Cytometry Part B: Clinical Cytometry最新文献

BH3 profiling can assess global mitochondrial priming and dependence of leukemic cells on specific BH3 anti-apoptotic proteins such as BCL-2. In acute myeloid leukemia (AML), proof-of-concept prognostic studies have been performed on archived samples variably accounting for molecular genetics. We undertook a single-center feasibility study of a simplified flow-based assay to determine the absolute mitochondrial priming and BCL-2 dependence in consecutive AML patients. When possible, results on the leukemic fraction were normalized to the cognate lymphocyte population (relative priming and BCL-2 dependence). Samples from 97 (89.8%) of the 108 referred patients were successfully processed. Relative priming and BCL-2 dependence could be determined in 62 (67.4%) and 67 (62.0%) samples, respectively. Absolute mitochondrial priming was lower in patients having previously failed intensive chemotherapy compared to chemotherapy-naïve patients (p = 0.01), but its prognostic impact was limited. Conversely, relative BCL-2 independence tended to predict worse EFS (HR = 2.51, p = 0.07) and OS (HR = 2.79, p = 0.10) independently of adverse genetic risk. Our results show that simplified BH3 profiling can be prospectively assessed in AML patients but that its prognostic use may require internal normalization. Future studies should compare its relevance with other functional assays such as ex vivo drug testing or BH3 protein expression.

Flow cytometry is a high-throughput, high-dimensional technique that generates large sets of single-cell data. Prior to analyzing this data, it is common to exclude any events that contain two or more cells, multiplets, to ensure downstream analysis and quantification is of single-cell events, singlets, only. The process of singlet discrimination is critical yet fundamentally subjective and time-consuming; it is performed manually by the user, where the proper exclusion of multiplets depends on the user's expertise and often varies from experiment to experiment. To address this problem, we have developed an algorithm to automatically discriminate singlets from other unwanted events such as multiplets and debris. Using parameters derived from imaging, the algorithm first identifies high-density clusters of events using a density-based clustering algorithm, and then classifies the clusters based on their properties. Multiplets are discarded in the first step, while singlets are distinguished from debris in the second step. The algorithm can use different strategies on imaging feature selection-based user's preferences and imaging features available. In addition, the relative importance of singlets precision vs. sensitivity can be further tweaked via a density coefficient adjustment. Twenty-two datasets from various sites and of various cell types acquired on the BD FACSDiscover™ S8 Cell Sorter with CellView™ Image Technology were used to develop and validate the algorithm across multiple imaging feature sets. A consistent singlets precision >97% with a solid >88% sensitivity has been demonstrated with a LightLoss feature set and the default density coefficient. This work yields a high-precision, high-sensitivity algorithm capable of objective and automated singlet discrimination across multiple cell types using various imaging-derived parameters. A free FlowJo™ Software plugin implementation is available for simple and reproducible singlet discrimination for use at the beginning of any user's workflow.

The FDA-approved ClearLLab 10C Reagents Panel (Beckman Coulter) simplified the diagnosis of leukemias and lymphomas by flow cytometry. However, the requirement of using 3 × 10⁶ cells/mL cannot be met for paucicellular samples. Therefore, we tested whether this 10-color panel can be reliably employed to analyze specimens with low cell concentrations. Serial dilutions of 16 samples (5 normal, 11 abnormal), yielding concentrations ranging from 3.0 × 10⁶ to 0.0469 × 10⁶ cells/mL (64-fold difference), were stained using the B-cell and T-cell panels of the ClearLLab 10C system, and mean fluorescence intensity (MFI) was measured for each antibody. For each cell dilution, the deviation from the value obtained with the FDA-approved concentration of 3.0 × 10⁶ cells/mL was calculated. The agreement between the highest and lowest cell concentration data was evaluated by the Bland and Altman method, Pearson's and Spearman's correlation analyses, and linear regression. In all patients, the antigen expression pattern was similar at all cell concentrations tested, and the mean deviation of the MFI from the value obtained using 3.0 × 10⁶ cells/mL never exceeded 10% for any of the antibodies. The Bland-Altman method demonstrated the similarity between results obtained with the FDA-approved cell concentration and a 64-fold diluted cell suspension, and a high positive correlation was found between MFI acquired under these two conditions. The tests utilizing the lowest density of cells yielded the same patterns of antigen expression in all patients as those performed with the FDA-approved concentration, documenting a 100% concordance between these two protocols. The ClearLLab 10C panel can reliably determine the expression of markers of leukemias and lymphomas in paucicellular samples containing as little as 0.0469 × 10⁶ cells/mL (64-fold lower than the FDA-approved concentration). This finding markedly expands the applicability of the ClearLLab 10C platform in a clinical setting.

Rare acute leukemia (AL) components or subtypes such as blastic plasmacytoid dendritic cell neoplasm (BPDCN) or early T-cell precursor acute Lymphoblastic Leukemia (ETP-ALL) can be difficult to detect by routine flow cytometry due to their immunophenotypes overlapping with other poorly differentiated AL. We hypothesized that using standardized EuroFlow™ Consortium approach could better diagnose such entities among cases that previously classified as acute myeloid leukemia (AML)-M0, AML with minimal differentiation, AML with myelodysplasia-related changes without further lineage differentiation, and AL of ambiguous lineage. In order to confirm this hypothesis and assess whether these AL subtypes such as BPDCN and ETP-ALL had previously gone undetected, we reanalyzed 49 banked cryopreserved sample cases using standardized EuroFlow™ Consortium panels. We also performed target sequencing to capture the mutational commonalities between these AL subtypes. Reanalysis led to revised or refined diagnoses for 23 cases (47%). Of these, five diagnoses were modified, uncovering 3 ETP-ALL and 2 typical BPDCN cases. In 12 AML cases, a variable proportion of immature plasmacytoid dendritic cell and/or monocytic component was newly identified. In one AML case, we have identified a megakaryoblastic differentiation. Finally, in five acute lymphoblastic leukemia (ALL) cases, we were able to more precisely determine the maturation stage. The application of standardized EuroFlow flow cytometry immunophenotyping improves the diagnostic accuracy of ALs and could impact treatment decisions.

Cervical cancer (CC) is the fourth most common malignant tumor in women worldwide. Detecting different biomarkers together on single cells by novel method mass cytometry could contribute to more precise screening. Liquid-based cytology (LBC) cervical samples were collected (N = 53) from women categorized as normal and precancerous lesions. Human papillomavirus was genotyped by polymerase chain reaction, while simultaneous examination of the expression of 29 proteins was done by mass cytometry (CyTOF). Differences in cluster abundances were assessed with Spearman's rank correlation as well as high dimensional data analysis (t-SNE, FlowSOM). Cytokeratin (ITGA6, Ck5, Ck10/13, Ck14, Ck7) expression patterns allowed determining the presence of different cells in the cervical epithelium. FlowSOM analysis enabled to phenotype cervical cells in five different metaclusters and find new markers that could be important in CC screening. The markers Ck18, Ck18, and CD63 (Metacluster 3) showed significantly increasing associated with severity of the precancerous lesions (Spearman rank correlation rho 0.304, p = 0.0271), while CD71, KLF4, LRIG1, E-cadherin, Nanog and p53 (Metacluster 1) decreased with severity of the precancerous lesions (Spearman rank correlation rho -0.401, p = 0.0029). Other metaclusters did not show significant correlation, but metacluster 2 (Ck17, MCM, MMP7, CD29, E-cadherin, Nanog, p53) showed higher abundance in low- and high-grade intraepithelial lesion cases. CyTOF appears feasible and should be considered when examining novel biomarkers on cervical LBC samples. This study enabled us to characterize different cells in the cervical epithelium and find markers and populations that could distinguish precancerous lesions.

Automated analysis of flow cytometry data can improve objectivity and reduce analysis time but has generally required work by software and algorithm experts. Here, we investigated the performance of BD ElastiGate™ Software (hereafter ElastiGate), which allows users to automate gating by selecting gated training files, then uses elastic image registration to gate new files. Three assays of increasing complexity were examined: TBNK, stem cell enumeration (SCE), and lymphoid screening tube (LST). For TBNK analysis, 60 peripheral blood (PB) samples from normal, HIV+, and controls were tested with ground truth analysis by an existing automated method. For SCE, 128 samples including bone marrow (BM), cord blood (CB), and apheresis were tested with analysis by multiple manual analysts. For LST, 80 PB and 28 BM samples were tested with manual analysis. For ElastiGate, a minimal number of training files was selected. Results were compared by Bland-Altman or F1 score analysis. For TBNK, ElastiGate using three training files (1 control, 1 normal, 1 HIV+) showed mean %bias across all reported populations between -1.48% and 7.13% (average 2.08%). For SCE, ElastiGate using three BM and two CB training files showed median F1 scores >0.93 in comparison to >0.94 and >0.92 for two other manual analysts. For LST, ElastiGate using four training files for each of PB and BM showed median F1 scores >0.945 for 13 of 14 PB populations and 10 of 14 BM populations, with generally similar or better performance for normal samples compared to abnormal; populations with lower scores were often associated with lower agreement between manual analysts. Based on analysis of three assays with four sample types of increasing complexity, ElastiGate with minimal training files may perform as an automated gating assistant. The results reported here are for research use only, not for use in diagnostic or therapeutic procedures.

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is a common enzymopathy that affects red blood cells (RBCs) and renders them susceptible to oxidative stress. G6PD deficiency can cause hemolytic anemia, especially after exposure to certain drugs or infections. The diagnosis of G6PD deficiency is usually based on spectrophotometric measurement of enzyme activity, but this method has limitations in heterozygous females and in patients with other hematological disorders. In this study, we evaluated the use of flow cytometry as an alternative method for detecting G6PD deficiency in 514 samples (265 females and 249 males) from a clinical laboratory. We compared the results of flow cytometry with those of spectrophotometry and molecular analysis, and assessed the performance of flow cytometry in different subgroups of patients. We found that flow cytometry was able to identify G6PD deficiency in most cases, with high sensitivity and specificity. Flow cytometry also allowed the quantification of the percentage of G6PD-deficient RBCs, which varied among heterozygous females due to X-chromosome inactivation. Moreover, flow cytometry detected several cases of G6PD deficiency that were missed by spectrophotometry, especially in heterozygous females with normal or subnormal enzyme activity. However, flow cytometry also showed some false negative results, mainly in patients with sickle cell disease. Therefore, flow cytometry is a reliable and efficient tool for screening G6PD deficiency, but some precautions should be taken in interpreting the results in patients with other hematological conditions.