Cytometry Part B: Clinical Cytometry最新文献

{"title":"Consensus recommendations for technical standardization of flow cytometric measurable residual disease assessment in B-cell acute lymphoblastic leukemia: A report from The Cytometry Society, India.","authors":"Prashant Tembhare, Kunal Sehgal, Karthik Bommannan, Khaliqur Rahman, Sachin Jain, Nitin Dayal, Sitaram Ghogale, Ananthvikas Jayaram, Man Updesh Singh Sachdeva, Ritu Gupta, Papagudi G Subramanian, Prabhu Manivannan, Mohan Galande, Manasi Mundada, Asish Rath, Phaneendra Datari, Sweta Rajpal, Gaurav Chatterjee, Nilesh Deshpande, Kotteeswari Kathirvel, Kuldeep Singh, Bhausaheb Bagal, Sachin Punatar, Ambreen Pandrowala, Chetan Dhamne, Anil Handoo, Julio-Javier, Alexander Popov, Dalia Salem, David Westerman, Alberto Orfao","doi":"10.1002/cyto.b.70055","DOIUrl":"https://doi.org/10.1002/cyto.b.70055","url":null,"abstract":"<p><p>Measurable residual disease (MRD) assessment is a key determinant of risk stratification and treatment modification in B-cell acute lymphoblastic leukemia (B-ALL). Multicolour flow cytometry (MFC) is a globally adopted rapid and sensitive MRD technique. However, technical practices remain significantly variable across laboratories, compromising assay sensitivity, reproducibility, and comparability. Currently, systemic recommendations providing guidelines on the technical aspects of MFC-MRD in B-ALL are unavailable. The Cytometry Society (TCS)-India undertook a structured consensus process to standardize technical aspects of MFC-MRD testing. A two-round Delphi survey was conducted among laboratory professionals and clinicians across India to capture the prevailing practices and priorities. Consensus recommendations were prepared through survey findings and further refined during an in-person consensus congress with national and international experts from Australia, Egypt, Spain, and Russia. This document provides comprehensive recommendations across pre-analytic, analytic, and post-analytic phases of MFC-MRD including minimal antibody panel, best practices for sample collection, transport, and processing, Instrument setup, quality control, acquisition targets, gating strategies, approaches for LOD/LLOQ definition, hemodilution assessment, etc. A structured MRD report format with quality caveats is also provided. The recommendations are categorized into \"Must,\" \"Preferred,\" and \"Acceptable\" levels to suit diverse resource settings while promoting harmonization. Implementation of these standards will enhance assay sensitivity, reproducibility, and comparability, thereby strengthening MRD-guided clinical decision-making in B-ALL.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148668572","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":"Automated B-cell and plasma cell identification using unsupervised clustering by FlowSOM and an excel-based classification model.","authors":"Ethan James Gantana, Ernest Musekwa, Erica-Mari Nell, Zivanai Cuthbert Chapanduka","doi":"10.1002/cyto.b.70058","DOIUrl":"https://doi.org/10.1002/cyto.b.70058","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Manual gating for plasma cell (PC) identification in multiparametric flow cytometry (MFC) is time-consuming and operator-dependent, especially when PCs are scarce. Artificial intelligence approaches such as unsupervised clustering (e.g., FlowSOM) map high-dimensional data that still require expert interpretation. The primary aim of this work was to develop a lightweight, transparent, spreadsheet-based algorithm for a classification model that integrates with automated clustering outputs for standardized B-cell and PC identification in research flow cytometry datasets. Bone marrow aspirates were stained with a standard BD OneFlow™ PC screening tube (CD38, CD56, β2-microglobulin, CD19, cyIgκ, cyIgλ, CD45, CD138) and acquired on a BD FACSLyric™ flow cytometer. FCS files were exported to CellEngine cytometry software and singlet nucleated events underwent FlowSOM clustering (8 clusters/sample). Cluster-level median fluorescence intensities (MFIs) were exported to an Excel \"PC Trainer Classifier\" that (i) normalizes markers to an in-sample B-cell anchor, (ii) computes a PC&lt;sub&gt;score&lt;/sub&gt; with CD138 as a hard gate and CD38 as a soft gate, plus secondary features (CD19↓, CD45↓, CD56↑), (iii) applies a forced core fallback (highest CD38/CD138 core score) when strict criteria yield no PCs, and (iv) derives a NEO&lt;sub&gt;score&lt;/sub&gt; (CD56↑, CD19↓, CD45↓) for neoplastic phenotype. The rule-based classifier was trained on expert assigned PC and B-cell clusters from 40 samples (30 clonal and 10 polyclonal). Validation was done on a new set of 52 samples, independent of the model. Elements of the Excel formula design and error-proofing were co-developed with ChatGPT (OpenAI); all outputs were verified by the authors. Across 52 validation cases (8 clusters/case; 416 clusters total), B-cell detection achieved: Sensitivity 0.902 (0.79-0.96), Specificity 0.984 (0.96-0.99), Precision 0.885 (0.77-0.94), Accuracy 0.973 (0.95-0.99) and F1 0.893. PC identification achieved: Sensitivity 0.651 (0.54-0.75), Specificity 0.828 (0.79-0.86), Precision 0.458 (0.37-0.55), Accuracy 0.796 (0.76-0.83) and F1 0.537. A transparent Excel-based classifier integrated with FlowSOM clustering enables highly reproducible B-cell identification and provides a structured approach to PC classification in research flow cytometry datasets. While the B-cell classifier demonstrated excellent discriminatory performance, PC identification yielded moderate sensitivity and precision, likely reflecting underlying biological and phenotypic heterogeneity. Consequently, the PC classification component is best interpreted as a triage or augmented-intelligence tool intended to support, rather than replace, expert assessment. This approach provides a structured and auditable framework that reduces operator dependency and improves inter-case harmonization. Its interpretability, low cost and portability make it particularly suited to research laboratories operating in resource-variable settings. Further op","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148663593","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":"CD72 as a complementary B-lineage marker for longitudinal measurable residual disease surveillance after CD19 CAR-T therapy in R/R B-ALL.","authors":"Man Chen, Jing Zhou, Wei Zhao, Jing Long, Minjing Fu, Xian Zhang, Yi Li, Gailing Zhang, Hui Wang","doi":"10.1002/cyto.b.70057","DOIUrl":"https://doi.org/10.1002/cyto.b.70057","url":null,"abstract":"<p><p>This study aimed to evaluate the feasibility of CD72 as a complementary CD19-independent B-lineage gating marker for longitudinal measurable residual disease (MRD) surveillance in relapsed/refractory B-cell acute lymphoblastic leukemia (R/R B-ALL) following CD19 CAR-T therapy. Correlation analyses were performed in 66 B-ALL samples to compare MRD detection using CD72, CD19, and cytoplasmic CD79a. CD72 expression specificity was further evaluated in 129 leukemia patients. In addition, 129 patients with R/R B-ALL treated with autologous CD19 CAR-T therapy in registered clinical trials (ChiCTR-IIh-16008711; NCT03173417) between January 2021 and December 2022 were retrospectively analyzed, with follow-up continued until January 2025. CD72 gating showed excellent concordance with both CD19- and cCD79a-based strategies for MRD assessment. CD72 expression demonstrated high specificity in B-ALL, with a positivity rate of 95.77%, compared with 29.27% in AML and 23.53% in T-ALL. All 129 heavily pretreated patients achieved MRD-negative CR at day 28 after CAR-T infusion and subsequently underwent allo-HSCT, with a median interval of 54 days (range, 40-338). A total of 16 patients experienced MRD relapse during follow-up, including four clinically confirmed CD19-negative relapses that retained CD72 expression. Patients with pre-CAR-T MRD ≤1% showed earlier B-cell recovery than those with MRD >1% (median 30 [18-45] vs. 32 [26-79] days, p = 0.028). The MRD ≤1% cohort demonstrated significantly improved 3-year overall survival compared with the MRD >1% cohort (88.1% vs. 69.2%, p = 0.014). The 3-year cumulative incidence of MRD relapse was significantly lower in the MRD ≤1% cohort than in the MRD >1% cohort (3.96% vs. 17.95%, p = 0.019), while non-relapse mortality was also numerically lower in the MRD ≤1% cohort (5.92% vs. 17.95%, p = 0.053). Multivariate analysis identified KMT2A rearrangement, IKZF1 mutation, TP53 mutation, and elevated pre-CAR-T MRD as independent predictors of inferior outcomes. CD72 represents a feasible complementary B-lineage marker for longitudinal MRD surveillance following CD19 CAR-T therapy. Retention of CD72 expression in clinically confirmed CD19-negative relapses supports its potential utility when CD19 expression is lost after targeted therapy.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148663586","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":"Detailed analysis of TRBC1 distribution in T-cell subsets and its application in T-cell clonality assessment.","authors":"Anumeha Chaturvedi, Simpy Raj, Jagruti Patil, Twinkle Khanka, Aswathy Anilkumar, Sitaram G Ghogale, Nilesh Deshpande, Karishma Girase, Suresh Poojari, K Balaji, Manju Sengar, Bhausaheb Bagal, Hasmukh Jain, Sachin Punatar, Anant Gokarn, Navin Khattry, Dhanalaxmi Shetty, Sweta Rajpal, Pratyusha Gudapati, Nikhil Patkar, Gaurav Chatterjee, Sridhar Epari, Tanuja Shet, Papagudi G Subramanian, Sumeet Gujral, Prashant R Tembhare","doi":"10.1002/cyto.b.70054","DOIUrl":"https://doi.org/10.1002/cyto.b.70054","url":null,"abstract":"<p><p>Assessment of T-cell clonality is critical for diagnosing T-cell non-Hodgkin lymphomas (T-NHL). Flow cytometric T-cell receptor (TCR)-Vβ-repertoire analysis is specific but technically complex, multi-tube, and often limited in paucicellular specimens. T-cell receptor-beta-constant-region-1 (TRBC1) has emerged as a simpler alternative, but normal distribution ranges in clinically relevant T-cell subsets remain insufficiently characterized and data on direct comparison with TCR-Vβ restriction is limited. We prospectively analyzed 70 blood samples from healthy donors and 58 samples (bone marrow, peripheral blood, fine-needle aspirates, body fluids) from T-NHL patients. Multiparameter flow cytometry (MFC) was used for diagnostic immunophenotyping in T-NHL cases and for TRBC1 assessment in T-NHL cases and 28 immunophenotypic T-cell subsets in healthy individuals. In T-NHL, clonality was determined by TRBC1 restriction in aberrant T-cell populations and, where sufficient material was available, corroborated by TCR-Vβ repertoire analysis (IOTest Beta Mark).In healthy donors, median TRBC1-positive fractions across T-cell subsets ranged from 21.39% to 78.61%, with narrow 99% confidence intervals in major CD4⁺ and CD8⁺ compartments. Minor subsets occasionally showed extreme values (7%-93%) but remained polyclonal by TCR-Vβ analysis, leading to thresholds of ≤6% or ≥94% TRBC1 positivity as indicative of clonality in our cohort. Among 57 evaluable T-NHL cases, all CD3-positive neoplastic populations showed monotypic TRBC1 expression, with 100% concordance with TCR-Vβ results in 18 tested cases. TRBC1 was non-informative on surface-CD3-negative T-NHL, although cytoplasmic staining was sometimes helpful. Flow cytometric TRBC1 analysis is a rapid, cost-effective, single-tube method for T-cell clonality assessment, with applicability to small T-cell subsets such as paucicellular and measurable residual disease samples.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148629724","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":"Automating clinical history extraction for flow cytometry panel selection using an EHR-integrated large language model.","authors":"Rebecca Rojansky, Timothy Keyes, Jean Oak","doi":"10.1002/cyto.b.70051","DOIUrl":"https://doi.org/10.1002/cyto.b.70051","url":null,"abstract":"<p><p>Flow cytometry immunophenotyping is essential for diagnosing hematologic malignancies, but accurate antibody panel selection depends on clinical context that is often fragmented across the electronic health record (EHR). At our institution, clinical laboratory scientists (CLS) use a standardized decision-tree algorithm incorporating specimen characteristics, laboratory values, and prior diagnoses to select panels. This process requires manual review and synthesis of longitudinal clinical documentation and remains time-intensive. We evaluated whether ChatEHR-an institutionally developed, EHR-integrated large language model (LLM) platform-could automate clinical history extraction and support flow cytometry panel selection across 100 cases. Performance was compared with the current CLS-driven workflow using hematopathologist-reviewed panel selections as the reference standard. ChatEHR achieved comparable accuracy to CLS in extracting and categorizing prior hematologic diagnoses (78% vs. 78%). Average processing time was 20.3 s for ChatEHR versus 41 s for manual review, corresponding to an estimated annual reduction of approximately 120 staff hours. Direct panel selection accuracy was lower for ChatEHR (47% vs. 78%), primarily due to errors in deterministic protocol execution and structured data interpretation. Major error categories included incorrect decision-tree logic (39%), diagnostic conflation (22%), failure to retrieve or apply clinical history (22%), laboratory value misinterpretation (9%), and hallucination of nonexistent panels (7%). ChatEHR demonstrated strong performance in extracting and classifying clinical history but was less reliable for deterministic protocol execution and structured data interpretation. Integration of LLM-based clinical history extraction with rules-based laboratory algorithms provides a practical hybrid workflow that preserves diagnostic reliability while reducing manual chart review burden. This approach enables scalable automation while maintaining appropriate hematopathologist oversight in clinical flow cytometry workflows.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148419446","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":"Plasmacytoid dendritic cell proliferation can be clonally related to early T-cell precursor acute lymphoblastic leukemia.","authors":"Germain Simon, Aurore Keutgens, Benjamin Koopmansch, Adrien de Voeght, Mickael Simul, Loïse Schonbrodt, Rafael Fernandez Carazo, Frédéric Lambert, André Gothot, Françoise Tassin, Jacques Foguenne","doi":"10.1002/cyto.b.70053","DOIUrl":"https://doi.org/10.1002/cyto.b.70053","url":null,"abstract":"","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148403790","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":"Effects of washing procedures on cell loss in different diagnostic flow cytometry sample types.","authors":"Gunnhild Vatne Leirvik, Trude Westgård, Mona Høysæter Fenstad, Henning Sørensen Øfsteng, Toril Holien","doi":"10.1002/cyto.b.70052","DOIUrl":"https://doi.org/10.1002/cyto.b.70052","url":null,"abstract":"","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148390130","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":"High-parameter flow cytometry for clinical laboratories—Worth it or not?","authors":"Ahmad Al-Attar,&nbsp;Thomas C. Beadnell,&nbsp;Robert J. Durso,&nbsp;Veronica Nash,&nbsp;Fernando Ortiz,&nbsp;Sagar Patil,&nbsp;Nina Rolf,&nbsp;Amanda Scott,&nbsp;Xuehai Wang","doi":"10.1002/cyto.b.70021","DOIUrl":"10.1002/cyto.b.70021","url":null,"abstract":"","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"110 4","pages":"301-304"},"PeriodicalIF":2.9,"publicationDate":"2026-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147303463","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":"Measurable residual disease by multicolor flow cytometry in acute myeloid leukemia: A comparison of peripheral blood and bone marrow","authors":"Jonas Schadt,&nbsp;Malte von Bonin,&nbsp;Uta Oelschlägel,&nbsp;Christoph Röllig,&nbsp;Christian Thiede,&nbsp;Leo Ruhnke,&nbsp;Martin Bornhäuser,&nbsp;Sebastian Brenner,&nbsp;Maximilian Alexander Röhnert","doi":"10.1002/cyto.b.70019","DOIUrl":"10.1002/cyto.b.70019","url":null,"abstract":"<p>Measurable residual disease (MRD) monitoring by multiparameter flow cytometry (MFC) is well established in bone marrow (BM) samples for acute myeloid leukemia (AML), but its use in peripheral blood (PB) remains less developed. We adapted a semi-automated and well validated MFC-MRD assay, originally developed for BM, to PB aiming to evaluate its applicability and concordance with established methods. To transfer the MFC-MRD assay from BM to PB, we incorporated population-specific reference values derived from healthy and chemotherapy-exposed non-AML controls. MRD detection was based on a combined aberrant leukemia associated immunophenotype (aLAIP) and different from normal (DfN) approach. We compared MFC-MRD detection in paired PB and BM samples and evaluated concordance with molecular MRD (Mol-MRD) diagnostics. Additional analyses included assessment of mast cells as markers for BM hemodilution as well as time requirements for analyses. Reference values for aberrant populations in PB were generally lower than in BM, particularly considering immature markers. At follow-up, MFC-MRD positivity was less common in PB than in BM, leading to a concordance rate of 73.7%. Both quantitative and qualitative differences in aberrant antigen expression between PB and BM were observed. Most cases of MRD positivity were characterized by newly emerging aberrant features rather than persistent ones. Concordance between MFC-MRD from PB and Mol-MRD from BM was 64.6%, similar to that of MFC-MRD from BM versus Mol-MRD from BM (58.5%). Most discordant cases (MFC-MRD^pos/Mol-MRD^neg) may reflect clonal hematopoiesis or limited spectrum of molecular panels. Mast cell quantification proved useful in identifying hemodiluted BM samples, which comprised ~15% of cases. Inter-rater agreement for MRD detection was strong (<i>Kα</i> &gt; 0.8). The MFC-MRD gating and evaluation was rapid (~2 min/sample in both PB and BM). The adapted MFC-MRD assay is feasible and robust in PB, offering a fast and reproducible alternative to BM-based MRD monitoring. However, the prognostic relevance of the proposed method needs to be validated in a prospective cohort of patients.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"110 4","pages":"259-265"},"PeriodicalIF":2.9,"publicationDate":"2026-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.b.70019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146200398","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":"Mature T-cell leukemia/lymphoma with an NK-like immunophenotype: A report of 7 cases","authors":"Wei J. Wang,&nbsp;Sa A. Wang,&nbsp;Hong Fang,&nbsp;Jeffrey L. Jorgensen,&nbsp;Shimin Hu,&nbsp;Lianqun Qiu,&nbsp;Jie Xu,&nbsp;L. Jeffrey Medeiros,&nbsp;Wei Wang","doi":"10.1002/cyto.b.70020","DOIUrl":"10.1002/cyto.b.70020","url":null,"abstract":"<p>Distinguishing T-cell from NK-cell neoplasms can occasionally be challenging, as neoplastic T cells can lose T-cell markers such as surface CD3 (sCD3) and CD5 while acquiring NK-cell markers such as CD16, CD56, and CD94. In this study, we present a series of 7 mature T-cell lymphoma/leukemia cases with NK-like immunophenotypes to clarify diagnostic approaches for lineage determination. The cohort included 3 cases of peripheral T-cell lymphoma, not otherwise specified, 2 cases of T-large granular lymphocytic leukemia, and 2 cases of hepatosplenic T-cell lymphoma. In all cases, flow cytometry immunophenotypic analysis showed that the neoplastic cells exhibited an NK-like immunophenotype characterized by expression of CD56 and CD94 in all 7 cases, with 4 cases also positive for CD16. Concurrently, the neoplastic cells in all cases were negative for the T-cell markers, including sCD3, CD4, CD5, TCRαβ, TCRγδ, and TRBC1 by flow cytometry. These immunophenotypic features mimicked NK cells. But in <i>T-cell receptor</i> (<i>TCR</i>) gene rearrangement analysis, all 7 cases had monoclonal <i>TRG</i> rearrangements, and 4 cases also showed concurrent <i>TRB</i> rearrangements. Immunohistochemical analysis showed that all 6 tested cases were positive for BCL11B, and 1 case was positive for TCRαβ. Additionally, 2 of 3 cases assessed using a T-cell-specific CD3 antibody were positive for cytoplasmic CD3 by flow cytometry. In summary, this study illustrates that neoplastic T cells can show an NK-like immunophenotype. Features useful for supporting T-lineage in this context include cytoplasmic CD3 expression assessed using a T-cell-specific CD3 antibody, clonal <i>TCR</i> gene rearrangement, BCL11B expression, and detection of TCRαβ, TCRγδ, or TRBC by immunohistochemistry.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"110 4","pages":"288-296"},"PeriodicalIF":2.9,"publicationDate":"2026-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.b.70020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146257433","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}