upper Maudlin Street, Bristol, BS2 8HW, UK
| | - Sindhu Cherian
- Department of Laboratory Medicine and Pathology, University of Washington, 825 Eastlake Avenue East, Seattle, WA 98109, USA.
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10
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Therkelsen J, Traeden DW, Schjødt I, Andersen MK, Sjö LD, Hansen JW, Grønbaek K, Dimopoulos K. ProGraME: A novel flow cytometry algorithm for the diagnosis of low-risk myelodysplastic syndromes in patients with cytopenia. Eur J Haematol 2023; 111:851-862. [PMID: 37611916 DOI: 10.1111/ejh.14086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 08/04/2023] [Accepted: 08/08/2023] [Indexed: 08/25/2023]
Abstract
OBJECTIVES Flow cytometry (FC) is, together with morphology, genetics, and cytogenetics, used in the diagnostic assessment of cytopenia, as its value in evaluating bone marrow dysplasia been highlighted by several studies. However, despite the development of algorithms and guidelines, there is still a lack of standardization of the FC assessment of bone marrow dysplasia. METHODS By combining FC, together with morphological analysis and cytogenetic/molecular assessment in a training cohort of 209 patients, we created a novel score, ProGraME, which includes four parameters, each from a different cell lineage (Progenitor cells, Granulocytes, Monocytes, Erythroid precursors), solely based on relevant population gating. Points for ProGraME were attained for: lymphoid precursors ≤5% of all CD34+ cells (1.5 point); a granulocyte-to-lymphocyte side-scatter ratio ≤6 (1 point); a monocyte CD33-CV% ≥ 63 (2 points), and an erythroid precursor CD36-CV% ≥ 65 (2 points). RESULTS Using a cutoff of ≥2 as suggestive of dysplasia, ProGraME showed a sensitivity of 91% and a specificity of 81% in the training cohort and 95% and 75%, respectively, in an independent validation cohort of 159 patients. In addition, ProGraME had a very high negative predictive value of 97.1% and 97.8% in the training and validation cohorts, respectively, offering a useful tool for excluding bone marrow dysplasia. Finally, among the 23 CCUS patients that scored positive for dysplasia with ProGraME in the training cohort, 16 of them (69%) carried high-risk mutations, suggesting that FC might help identify early changes of dysplasia. CONCLUSIONS ProGraME can potentially optimize the FC diagnosis of low-risk myelodysplasia without minimal requirements of flow analysis other than accurate population gating.
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Affiliation(s)
- Jesper Therkelsen
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Hematology, Rigshospitalet, Copenhagen, Denmark
| | - Dicte Wilhjelm Traeden
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Hematology, Rigshospitalet, Copenhagen, Denmark
| | - Ida Schjødt
- Department of Hematology, Rigshospitalet, Copenhagen, Denmark
- Flow Cytometry Laboratory, Rigshospitalet, Copenhagen, Denmark
| | | | | | - Jakob Werner Hansen
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Hematology, Rigshospitalet, Copenhagen, Denmark
- Biotech Research and Innovation Centre, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kirsten Grønbaek
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Hematology, Rigshospitalet, Copenhagen, Denmark
- Biotech Research and Innovation Centre, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Konstantinos Dimopoulos
- Flow Cytometry Laboratory, Rigshospitalet, Copenhagen, Denmark
- Biotech Research and Innovation Centre, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Biochemistry, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
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11
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Saft L. The role of flow cytometry in the classification of myeloid disorders. PATHOLOGIE (HEIDELBERG, GERMANY) 2023; 44:164-175. [PMID: 37991530 PMCID: PMC10739577 DOI: 10.1007/s00292-023-01272-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/24/2023] [Indexed: 11/23/2023]
Abstract
The World Health Organization classification (WHO-HAEM5) and the International Consensus Classification (ICC 2022) of myeloid neoplasms are based on the integration of clinical, morphologic, immunophenotypic, and genomic data. Flow cytometric immunophenotyping (FCIP) allows the identification, enumeration, and characterization of hematopoietic cells, and is therefore a powerful tool in the diagnosis, classification, and monitoring of hematological neoplasms. The vast majority of flow cytometry (FCM) studies in chronic myeloid neoplasms focus on its role in myelodysplastic neoplasms (MDS). FCM can also be helpful for the assessment of myeloproliferative neoplasms (MPN) and MDS/MPN, including the early detection of evolving myeloid or lymphoid blast crisis and the characterization of monocytic subsets. The classification of acute myeloid leukemia (AML) is primarily based on cytogenetic and molecular findings; however, FCIP is needed for subclassification of AML, not otherwise specified (NOS; ICC)/AML defined by differentiation (WHO-HAEM5). The main role of FCM in AML remains in making a rapid diagnosis and as a tool for measurable residual disease monitoring. Machine learning and artificial intelligence approaches can be used to analyze and classify FCM data. This article, based on an invited lecture at the 106th Annual Meeting of the German Society of Pathology in 2023, reviews the role of FCM in the classification of myeloid neoplasms, including recent publications on the application of artificial intelligence.
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Affiliation(s)
- Leonie Saft
- Clinical Pathology and Cancer Diagnostics, Karolinska University Hospital and Institute, 171 76, Stockholm, Sweden.
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12
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Foucar K, Bagg A, Bueso-Ramos CE, George T, Hasserjian RP, Hsi ED, Orazi A, Tam W, Wang SA, Weinberg OK, Arber DA. Guide to the Diagnosis of Myeloid Neoplasms: A Bone Marrow Pathology Group Approach. Am J Clin Pathol 2023; 160:365-393. [PMID: 37391178 DOI: 10.1093/ajcp/aqad069] [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: 03/17/2023] [Accepted: 05/18/2023] [Indexed: 07/02/2023] Open
Abstract
OBJECTIVES The practicing pathologist is challenged by the ever-increasing diagnostic complexity of myeloid neoplasms. This guide is intended to provide a general roadmap from initial case detection, often triggered by complete blood count results with subsequent blood smear review, to final diagnosis. METHODS The integration of hematologic, morphologic, immunophenotypic, and genetic features into routine practice is standard of care. The requirement for molecular genetic testing has increased along with the complexity of test types, the utility of different testing modalities in identifying key gene mutations, and the sensitivity and turnaround time for various assays. RESULTS Classification systems for myeloid neoplasms have evolved to achieve the goal of providing a pathology diagnosis that enhances patient care, outcome prediction, and treatment options for individual patients and is formulated, endorsed, and adopted by hematologists/oncologists. CONCLUSIONS This guide provides diagnostic strategies for all myeloid neoplasm subtypes. Special considerations are provided for each category of testing and neoplasm category, along with classification information, genetic testing requirements, interpretation information, and case reporting recommendations based on the experience of 11 Bone Marrow Pathology Group members.
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Affiliation(s)
- Kathryn Foucar
- Department of Pathology, University of New Mexico, Albuquerque, NM, US
| | - Adam Bagg
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, US
| | - Carlos E Bueso-Ramos
- Department of Hematopathology, University of Texas MD Anderson Cancer Center, Houston, TX, US
| | - Tracy George
- Department of Pathology, University of Utah, Salt Lake City, UT, US
| | | | - Eric D Hsi
- Department of Pathology, Wake Forest School of Medicine, Winston-Salem, NC, US
| | - Attilio Orazi
- Department of Pathology, Texas Tech University, El Paso, TX, US
| | - Wayne Tam
- Department of Pathology and Laboratory Medicine, Donald and Barbara Zucker School of Medicine, Hofstra/Northwell, Greenvale, NY, US
| | - Sa A Wang
- Department of Hematopathology, University of Texas MD Anderson Cancer Center, Houston, TX, US
| | - Olga K Weinberg
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, US
| | - Daniel A Arber
- Department of Pathology, University of Chicago, Chicago, IL, US
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13
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Porwit A, Béné MC, Duetz C, Matarraz S, Oelschlaegel U, Westers TM, Wagner-Ballon O, Kordasti S, Valent P, Preijers F, Alhan C, Bellos F, Bettelheim P, Burbury K, Chapuis N, Cremers E, Della Porta MG, Dunlop A, Eidenschink-Brodersen L, Font P, Fontenay M, Hobo W, Ireland R, Johansson U, Loken MR, Ogata K, Orfao A, Psarra K, Saft L, Subira D, Te Marvelde J, Wells DA, van der Velden VHJ, Kern W, van de Loosdrecht AA. Multiparameter flow cytometry in the evaluation of myelodysplasia: Analytical issues: Recommendations from the European LeukemiaNet/International Myelodysplastic Syndrome Flow Cytometry Working Group. CYTOMETRY. PART B, CLINICAL CYTOMETRY 2023; 104:27-50. [PMID: 36537621 PMCID: PMC10107708 DOI: 10.1002/cyto.b.22108] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 11/20/2022] [Accepted: 11/29/2022] [Indexed: 01/18/2023]
Abstract
Multiparameter flow cytometry (MFC) is one of the essential ancillary methods in bone marrow (BM) investigation of patients with cytopenia and suspected myelodysplastic syndrome (MDS). MFC can also be applied in the follow-up of MDS patients undergoing treatment. This document summarizes recommendations from the International/European Leukemia Net Working Group for Flow Cytometry in Myelodysplastic Syndromes (ELN iMDS Flow) on the analytical issues in MFC for the diagnostic work-up of MDS. Recommendations for the analysis of several BM cell subsets such as myeloid precursors, maturing granulocytic and monocytic components and erythropoiesis are given. A core set of 17 markers identified as independently related to a cytomorphologic diagnosis of myelodysplasia is suggested as mandatory for MFC evaluation of BM in a patient with cytopenia. A myeloid precursor cell (CD34+ CD19- ) count >3% should be considered immunophenotypically indicative of myelodysplasia. However, MFC results should always be evaluated as part of an integrated hematopathology work-up. Looking forward, several machine-learning-based analytical tools of interest should be applied in parallel to conventional analytical methods to investigate their usefulness in integrated diagnostics, risk stratification, and potentially even in the evaluation of response to therapy, based on MFC data. In addition, compiling large uniform datasets is desirable, as most of the machine-learning-based methods tend to perform better with larger numbers of investigated samples, especially in such a heterogeneous disease as MDS.
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Affiliation(s)
- Anna Porwit
- Division of Oncology and Pathology, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
| | - Marie C Béné
- Hematology Biology, Nantes University Hospital, CRCINA Inserm 1232, Nantes, France
| | - Carolien Duetz
- Department of Hematology, Amsterdam UMC, VU University Medical Center Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Sergio Matarraz
- Cancer Research Center (IBMCC-USAL/CSIC), Department of Medicine and Cytometry Service, Institute for Biomedical Research of Salamanca (IBSAL) and CIBERONC, University of Salamanca, Salamanca, Spain
| | - Uta Oelschlaegel
- Department of Internal Medicine, University Hospital Carl-Gustav-Carus, TU Dresden, Dresden, Germany
| | - Theresia M Westers
- Department of Hematology, Amsterdam UMC, VU University Medical Center Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Orianne Wagner-Ballon
- Department of Hematology and Immunology, Assistance Publique-Hôpitaux de Paris, University Hospital Henri Mondor, Créteil, France
- Inserm U955, Université Paris-Est Créteil, Créteil, France
| | | | - Peter Valent
- Department of Internal Medicine I, Division of Hematology & Hemostaseology and Ludwig Boltzmann Institute for Hematology and Oncology, Medical University of Vienna, Vienna, Austria
| | - Frank Preijers
- Laboratory of Hematology, Department of Laboratory Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Canan Alhan
- Department of Hematology, Amsterdam UMC, VU University Medical Center Cancer Center Amsterdam, Amsterdam, The Netherlands
| | | | - Peter Bettelheim
- Department of Hematology, Ordensklinikum Linz, Elisabethinen, Linz, Austria
| | - Kate Burbury
- Department of Haematology, Peter MacCallum Cancer Centre, & University of Melbourne, Melbourne, Australia
| | - Nicolas Chapuis
- Laboratory of Hematology, Assistance Publique-Hôpitaux de Paris, Centre-Université de Paris, Cochin Hospital, Paris, France
- Institut Cochin, INSERM U1016, CNRS UMR, Université de Paris, Paris, France
| | - Eline Cremers
- Division of Hematology, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Matteo G Della Porta
- IRCCS Humanitas Research Hospital, Milan, Italy
- Department of Biomedical Sciences, Humanitas University, Milan, Italy
| | - Alan Dunlop
- Department of Haemato-Oncology, Royal Marsden Hospital, London, UK
| | | | - Patricia Font
- Department of Hematology, Hospital General Universitario Gregorio Marañon-IiSGM, Madrid, Spain
| | - Michaela Fontenay
- Laboratory of Hematology, Assistance Publique-Hôpitaux de Paris, Centre-Université de Paris, Cochin Hospital, Paris, France
- Institut Cochin, INSERM U1016, CNRS UMR, Université de Paris, Paris, France
| | - Willemijn Hobo
- Department of Internal Medicine I, Division of Hematology & Hemostaseology and Ludwig Boltzmann Institute for Hematology and Oncology, Medical University of Vienna, Vienna, Austria
| | - Robin Ireland
- Department of Haematology and SE-HMDS, King's College Hospital NHS Foundation Trust, London, UK
| | - Ulrika Johansson
- Laboratory Medicine, SI-HMDS, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | | | - 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, Institute for Biomedical Research of Salamanca (IBSAL) and CIBERONC, University of Salamanca, Salamanca, Spain
| | - Katherina Psarra
- Department of Immunology - Histocompatibility, Evangelismos Hospital, Athens, Greece
| | - Leonie Saft
- Clinical Pathology and Cancer Diagnostics, Karolinska University Hospital and Institute Solna, Stockholm, Sweden
| | - Dolores Subira
- Department of Hematology, Flow Cytometry Unit, Hospital Universitario de Guadalajara, Guadalajara, Spain
| | - Jeroen Te Marvelde
- Laboratory Medical Immunology, Department of Immunology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | | | - Vincent H J van der Velden
- Laboratory Medical Immunology, Department of Immunology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | | | - Arjan A van de Loosdrecht
- Department of Hematology, Amsterdam UMC, VU University Medical Center Cancer Center Amsterdam, Amsterdam, The Netherlands
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14
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Wang W, Khoury JD. Where diagnosis for myelodysplastic neoplasms (MDS) stands today and where it will go: The role of flow cytometry in evaluation of MDS. CYTOMETRY. PART B, CLINICAL CYTOMETRY 2023; 104:12-14. [PMID: 36573832 DOI: 10.1002/cyto.b.22110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 12/11/2022] [Accepted: 12/13/2022] [Indexed: 12/28/2022]
Affiliation(s)
- Wei Wang
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Joseph D Khoury
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, Nebraska, USA
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15
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Kern W, Westers TM, Bellos F, Bene MC, Bettelheim P, Brodersen LE, Burbury K, Chu SC, Cullen M, Porta MD, Dunlop AS, Johansson U, Matarraz S, Oelschlaegel U, Ogata K, Porwit A, Preijers F, Psarra K, Saft L, Subirá D, Weiß E, van der Velden VHJ, van de Loosdrecht A. Multicenter prospective evaluation of diagnostic potential of flow cytometric aberrancies in myelodysplastic syndromes by the ELN iMDS flow working group. CYTOMETRY. PART B, CLINICAL CYTOMETRY 2023; 104:51-65. [PMID: 36416672 DOI: 10.1002/cyto.b.22105] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 10/31/2022] [Accepted: 11/14/2022] [Indexed: 11/24/2022]
Abstract
BACKGROUND Myelodysplastic syndromes (MDS) represent a diagnostic challenge. This prospective multicenter study was conducted to evaluate pre-defined flow cytometric markers in the diagnostic work-up of MDS and chronic myelomonocytic leukemia (CMML). METHODS Thousand six hundred and eighty-two patients with suspected MDS/CMML were analyzed by both cytomorphology according to WHO 2016 criteria and flow cytometry according to ELN recommendations. Flow cytometric readout was categorized 'non-MDS' (i.e. no signs of MDS/CMML and limited signs of MDS/CMML) and 'in agreement with MDS' (i.e., in agreement with MDS/CMML). RESULTS Flow cytometric readout categorized 60% of patients in agreement with MDS, 28% showed limited signs of MDS and 12% had no signs of MDS. In 81% of cases flow cytometric readouts and cytomorphologic diagnosis correlated. For high-risk MDS, the level of concordance was 92%. A total of 17 immunophenotypic aberrancies were found independently related to MDS/CMML in ≥1 of the subgroups of low-risk MDS, high-risk MDS, CMML. A cut-off of ≥3 of these aberrancies resulted in 80% agreement with cytomorphology (20% cases concordantly negative, 60% positive). Moreover, >3% myeloid progenitor cells were significantly associated with MDS (286/293 such cases, 98%). CONCLUSION Data from this prospective multicenter study led to recognition of 17 immunophenotypic markers allowing to identify cases 'in agreement with MDS'. Moreover, data emphasizes the clinical utility of immunophenotyping in MDS diagnostics, given the high concordance between cytomorphology and the flow cytometric readout. Results from the current study challenge the application of the cytomorphologically defined cut-off of 5% blasts for flow cytometry and rather suggest a 3% cut-off for the latter.
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Affiliation(s)
| | - Theresia M Westers
- Department of Hematology, Amsterdam University Medical Centers, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | | | | | - Peter Bettelheim
- Department of Hematology, Elisabethinen Hospital, Linz, Upper Austria, Austria
| | | | - Kate Burbury
- Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Sung-Chao Chu
- Department of Hematology and Oncology, Buddhist Tzu Chi General Hospital, Hualien, Taiwan
| | - Matthew Cullen
- Haematological Malignancy Diagnostic Service, St James's University Hospital, Leeds, UK
| | - Matteo Della Porta
- Department of Biomedical Sciences, IRCCS Humanitas Research Hospital, Humanitas University, Milan, Italy
| | | | - Ulrika Johansson
- Laboratory Medicine, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Sergio Matarraz
- Cytometry Service (NUCLEUS), Department of Medicine and IBSAL, Cancer Research Center (IBMCC, University of Salamanca-CSIC), Salamanca, Spain and Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Salamanca, Spain
| | - Uta Oelschlaegel
- Department of Internal Medicine, University Hospital of Technical University Dresden, Dresden, Germany
| | - Kiyoyuki Ogata
- Metropolitan Research and Treatment Centre for Blood Disorders (MRTC Japan), Tokyo, Japan
| | - Anna Porwit
- Division of Pathology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Frank Preijers
- Department of Laboratory Medicine, Laboratory of Hematology, Radboudumc, Nijmegen, The Netherlands
| | - Katherina Psarra
- Immunology Histocompatibility Department, Evangelismos Hospital, Athens, Greece
| | - Leonie Saft
- Clinical Pathology and Cancer Diagnostics, Karolinska University Hospital and Institute, Stockholm, Sweden
| | - Dolores Subirá
- Department of Medical Immunology, Hospital Universitario de Guadalajara, Guadalajara, Spain
| | | | - Vincent H J van der Velden
- Laboratory Medical Immunology, Department of Immunology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Arjan van de Loosdrecht
- Department of Hematology, Amsterdam University Medical Centers, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, The Netherlands
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16
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Brunner AM, Leitch HA, van de Loosdrecht AA, Bonadies N. Management of patients with lower-risk myelodysplastic syndromes. Blood Cancer J 2022; 12:166. [PMID: 36517487 PMCID: PMC9751093 DOI: 10.1038/s41408-022-00765-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 11/30/2022] [Accepted: 12/01/2022] [Indexed: 12/15/2022] Open
Abstract
Myelodysplastic syndromes (MDS) are a heterogeneous group of hematopoietic stem cell disorders characterized by ineffective hematopoiesis with abnormal blood cell development (dysplasia) leading to cytopenias and an increased risk for progression to acute myeloid leukemia (AML). Patients with MDS can generally be classified as lower- (LR-MDS) or higher-risk (HR-MDS). As treatment goals for patients with LR-MDS and those with HR-MDS differ significantly, appropriate diagnosis, classification, and follow-up are critical for correct disease management. In this review, we focus on the diagnosis, prognosis, and treatment options, as well as the prediction of the disease course and monitoring of treatment response in patients with LR-MDS. We discuss how next-generation sequencing, increasing knowledge on mechanisms of MDS pathogenesis, and novel therapies may change the current treatment landscape in LR-MDS and why structured assessments of responses, toxicities, and patient-reported outcomes should be incorporated into routine clinical practice.
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Affiliation(s)
| | - Heather A Leitch
- Hematology, St. Paul's Hospital, University of British Columbia, Vancouver, BC, Canada
| | - Arjan A van de Loosdrecht
- Department of Hematology, Cancer Center Amsterdam, Amsterdam University Medical Center, VU University Amsterdam, Amsterdam, Netherlands
| | - Nicolas Bonadies
- Department of Hematology and Central Hematology Laboratory, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
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17
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Simoni Y, Chapuis N. Diagnosis of Myelodysplastic Syndromes: From Immunological Observations to Clinical Applications. Diagnostics (Basel) 2022; 12:1659. [PMID: 35885563 PMCID: PMC9324119 DOI: 10.3390/diagnostics12071659] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 07/04/2022] [Accepted: 07/04/2022] [Indexed: 11/24/2022] Open
Abstract
Myelodysplastic syndromes (MDS) constitute a very heterogeneous group of diseases with a high prevalence in elderly patients and a propensity for progression to acute myeloid leukemia. The complexity of these hematopoietic malignancies is revealed by the multiple recurrent somatic mutations involved in MDS pathogenesis and the paradoxical common phenotype observed in these patients characterized by ineffective hematopoiesis and cytopenia. In the context of population aging, the incidence of MDS will strongly increase in the future. Thus, precise diagnosis and evaluation of the progression risk of these diseases are imperative to adapt the treatment. Dysregulations of both innate and adaptive immune systems are frequently detected in MDS patients, and their critical role in MDS pathogenesis is now commonly accepted. However, different immune dysregulations and/or dysfunctions can be dynamically observed during the course of the disease. Monitoring the immune system therefore represents a new attractive tool for a more precise characterization of MDS at diagnosis and for identifying patients who may benefit from immunotherapy. We review here the current knowledge of the critical role of immune dysfunctions in both MDS and MDS precursor conditions and discuss the opportunities offered by the detection of these dysregulations for patient stratification.
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Affiliation(s)
- Yannick Simoni
- Institut Cochin, Université Paris Cité, CNRS UMR8104, INSERM U1016, 75014 Paris, France;
| | - Nicolas Chapuis
- Institut Cochin, Université Paris Cité, CNRS UMR8104, INSERM U1016, 75014 Paris, France;
- Assistance Publique-Hôpitaux de Paris, Centre-Université Paris Cité, Service d’Hématologie Biologique, Hôpital Cochin, 75014 Paris, France
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18
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Tria FP, Ang DC, Fan G. Myelodysplastic Syndrome: Diagnosis and Screening. Diagnostics (Basel) 2022; 12:1581. [PMID: 35885487 PMCID: PMC9319204 DOI: 10.3390/diagnostics12071581] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 06/26/2022] [Accepted: 06/27/2022] [Indexed: 11/16/2022] Open
Abstract
Myelodysplastic syndromes (MDS) are heterogeneous groups of clonal myeloid disorders characterized by unexplained persistent peripheral blood (PB) cytopenia(s) of one or more of the hematopoietic lineages, or bone marrow (BM) morphologic dysplasia in hematopoietic cells, recurrent genetic abnormalities, and an increased risk of progression to acute myeloid leukemia (AML). In the past several years, diagnostic, prognostic, and therapeutic approaches have substantially improved with the development of Next Generation Sequencing (NGS) diagnostic testing and new medications. However, there is no single diagnostic parameter specific for MDS, and correlations with clinical information, and laboratory test findings are needed to reach the diagnosis.
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Affiliation(s)
- Francisco P. Tria
- Section of Cellular Immunology and Molecular Pathology, Institute of Pathology, St. Luke’s Medical Center—Global City, Taguig 1634, Metro Manila, Philippines; (F.P.T.IV); (D.C.A.)
| | - Daphne C. Ang
- Section of Cellular Immunology and Molecular Pathology, Institute of Pathology, St. Luke’s Medical Center—Global City, Taguig 1634, Metro Manila, Philippines; (F.P.T.IV); (D.C.A.)
| | - Guang Fan
- Department of Hematopathology, Oregon Health & Science University, Portland, OR 97239, USA
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