Cytometry Part B: Clinical Cytometry最新文献

Image-guided core needle biopsies (IG-CNB) represent a minimally invasive approach for obtaining tissue in patients with lymphadenopathy and suspected lymphoma. Despite their utility, diagnostic challenges persist, with lower efficacy compared with excisional biopsies. Our study aimed to evaluate the potential utility of incorporation of flow cytometry (FC) alongside immunohistochemistry (IHC) when performing IG-CNB for suspected lymphoproliferative diseases. Analyzing 170 consecutive cases, guided by ultrasound (n = 94) or computer tomography (n = 76), we employed a diagnostic algorithm, already established in our laboratory practice, utilizing three antibody cocktail-equipped tubes tailored for defining lymphomas, particularly those of B-cell origin. FC expedited the diagnostic process, yielding presumptive results in 87.6% of cases within 48 h, with a positive predictive value of 98%. Addition of FC to routine IHC enhanced the diagnostic rate from 91.2% to 95.3%, reducing IG-CNB failure rate by 45%, from 8.8% to 4.7%. This enhancement was particularly notable for deep-seated sites and in the setting of suspected disease recurrences. Consequently, FC emerges as a valuable adjunctive tool, allowing for the improvement of diagnostic performance, with a particular focus on the ability to quantify the expression of surface markers for targeted therapies, and holding the potential to diminish the necessity for repeat excisional biopsies subsequent to IG-CNB procedures.

The flow cytometry-based evaluation of TRBC1 expression has been demonstrated as a rapid and specific method for detecting T-cell clones in sCD3-positive TCRαβ+ mature T-cell lymphoma. The aim of the study was to validate the utility of surface (s) TRBC1 and cytoplastic (cy) TRBC1 assessment in detecting clonality of sCD3-negative peripheral T-cell lymphomas (PTCLs), as well as exploring the existence and characteristics of sCD3-negative clonal T-cell populations with uncertain significance (T-CUS). Evaluation of sTRBC1 and cyTRBC1 were assessed on 61 samples from 37 patients with sCD3-negative PTCLs, including 26 angioimmunoblastic T-cell lymphoma (AITL) patients and 11 non-AITL patients. The sCD3-negative T-CUS were screened from 1602 patients without T-cell malignancy and 100 healthy individuals. Additionally, the clonality of cells was further detected through T-cell gene rearrangement analysis. We demonstrated the monotypic expression patterns of cyTRBC1 in all sCD3-negative PTCLs. Utilizing the cyTRBC1 evaluation assay, we identified a novel and rare subtype of sCD3-negative T-CUS for the first time among 13 out of 1602 (0.8%) patients without T-cell malignancy. The clonality of these cells was further confirmed through T-cell gene rearrangement analysis. This subset exhibited characteristics such as sCD3-cyCD3 + CD4 + CD45RO+, closely resembling AITL rather than non-AITL. Further analysis revealed that sCD3-negative T-CUS exhibited a smaller clone size in the lymph node and mass specimens compared to AITL patients. However, the clone size of sCD3-negative T-CUS was significantly lower than that of non-AITL patients in both specimen groups. In conclusion, we validated the diagnostic utility of cyTRBC1 in detecting sCD3-negative T-cell clonality, provided a comprehensive analysis of sCD3-negative T-CUS, and established a framework and provided valuable insights for distinguishing sCD3-negative T-CUS from sCD3-negative PTCLs based on their phenotypic properties and clone size.

Clinical flow cytometry laboratories require quality control materials for assay development, validation, and performance monitoring, including new reagent lot qualification. However, finding suitable controls for populations with uncommonly expressed antigens or for rare populations, such as mast cells, can be difficult. To that end, we evaluated synthetic abnormal mast cell particles (SAMCP), developed together with, and manufactured by, Slingshot Biosciences. The SAMCP's were designed to phenotypically mimic abnormal neoplastic mast cells: they were customized to have the same light scatter and autofluorescence properties of mast cells, along with surface antigen levels of CD45, CD33, CD117, CD2, CD25, and CD30 consistent with that seen in mast cell disease. We evaluated several performance characteristics of these particles using ARUP's high sensitivity clinical mast cell assay, including limit of detection, off-target activity and FMO controls, precision, scatter properties of the particles utilizing several different cytometer platforms, and particle antigen stability. The phenotype of the SAMCP mimicked abnormal mast cells, and they could be distinguished from normal native mast cells. FMO controls demonstrated specificity of each of the markers, and no off-target binding was detected. The limit of detection of the particles spiked into normal bone marrow was found to be ≤0.003% in a limiting dilution assay. The mast cell particles were found to perform similarly on Becton Dickinson Lyric, Cytek Aurora, and Beckman Coulter Navios and CytoFLEX platforms. Within run and between run precision were less than 10% CV. SAMCP were stable up to 13 days with minimal loss of antigen fluorescence intensity. The SAMCP's were able to successfully mimic neoplastic mast cells based on the results of our high sensitivity mast cell flow cytometry panel. These synthetic cell particles represent an exciting and innovative technology, which can fulfill vital needs in clinical flow cytometry such as serving as standardized control materials for assay development and performance monitoring.

X-linked inhibitor of apoptosis (XIAP) deficiency is an infrequent inborn error of immunity caused by mutations in XIAP gene. Most cases present with absence of XIAP protein which can be detected by flow cytometry (FC), representing a rapid diagnostic method. However, since some genetic defects may not preclude protein expression, it is important to include a complementary functional test in the laboratory workup of these patients. L-selectin (CD62-L) is a molecule that is cleaved from the surface membrane of leukocytes upon stimulation of different receptors such as toll like receptors (TLRs) and nucleotide-binding oligomerization domain-like receptors (NLRs), including NOD2. Considering that XIAP deficiency impairs NOD2 signaling, we decided to assess CD62-L down-regulation by FC post-stimulation of neutrophils and monocytes with L18-muramyl Di-Peptide (L18-MDP), a NOD2 specific agonist, in order to develop a novel assay for the functional evaluation of patients with suspicion of XIAP defects. Whole blood samples from 20 healthy controls (HC) and four patients with confirmed molecular diagnosis of XIAP deficiency were stimulated with 200 ng/mL of L18-MDP for 2 h. Stimulation with 100 ng/mL of lipopolysaccharide (LPS) was carried out in parallel as a positive control of CD62-L shedding. CD62-L expression was evaluated by FC using an anti CD62-L- antibody and down-regulation was assessed by calculating the difference in CD62-L expression before and after stimulation, both in terms of percentage of CD62-L expressing cells (Δ%CD62-L) and median fluorescence intensity (ΔMFI%). Neutrophils and monocytes from XIAP deficient patients displayed a significantly diminished response to L18-MDP stimulation compared with HC (p < 0.0001), indicating a severely altered mechanism of CD62-L down-regulation following activation of NOD2-XIAP axis. On the other hand, the response to LPS stimulation was comparable between patients and heathy controls, suggesting preserved CD62-L shedding with a different stimulus. FC detection of CD62-L down-regulation in monocytes and neutrophils after whole blood stimulation with L18-MDP results in an effective and rapid functional test for the identification of XIAP deficient patients.

Peripheral blood lymphocyte phenotyping panels typically include CD45 for discrimination of the lymphocyte population, and fluorophore-conjugated monoclonal antibodies to identify T, B, and Natural Killer (NK) cells. While CD45 combined with side scatter is generally sufficient to clearly distinguish lymphocytes from monocytes in the majority of peripheral blood samples, it is challenging to accurately gate lymphocytes in samples from patients with monocytosis or significant lymphopenia, or from very young infants. Addition of a monocyte marker to lymphocyte phenotyping panels for monocyte exclusion has previously been evaluated for improved discrimination of lymphocytes, albeit largely in healthy donor adult samples. Here we evaluate the effect of the addition of CD14 to a standard lymphocyte phenotyping panel on total lymphocyte, T, B, and NK cell percentages in a predominantly pediatric population of patients under evaluation chiefly for immunodeficiency, immune-depletion, or immune reconstitution. Addition of CD14 to the standard lymphocyte phenotyping improved discrimination of lymphocytes from monocytes, resulted in decreased NK cell percentages, likely because CD16+ and/or CD56+ monocytes were included in the CD56+CD16+ NK cell gate with conventional gating, and although less significant, resulted in an increased percentage of B cells, since relatively larger B cells were likely gated out by more restrictive light scatter gating used with the conventional gating approach. The change in NK and B cell percentages were more pronounced in samples from patients below a year of age, and in patients who were relatively lymphopenic. These data suggest that addition of CD14 to conventional lymphocyte phenotyping panels that utilize CD45 versus side scatter gating results in significant improvement in the accuracy of lymphocyte gating, and accurate quantification of NK and B cells particularly in samples from infants and lymphopenic individuals.

Multiparameter flow cytometry data is visually inspected by expert personnel as part of standard clinical disease diagnosis practice. This is a demanding and costly process, and recent research has demonstrated that it is possible to utilize artificial intelligence (AI) algorithms to assist in the interpretive process. Here we report our examination of three previously published machine learning methods for classification of flow cytometry data and apply these to a B-cell neoplasm dataset to obtain predicted disease subtypes. Each of the examined methods classifies samples according to specific disease categories using ungated flow cytometry data. We compare and contrast the three algorithms with respect to their architectures, and we report the multiclass classification accuracies and relative required computation times. Despite different architectures, two of the methods, flowCat and EnsembleCNN, had similarly good accuracies with relatively fast computational times. We note a speed advantage for EnsembleCNN, particularly in the case of addition of training data and retraining of the classifier.

Meningeal infiltration in children with B acute lymphoblastic leukemia is one of the most serious complications. Timely diagnosis not only significantly enhances treatment efficacy but also leads to improve patient outcome and reduce risk of relapse. This is particularly crucial in low to middle income countries facing health constraints, where optimizing resources is essential. Conventional cytology (CC) study of cerebrospinal fluid (CSF) is considered in different countries to be the Gold-standard despite its low sensitivity (< 50%). The study of CSF by multiparametric flow cytometry (MFC) appears to be an alternative. The aim of our study was to assess MFC analytical performance compared with CC. Our cross sectional study was conducted over a six-month period in the biological hematology department. CSF samples underwent analysis for the presence of blasts using both CC and MFC. Cytological slides of the CSF were prepared by cytocentrifugation in a Shandon Cytospin 4™. Flow cytometric analysis was performed on the BD FACSLyric™ flow cytometer. All statistical analyses were performed using SPSS version 21.0 (SPSS Inc.). Agreement between the two methods was made using the Kappa index and χ² test. This study was approved by the local ethics committee. Sixty CSF samples from 39 children with B acute lymphoblastic leukemia were analyzed. Meningeal infiltration was detected respectively in 20% of cases by MFC and 5% of cases by CC, with a significant difference p = 0.006. Comparing the two methods, the Kappa coefficient was 0.35, indicating weak agreement between the two methods. Moreover, MFC positivity was higher even for hypocellular samples. Of the 51 hypocellular samples, eight were positive by MFC while they were negative by CC. MFC shows better sensitivity while retaining good specificity for the detection of meningeal involvement. MFC could therefore be a complementary method to CC for detecting blast cells in the central nervous system.

The assessment of T-cell clonality by flow cytometry has long been suboptimal, relying on aberrant marker expression and/or intensity. The introduction of TRBC1 shows much promise for improving the diagnosis of T-cell neoplasms in the clinical flow laboratory. Most laboratories considering this marker already have existing panels designed for T-cell workups and will be determining how best to incorporate TRBC1. We present this comprehensive summary of TRBC1 and supplemental case examples to familiarize the flow cytometry community with its potential for routine application, provide examples of how to incorporate it into T-cell panels, and signal caution in interpreting the results in certain diagnostic scenarios where appropriate.