Cytometry Part B: Clinical Cytometry最新文献

{"title":"Prognostic impact of immunophenotypic classification for newly diagnosed NPM1-mutated acute myeloid leukemia","authors":"Beatriz Martín-Herreros,&nbsp;Lourdes Cordón,&nbsp;Claudia Sargas,&nbsp;Samuel Romero,&nbsp;María Dolores Linares,&nbsp;Pilar Lloret,&nbsp;Irene Navarro-Vicente,&nbsp;Isabel Cano,&nbsp;Evelyn Acuña-Cruz,&nbsp;Laura Torres-Miñana,&nbsp;Rebeca Rodríguez-Veiga,&nbsp;David Martínez-Cuadron,&nbsp;Blanca Boluda,&nbsp;Eva Barragán,&nbsp;Amparo Sempere,&nbsp;Pau Montesinos","doi":"10.1002/cyto.b.70016","DOIUrl":"10.1002/cyto.b.70016","url":null,"abstract":"<p><i>NPM1</i> mutations are among the most frequent genetic alterations in acute myeloid leukemia (AML) and have been associated with several immunophenotypic features. This study aims to characterize the immunophenotypic profile of this entity at diagnosis using multiparametric flow cytometry and to evaluate the impact of phenotype classifications on prognosis. Immunophenotypic analysis enabled the identification and characterization of various populations previously described in this entity, including immature (CD117⁺ HLA-DR⁺), neutrophil-committed (CD117^{+/heterogeneous} HLA-DR⁻), and monocytic (with variable CD117 expression, HLA-DR⁺, and CD64⁺) leukemic cells, which were identified as leukemic expansions, as well as populations presenting immunophenotypic alterations. Cases were distributed in seven immunophenotypic patterns based on R-classification that considers the presence of the three previously described leukemic cell populations but independently of their proportion and relative distribution. Most of the patients included in this study (30, 33%) exhibited an immature and monocytic leukemic cells population (pattern 4), followed by those patients (16, 18%) with a predominant expansion of immature leukemic cells (pattern 1), and those (16, 18%) characterized by a neutrophil-committed leukemic population (pattern 2). Less frequent patterns included (11, 12%) neutrophil-committed and monocytic cells population (pattern 6), (7, 8%) coexistence of the three populations (pattern 7), (6, 7%) immature and neutrophil-committed leukemic cells population (pattern 5), and (5, 5%) predominant expansion of monocytic leukemic cells population (pattern 3). Our analysis indicated that cases with monocytic leukemic cells population predominance exhibit a trend towards a lower cumulative incidence of relapse compared to other leukemic populations, either as the predominant population or across different immunophenotypic patterns. However, differences did not reach statistical significance. These findings help us to contribute with additional information about the biological and immunophenotypic signature of <i>NPM1-</i>AML.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"110 2","pages":"118-127"},"PeriodicalIF":2.7,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146194229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prospective validation of podoplanin expression as a diagnostic biomarker of acute promyelocytic leukemia","authors":"Camilla Maria de Alencar Saraiva,&nbsp;Carla Roberta Peachazepi Moraes,&nbsp;Bruno Kosa Lino Duarte,&nbsp;Gislaine Borba Oliveira,&nbsp;Herton Luiz Alves Sales Filho,&nbsp;Paula de Melo Campos,&nbsp;Sara Teresinha Olalla Saad,&nbsp;Erich Vinicius De Paula","doi":"10.1002/cyto.b.22252","DOIUrl":"10.1002/cyto.b.22252","url":null,"abstract":"<p>Acute promyelocytic leukemia (APL) is a medical emergency that needs immediate diagnosis and treatment. Podoplanin, a transmembrane glycoprotein that binds CLEC-2 on platelets, was recently demonstrated to be abnormally expressed in leukemic blasts in APL, as opposed to other forms of AML, in a study using thawed primary cells. This study aimed to explore and validate the diagnostic accuracy of measuring podoplanin expression by flow cytometry in the differential diagnosis of APL and other forms of acute myeloid leukemia (AML) as part of the diagnostic work-up of all cases suspected of AML in an academic hematology center. Podoplanin expression was measured by flow cytometry in bone marrow samples obtained at disease presentation from all consecutive adult patients suspected of AML. Results from 24 APL patients were compared with those from 23 non-APL AML patients matched by age and sex. Markedly higher PDPN expression was observed in APL patients when compared to other AML patients, with an area under the curve of 0.92 (95%CI: 0.82–1.0, <i>p</i> &lt; 0.0001) for the percentage of positive cells. Combining an optimal cutoff of 7.66% for PDPN-positive blasts and 1691 for the mean fluorescence index of PDPN expression, APL was identified with a sensitivity of 87.5% and a specificity of 100%. Moreover, PDPN expression presented a negative correlation with platelet count and fibrinogen levels. PDPN expression measured by flow cytometry can accurately differentiate between APL and other forms of AML in a real-world clinical setting, contributing to the diagnosis of this form of acute leukemia. If confirmed in larger prospective studies, the negative association of PDPN expression with fibrinogen and platelet counts supports the concept that this biomarker can potentially contribute to the clinical characterization of APL.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"110 2","pages":"128-133"},"PeriodicalIF":2.7,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.b.22252","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145033111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"International Clinical Cytometry Society 2023 workload survey of clinical flow cytometry laboratories","authors":"D. Werner,&nbsp;M. A. Linden,&nbsp;L. E. Turner,&nbsp;F. Kreisel,&nbsp;A. Al-Attar,&nbsp;A. Dunlop,&nbsp;A. Ali,&nbsp;T. Denny,&nbsp;W. Kern,&nbsp;V. Litwin,&nbsp;G. Marti,&nbsp;H. Olteanu,&nbsp;C. Trindade,&nbsp;L. Zhang,&nbsp;B. Langworthy,&nbsp;P. K. Wallace,&nbsp;S. A. Monaghan","doi":"10.1002/cyto.b.22259","DOIUrl":"10.1002/cyto.b.22259","url":null,"abstract":"<p>Clinical flow cytometry laboratories are facing rising test volumes, greater assay complexity, and increasing requirements for quality control and assay validation. In response, the International Clinical Cytometry Society (ICCS) conducted a workload survey in early 2023 to gather updated information on assay volumes, complexity, staffing, and technology. Data analysis focused on identifying correlations between length of time to introduce new assays and other factors as a means to gain insight about laboratories that seem to be either adapting or struggling. Flow cytometry assays were categorized into 3 levels of technical/interpretative complexity: high (e.g., measurable/minimal residual disease (MRD assays)), moderate (e.g., leukemia/lymphoma assays (Assays_L&amp;L), excluding MRD assays), and low (e.g., CD4 count). Annual assays per staff member were calculated according to staff involved in case sign-out (Staff_Signout) or other laboratory operations (Staff_LabOps). Respondents were from 101 laboratories in the United States (69.3%), Canada (4.0%), and other countries (26.7%). Low, moderate, and high technical/interpretative complexity assays were performed in 85.1%, 97.0%, and 47.5% of all laboratories, respectively. Median annual total assays (Assays_Total) per laboratory were 3515 and, based on complexity, were 1518.5 (low), 1808.8 (moderate), and 350 (high). Among all laboratories, the median time (interquartile range) to introduce new Assays_L&amp;L was 6 mos. (4–12 mos.), to introduce MRD assays was 11 mos. (5–12 mos.), and to validate/go-live with new cytometers was 8 mos. (4–12 mos.); these times positively correlated with each other. This study confirmed significantly increased workload since the prior ICCS 2013 workload survey with a concurrent decrease in Staff_LabOps. Faster introduction of new assays correlated with other successes, including quicker validation of and going live with new cytometers. Among all laboratories, those that performed myeloid MRD assays versus those that did not were also found to be faster to introduce new assays. The need for sufficient staffing has been emphasized because laboratories with both higher annual volumes of myeloma MRD assays and higher ratios of Assays_Total per Staff_LabOps were slower to introduce new assays. “Lack of staff and/or time dedicated or protected for assay development” and, more generally, “staff number” were the most commonly identified major barriers for new assay development, with the former specifically linked to slower introduction of new assays among all laboratories.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"110 2","pages":"102-117"},"PeriodicalIF":2.7,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145399564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exercise affects systemic basophil responses in humans: Applying an automated and modified basophil activation test (mBAT) in a field study","authors":"T. C. Pelgrim,&nbsp;B. N. Jukema,&nbsp;L. Koopmans,&nbsp;C. C. W. G. Bongers,&nbsp;M. T. E. Hopman,&nbsp;E. F. Knol,&nbsp;N. Vrisekoop,&nbsp;L. Koenderman","doi":"10.1002/cyto.b.70017","DOIUrl":"10.1002/cyto.b.70017","url":null,"abstract":"<p>Basophils are effector cells in type I hypersensitivity reactions. Upon cross-linking of surface-bound (allergen-specific) IgE, basophils release a variety of mediators. Determining the activation of basophils ex vivo with anti-IgE (a basophil activation test or BAT) can be achieved using flow cytometry. However, this requires an experienced laboratory, hampering penetration of the BAT into general allergen diagnostics. Automation of the BAT could make this requirement redundant. Automation of the BAT enables rapid analysis in a field study setting of the effect of prolonged endurance exercise that can prime circulating basophils. A modified near-patient BAT (activation by anti-IgE and fMLF) was developed to identify basophils (SSC^Low and CD193^bright) and their activation status (based on expression of CD63, CD11b and CD62L) using blood samples taken from 7 healthy anonymous volunteers of the hospital's donor service. Due to logistic reasons, the modified BAT (mBAT) was developed at room temperature. Second, blood samples from 18 healthy volunteers were taken during a multiple day walking event to determine the effect of exercise on basophil activation in situ. Eosinophil (SSC^high and CD193^bright) and neutrophil (SSC^high and CD193^dim) activation were also measured as comparators. Anti-IgE- and fMLF-induced activation of basophils in whole blood of both groups showed reproducibility and optimal activation at 1 μg/mL and 0.1 μM, respectively. The field study showed that exercise led to activation of basophils in situ. The fully automated, 24/7 mBAT is feasible for near-patient analysis of priming and/or activation of innate immune cells. This can bring basophil activation testing by mBAT to peripheral care institutes as it does not depend on a specialized laboratory and/or personnel. This study indicates that prolonged exercise leads to activation of basophils in vivo, which might be used to study exercise intolerance in asthmatics.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"110 2","pages":"92-101"},"PeriodicalIF":2.7,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.b.70017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147456238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated CLL cell population detection using a weakly supervised approach and CLL MRD flow cytometry data","authors":"Wikum Dinalankara,&nbsp;Chandler Sy,&nbsp;Jiani Chai,&nbsp;Paul B. Barone,&nbsp;Luigi Marchionni,&nbsp;Paul D. Simonson","doi":"10.1002/cytob.70008","DOIUrl":"10.1002/cytob.70008","url":null,"abstract":"<p>Minimal/measurable residual disease detection is routinely performed as part of post-diagnostic treatment plans for many types of cancer, for which multiparameter flow cytometry is one possible modality frequently used. We propose a machine learning approach for binary prediction of minimal residual disease status with flow cytometry data. Our method involves the projection of cells from the original feature space to a low-dimensional embedding in which cells are clustered by similarity, and the cluster-wise cell proportions are used for prediction as well as regression. This is a weakly supervised approach in that the only annotation required for the training set data is the percentage of neoplastic cells present in each case. We demonstrate the applicability of our method with respect to a cohort of chronic lymphocytic leukemia patient data to obtain high levels of accuracy. We contrast our approach with other proposed machine learning methods for application to minimal residual disease prediction.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"110 2","pages":"77-91"},"PeriodicalIF":2.7,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cytob.70008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146212411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Issue Highlights—March 2026","authors":"Virginia Litwin","doi":"10.1002/cyto.b.70027","DOIUrl":"10.1002/cyto.b.70027","url":null,"abstract":"","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"110 2","pages":"71-72"},"PeriodicalIF":2.7,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147669003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flow cytometry-based monitoring of chimeric antigen receptor (CAR) T cells: Reagent selection, assay design, and clinical utility.","authors":"Jianhua Ling, Wei Wang, Sa A Wang","doi":"10.1002/cyto.b.70026","DOIUrl":"https://doi.org/10.1002/cyto.b.70026","url":null,"abstract":"<p><p>Accurate quantification of chimeric antigen receptor (CAR) T cells is essential for monitoring post-infusion CART expansion and persistence and for real-time clinical decision-making. Multiparameter flow cytometry (MFC) enables rapid, live-cell detection with absolute quantification and concurrent immunophenotypic characterization. This review focuses on the practical and technical aspects of flow cytometry-based CAR T-cell monitoring, including selection of CAR detection reagents (target-specific, construct-specific, and target-agnostic strategies), assay optimization, purpose-driven panel design, and matrix-appropriate validation for peripheral blood and other clinically relevant specimens. We also address assay considerations unique to gene-edited allogeneic CAR T-cell products, including the use of surrogate immunophenotypic approaches when construct-specific reagents are unavailable. Finally, we discuss the role of MFC in identifying CAR T-cell clonal expansions and in evaluating suspected secondary hematolymphoid neoplasms in the post-CAR T setting.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147497617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"110 3","pages":"201-220"},"PeriodicalIF":2.7,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148079047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Issue Highlights—January 2026","authors":"Francesco Lanza","doi":"10.1002/cytob.70007","DOIUrl":"10.1002/cytob.70007","url":null,"abstract":"&lt;p&gt;[Color figure can be viewed at wileyonlinelibrary.com]&lt;/p&gt;&lt;p&gt;This issue of Clinical Cytometry B deals with several topics which are relevant in either the hematology and oncology discipline, mostly focusing on multiple myeloma and malignant lymphoma. Two of these studies reported data on standardization of flow cytometry methods which may be of great value in several clinical situations. It is a personal pleasure to comment here on these interesting manuscripts.&lt;/p&gt;&lt;p&gt;The first paper of this issue was written by Deutsch-Biedermann et al. (&lt;span&gt;2026&lt;/span&gt;); it was related to the development of a one-tube flow cytometry panel for measurable residual disease (MRD) detection in multiple myeloma patients (MM). Recent data has clearly demonstrated that the achievement of MRD negativity after first-line therapy for MM is one of the strongest surrogate markers for both overall survival and progression-free survival and is now widely used as an endpoint in several clinical trials (Anderson et al., &lt;span&gt;2021&lt;/span&gt;; Mateos et al., &lt;span&gt;2019&lt;/span&gt;; Munshi et al., &lt;span&gt;2020&lt;/span&gt;). It is also known that flow cytometry represents the leading technique for MRD status assessment in MM and related diseases (Devitt et al., &lt;span&gt;2025&lt;/span&gt;). Furthermore, compliance with the International Myeloma working group (IMWG) Next Generation Flow (NGF) criteria for MRD negativity requires the absence of immunophenotypically abnormal and clonal plasma cells with a minimum sensitivity of 1 in 10&lt;sup&gt;5&lt;/sup&gt; nucleated cells in bone marrow aspirates using the EuroFlow standard method or a validated equivalent method. Interestingly, in this manuscript, authors have proposed a novel MRD panel based on the use of all EuroFlow recommended immunophenotypic markers (cytoplasmic light chain kappa and lambda, CD19, CD27, CD38, CD45, CD56, CD81, CD117, CD138) other than the CD200 marker, which allows the inclusion of a total of 11 fluorochromes in one tube (Terra et al., &lt;span&gt;2025&lt;/span&gt;). This protocol meets the quality specifications of the IMWG. This flow cytometry protocol showed higher sensitivity than the previously developed flow panel and showed concordant results with the EuroFlow NGF panel, thus sustaining the reliability and sensitivity of this approach for detecting MRD in MM patients.&lt;/p&gt;&lt;p&gt;In the paper by Groves et al. (&lt;span&gt;2026&lt;/span&gt;) the authors provide guidance for performing minor modifications to validated antibody panels designed to ensure consistent and accurate results in the immunophenotyping of hematopoietic cells in several diseases. However, it is well known that in unforeseen situations, such as unique or unusual immunophenotypes or supply chain issues, ad hoc modifications to these panels are strongly necessary (D'Addio et al., &lt;span&gt;2025&lt;/span&gt;; Kelleher et al., &lt;span&gt;2024&lt;/span&gt;; Lanza et al., &lt;span&gt;2025&lt;/span&gt;; Terra et al., &lt;span&gt;2025&lt;/span&gt;; Tian et al., &lt;span&gt;2024&lt;/span&gt;). This manuscript provides guidance for performing minor modificati","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"110 1","pages":"7-10"},"PeriodicalIF":2.7,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cytob.70007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146092413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"110 3","pages":"226-227"},"PeriodicalIF":2.7,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148090954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}