The reliability of clinical flow cytometry assays hinges on the availability of robust assay controls that accurately reflect representative samples. Widely used conventional assay controls, such as cell lines, often fail to replicate the phenotypical and biophysical properties of representative primary samples resulting in gating variability and limited confidence in assay performance as certain markers may not be expressed. To address these limitations, we developed a custom synthetic multiple myeloma (MM) cell mimic using Slingshot Biosciences TruCytes® technology. Currently, the MM1.S cell line can be used as an assay control in a flow cytometry panel to evaluate key markers, B cell maturation antigen (BCMA) and G protein-coupled receptor, class C, group 5, member D (GPRC5D), on plasma cells (PCs) and B cells in bone marrow aspirate, for MM clinical trials. Although MM.1S shows strong expression of the key markers BCMA and GPRC5D, it lacks CD45 and CD19 which are needed for PC and B cell identification. We aimed to engineer a MM cell mimic to simulate the scatter properties and antigen density for our fresh MM bone marrow aspirate sample testing. Representative MM bone marrow mononuclear cells (BMMCs) were reviewed to find scatter properties and representative median fluorescence intensity (MFI) of CD45, CD19, CD38, CD138, BCMA, GPRC5D, CD56, and PD-L1 on PCs and B cells. We engineered the MM cell mimic with one population representing PCs and another population representing B cells, based on MM BMMC samples. The MM cell mimic overcame the lack of CD45 and CD19 expression and the divergent scatter and MFI profiles observed in traditional MM cell lines like MM1.S. Qualification studies demonstrated intra- and inter-assay precision (%CV ≤20%), robust inter-instrument reproducibility, post-reconstitution stability up to 7 days at 4°C, and closed-vial storage stability of up to 13 months at -20°C. In summary, these results establish the MM mimics as an improved and alternate assay control to MM1.S, facilitating longitudinal assay performance monitoring and ongoing quality assurance in clinical flow cytometry.

Accurate immunophenotypic evaluation of natural killer (NK)-cell neoplasms is challenging because NK-cells lack somatically rearranged antigen receptors, are comprised of phenotypically distinct subsets, and exhibit tissue-specific subset distribution. We developed a flow cytometry (FC) panel for NK-cell immunophenotypic analysis and clonality assessment and applied it to 120 specimens, including normal peripheral blood (PB), bone marrow (BM), lymph node (LN), and body fluids, as well as a series of NK-cell neoplasms and NK-cell clones of uncertain significance (NK-CUS). The expression ranges for NK-cell receptors (NKR) including killer immunoglobulin-like receptors (KIR, CD158) in the PB were consistent with those reported previously by other groups. The distribution of NK-cell subsets differed by the specimen type. While PB and BM NK-cells showed predominance of the CD56[dim] subset, LN and fluid samples were enriched for the CD56[bright] subset, resulting in higher CD94/NKG2A and lower KIR expression compared to PB. Epstein-Barr-virus (EBV)-positive NK/T-cell neoplasms exhibited a relatively consistent CD56[bright] CD16[-] CD94/NKG2A[+] CD57[-] KIR[-] immunophenotype that resembled normal CD56[bright] NK-cells, emphasizing the importance of immunophenotypic aberrancies and increased scatter properties rather than restricted KIR expression in diagnosing such neoplasms. NK-large granular lymphocytic leukemia (NK-LGLL) demonstrated a mature CD56[dim] phenotype with restricted KIR expression. Twelve cases fulfilled the proposed criteria for NK-CUS, comprising both putative cytomegalovirus (CMV)-related NK-cell clones and phenotypically distinct (likely) CMV-unrelated clones with more pronounced immunophenotypic abnormalities. Our findings suggest that interpretation of NK-cell clonality should take into account NK-cell subset composition and tissue-specific receptor expression. These results provide practical considerations for NK-cell immunophenotypic analysis and contribute to a better understanding of the role of FC in diagnosing such neoplasms.

Acute myeloid leukemia (AML) is characterized by high genotypic and immunophenotypic heterogeneity. We collected an extensive dataset containing 5366 flow cytometry files from 885 AML patients, stained with the EuroFlow acute leukemia orientation tube (ALOT) and AML/MDS panel, acquired in a standardized way at eight centers over a period of 10 years. Unsupervised clustering identified groups of patients based on FlowSOM-derived cell population percentages. In addition, we investigated immunophenotypic patterns in World Health Organization (WHO) patient classes and NPM1[mut] subclasses, both at the cell population and the individual marker level. Some WHO classes, for example, AML with t(8;21)(q22;q22)/RUNX1::RUNX1T1 or t(15;17)(q24;q21)/PML::RARA, showed homogeneous immunophenotypes. Characterization of maturation arrest using FlowSOM confirmed maturation arrest at early stages in distinct WHO classes. Finally, a machine learning model was trained to predict WHO genetic classes from immunophenotypic data. The model allowed accurate prediction in 77% of cases, reproducible in an independent validation cohort. In conclusion, we show that EuroFlow standardized protocols allow analysis of multi-centric data measured over an extended period of time. Computational analysis demonstrated inter- and intrapatient immunophenotypic heterogeneity and allowed prediction of genetic abnormalities.

Natural killer (NK) cell neoplasms span indolent to highly aggressive entities, and flow cytometric immunophenotyping is central to their detection and classification. However, distinguishing reactive from neoplastic NK cell expansions can be challenging because NK cells lack somatically recombined antigen receptors, and reactive states may produce restricted phenotypes that mimic clonality. This best-practices manuscript outlines a practical, flow cytometry-based approach to NK cell analysis that integrates (i) robust lineage definition and gating, (ii) subset-aware interpretation of CD16/CD56 patterns, (iii) inference of clonality using killer cell immunoglobulin-like receptor (KIR; CD158) repertoire restriction and other NK cell receptors. We highlight key pitfalls-particularly the limited utility of KIR-based clonality inference in CD56[bright]CD16[-] NK cells and the potential for adaptive NK cell expansions to appear KIR-restricted-and propose an operational reflex algorithm triggered by NK cell expansion and/or defined immunophenotypic abnormalities in screening tubes. Case-based examples illustrate common scenarios, including NK-large granular lymphocytic leukemia, extranodal NK/T-cell lymphoma with circulating CD56[bright]CD16[-] cells, reactive adaptive NK cell expansions, and concurrent neoplastic and reactive NK clones. This framework supports standardized, reproducible NK cell assessment and improves specificity of flow-based clonality inference in routine clinical practice.

We evaluated morphologic and immunophenotypic features of adult T-cell leukemia/lymphoma (ATLL) using morphology and flow cytometry (FCM), compared tumor cell proportions in bone marrow (BM) and peripheral blood (PB), and assessed whether these parameters could improve prognostication beyond existing indices for aggressive ATLL. We retrospectively analyzed PB and BM morphology, FCM, and clinical records of individuals newly diagnosed with ATLL at our institution from 2010 to 2024. Morphologic reevaluation was performed in 47 of 58 enrolled individuals, all with leukemic manifestations. ATLL cells showed heterogeneity. Cytoplasmic vacuoles were present in 61.7% of cases, including a previously undescribed pattern of small peripheral vacuoles (38.3%). Nuclear forms included flower-like (66.0%), cerebriform (10.6%), and small indented lymphocyte-like (36.2%) cells. Cells typically expressed CD4, CD25, CD2, and CD5. However, CD25 was negative in 26.3% of cases when assessed with a weakly conjugated fluorochrome. CD8, CD7, and CD56 were consistently absent, CD3 was variable, whereas TRBC1 showed preliminary variability in the limited subset. Both cytology (with more ATLL cells showing abnormal morphology in PB than in BM) and flow cytometry demonstrated a higher tumor burden in PB than in BM. FCM detected BM infiltration more sensitively than conventional BM smears. In this single-center derivation cohort without validation, the PB tumor load prognostic index (PBTL-PI), incorporating PB abnormal lymphocyte percentage (PB-PAL) and corrected calcium, showed excellent apparent discrimination (area under the curve [AUC] = 0.871). PBTL-PI outperformed the Japan Clinical Oncology Group prognostic index in risk stratification (log-rank p = 0.0002 vs. 0.0147) and prognostic accuracy (AUC: 0.871 vs. 0.738, DeLong's p = 0.024). However, these findings are exploratory and require independent validation. ATLL shows morphologic and immunophenotypic heterogeneity. Cytology and flow cytometry both confirmed higher tumor burden in PB (vs. BM). FCM improves the detection of BM infiltration. PBTL-PI may identify high-risk ATLL and guide risk-adapted management.

Circulating tumor plasma cells (CTCs) at diagnosis are independent prognostic markers in newly diagnosed multiple myeloma (NDMM). Flow cytometry (FC) enables sensitive and cost-effective CTC quantification, but prognostic cut-offs vary across studies. The methodological approach used for quantification may affect the determination of the CTC percentage. In this study we compare head-to-head two FC techniques [single-platform FC versus Next Generation Flow (NGF)] to measure CTC levels in NDMM patients. Methodological differences between the two techniques can be found in sample processing (NGF includes fixation and permeabilization steps that are not required for CTC quantification by single-platform FC) and analytical sensitivity, which is higher for NGF than for single-platform FC. The percentage of CTCs was simultaneously assessed with both techniques in the peripheral blood (PB) of 34 patients enrolled in the REAL MM trial (NCT03829371) at screening. Single-platform FC detected CTCs in 29/34 patients (85.3%) patients, while NGF detected CTCs in 31/34 patients (91.2%), including 2 cases that were negative by single-platform FC. The CTC percentage measured using the NGF technique (median 0.0049%, range 0%-0.377%) was significantly lower than that obtained using single-platform FC (median 0.009%, range 0%-0.59%) (p < 0.0001). Indeed, quantifying CTCs with FC after fixation and permeabilization (comparably to NGF) led to results that were similar to NGF. In conclusion, NGF demonstrated higher sensitivity than single-platform FC to detect CTCs at diagnosis in MM patients. Employing standardized techniques like NGF may avoid variability across different laboratories and centers.

Aberrant antigen expression on mast cells (MCs) is one of the most accurate diagnostic markers for clonal MC diseases (CMCD). Although the coexistence of normal and pathologic MCs is frequently seen, the disease characteristics associated with it have been minimally investigated. We aimed to gain further insight into the relevance of partial aberrancy for establishing the diagnosis and risk stratification of systemic mastocytosis (SM) and monoclonal MC activation syndromes (MMAS). In patients with MMAS or SM, MC load, KIT D816V variant allele fraction (VAF), immunophenotype, mutational profile, basal serum tryptase (BST), and hematology parameters were evaluated to characterize the coexistence of normal and aberrant MCs. From 207 patients with CMCD, 75% of patients with MMAS, 67% with non-advanced SM (non-AdvSM), and 27% with advanced SM (AdvSM) exhibited partial aberrancy. This turned out to be one of the most discriminative parameters between indolent and advanced subtypes. Partial aberrancy was associated with less severe disease characteristics, that is, more indolent subtype, lower MC burden, KIT D816V VAF and BST, a mature MC immunophenotype, hematological parameters more closely corresponding to the normal-range values, and in a subgroup of patients with an SM-AHN, a less complex mutational profile. Assessing the coexistence of normal and pathologic MCs is a widely available, fast, and sensitive diagnostic and prognostic tool and may also be used in SM disease follow-up and treatment monitoring.

Flow cytometric analysis of leukocytes and red blood cells (RBCs) for loss of GPI-linked proteins is the gold standard for the diagnosis of PNH. Assessment of mature RBCs is often confounded by recent transfusions and the variable survival of normal versus PNH erythrocytes. Analysis of immature RBCs (iRBCs) provides a more accurate reflection of the underlying marrow clone size compared with mature RBCs (mRBCs). CD71 (transferrin receptor) serves as a robust marker for identifying iRBCs, thereby enabling the evaluation of PNH clones. This approach is still under investigation and has not yet been incorporated into the guidelines. We evaluated it in a large cohort of patients to validate its utility. FCM-based screening of leukocytes was carried out using a single-tube five-color panel (CD45-V500, FLAER-AF488, CD157-PE, CD15-PC 5.5, CD64-APC). The three-color RBC tube (CD235a-FITC, CD59-PE, CD71-APCH7) was used only in cases in which the leukocyte PNH clone size was >1%. Clone sizes across different cell populations, CD59 staining intensity, and the ability to distinguish among normal RBCs and type II and type III clones were compared between mRBCs (CD71-) and iRBCs (CD71+). A total of 782 samples were screened over a period of 24 months for various indications, including AA, non-immune hemolytic anemia, and unexplained thrombosis. PNH clones with a leukocyte clone size >1% were detected in 120 samples. The iRBC-PNH clone size was significantly higher than the mRBC-PNH clone size (median [range]: 49.9% [0.8-97.3] vs. 12.0% [0-86.0]; p = 0.002). The iRBC-PNH clone size corresponded closely with those of neutrophils and monocytes (median [range]: 49.9% [1-97.3] vs. 54.5% [1-99.5] vs. 58.7% [6.3-98.5], respectively). The MFI of CD59 in iRBCs was higher than that in mRBCs (8996 vs. 5687; p < 0.001). Normal RBCs and type II and III clones were better delineated in iRBCs than in mRBCs. Among cases with clinical evidence of hemolysis and/or thrombosis, the iRBC-PNH clone size reflected the disease burden better than the mRBC-PNH clone size (median [range]: 80.4% [20-95.6] vs. 26.6% [1.1-85.6]). This study validates the role of CD71-based analysis of iRBC-PNH clones, which was found to improve the detection, delineation, and sizing of PNH RBC clones and to correlate better with leukocyte clone sizes and clinical features. Therefore, incorporation of CD71 into high-sensitivity FCM-based PNH screening is suggested.

Receptor occupancy (RO) assessments are a critical component of elucidating PK/PD/safety relationships during early clinical development. As an initial measure of target engagement, RO can inform the pharmacological activity, and RO data from nonclinical studies are often translated to support human dose projection when the therapeutic target is a membrane-bound protein. Currently, across the industry, RO measurements are typically performed using freshly collected blood samples that require real-time bioanalysis, often resulting in highly variable data, missed time points, substantial operational costs, and logistical challenges. Here, we describe a novel RO method that utilizes cryopreserved whole blood, representing a substantial process improvement and enhanced robustness of RO endpoints. Instead of measuring cell surface target engagement in freshly collected whole blood, this method utilizes whole blood that is cryopreserved at the time of collection without subsequent peripheral blood mononuclear cell (PBMC) isolation. This approach extends the sample stability window from 2 to 3 days to 12 months post-collection. Internal method development demonstrated that a 1:1 dilution of whole blood with freezing media followed by cryopreservation produced RO results in T cells comparable to those obtained from fresh blood. Follow-up studies confirmed that this observation extended to multiple target binding arms of multispecific T-cell engagers, as well as RO measurements in B-cell and monocyte targets. Additional studies evaluated the feasibility of implementing this method in clinical settings by assessing assay robustness, sample freezing conditions, and shipping methods.

In ISO 15189-accredited medical laboratories, estimation and management of measurement uncertainty (MU) is a fundamental requirement. However, both the theoretical and practical aspects of MU estimation in medical testing are still evolving. In the specific context of clinical flow cytometry, only a limited number of publications address this subject. A survey distributed to European Society of Clinical Cell Analysis members revealed that guidance in this area would be valuable, as current practices vary significantly across laboratories and countries. To address this, a dedicated working group was established to explore how MU could be implemented in flow cytometry laboratories in a manner that embeds it in the laboratory's quality system and that is consistent with ISO 15189:2022 requirements, with the view to avoid it becoming a mere compliance task. Given that a significant number of flow cytometry assays yield qualitative rather than quantitative results and considering the patient-focused, risk-based perspective of the 15189:2022 standards, we approached MU from the perspective of understanding process variability. This paper details and summarizes the result of our work. We present a set of recommendations aimed to help flow cytometry laboratories approach this subject effectively; providing guidance for the types of assays that may be suited for an estimated and monitored MU, and recommendations for how to adopt a structured, risk-based methodology to minimize sources of variation for all assays. This involves identifying sources of uncertainty throughout the analytical process, evaluating their impact, and prioritizing control efforts where the risk to result integrity and patient safety is greatest.

Published data on flow cytometric assessment of Classic Hodgkin lymphoma (CHL) are largely limited to lymph node biopsies, where histopathological and immunophenotypic findings are already available, thereby restricting its practical applicability. Real-world evidence demonstrating the additional diagnostic role of flow cytometric immunophenotyping (FCI) in CHL is limited. This study evaluated the utility of FCI in body fluids (BF) and bone marrow samples submitted for the diagnostic evaluation and staging of CHL in routine clinical practice. We studied 126 samples from 120 patients evaluated for CHL diagnosis or staging, including fine-needle aspirates (FNAs, n = 15), tissue biopsies (n = 6), bone marrow aspirates (BMAs, n = 76), and BF (n = 29). Samples were processed using a lyse-stain-wash protocol, acquired on BD-LSRFortessa, and analyzed using Kaluza software. A single-tube 16-color antibody panel (CD3, CD11b, CD13, CD15, CD19, CD20, CD30, CD33, CD38, CD40, CD45, CD64, CD71, CD73, CD95, and CD271) was used. The findings were correlated with the clinical, histopathological, and immunohistochemical data. CHL involvement was detected in 13 samples (5 FNAs, 5 fluids, 2 BMAs, 1 lymph node). The level of Hodgkin and Reed-Sternberg cells (HRS) ranged from 0.03% to 2.86% (median, 0.43%) in positive samples. HRS cells consistently expressed CD30, CD40, CD71, and CD95. FCI demonstrated excellent sensitivity and specificity in fluids, FNA, and core needle biopsy; however, it exhibited poor sensitivity in BMA, likely due to hemodilution or non-representative sampling. FCI complements histopathology by enabling the rapid and accurate detection of CHL involvement, particularly in BF and limited tissue samples such as FNA and small biopsies.