Cytometry Part B: Clinical Cytometry最新文献

Measurable residual disease (MRD) testing for chronic lymphocytic leukemia (CLL) is often done on peripheral blood (PB) since the concordance of results with bone marrow is high and testing is less invasive. When analyzing CLL MRD data, one must be aware of small, normal populations in the PB that may be mistaken for residual CLL cells. As part of our CLL MRD assay validation, PB samples were collected from 10 healthy donors and a 2-tube CLL MRD flow cytometry panel was stained for each donor using markers CD19, CD20, BAFF-R, kappa, lambda, CD5, CD200, CD23, CD38, CD81, ROR1, CD79b, CD43, and CD45. Additional markers were utilized to exclude T-cells, NK-cells, and myeloid cells from the analysis. Samples were acquired on the Navios EX flow cytometer, and the data were analyzed using FCS Express software. Once the test was implemented, CLL PB patient samples were monitored. All 10 PBs from healthy donors contained small populations of cells present in the lymphocyte gate which mimicked CLL cells in their expression of CD45, CD19, CD20, CD43 (both positive, although CLL cells showed dimmer positive expression), CD79b, and level of surface light chains, immunophenotypically compatible with plasmablasts. Clinical implementation of the CLL assay revealed 12 out of 77 (16%) CLL PB patient samples demonstrating a small population of plasmablasts. Plasmablasts normally exist in peripheral blood at levels detectable by flow cytometry MRD assays and may be a potential confounder in the identification of MRD in CLL.

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&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&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.

The diagnosis of T-cell neoplasms remains one of the most challenging areas in hematopathology due to the immunophenotypic heterogeneity and subtle aberrancies often present in these entities. This “Best Practice” manuscript provides a practical framework for laboratories to design, validate, and interpret immunophenotyping studies of immature and mature T-cell neoplasms. We outline the utility of key antigens in the screening and classification of T-cell lymphomas/leukemia including TRBC1 and TRBC2. Analytical strategies using the “difference from normal” method and template-based gating are discussed, along with validation considerations aligned with CLSI H62 guidelines. By integrating these principles into laboratory workflows, this manuscript aims to standardize and improve the assessment of T-cell neoplasms across diverse clinical settings.

To screen hereditary spherocytosis (HS), we first introduced the novel flow cytometric osmotic fragility test (FC-OFT) based on the two-point kinetic assay principle (FC-OFT_Kinetic). With the introduction of FC systems with automatic tube loaders, we updated the FC-OFT protocol to follow the endpoint assay principle (FC-OFT_Endpoint). This study aims to evaluate the updated FC-OFT protocol (FC-OFT_Endpoint) and compare its assay performance with that of FC-OFT_Kinetic. We investigated factors influencing the FC-OFT_Endpoint assay, optimized its protocol, and defined the cutoff index using 152 negative or artificially positive control samples. We then compared the assay performance with that of FC-OFT_Kinetic in 25 patients with anemia, including 14 with spherocytosis—8, 4, 1, and 1 with HS, autoimmune hemolytic anemia, burn injury, and liver cirrhosis, respectively. To optimize FC-OFT_Endpoint, we adopted phosphate-buffered saline as the red cell suspension medium, 50% deionized water for hypotonic osmotic pressure in adults, and a 3-min standby time. This FC-OFT_Endpoint was more accurate than FC-OFT_Kinetic in identifying spherocytosis in the 25 patients with anemia (p = 0.0313). FC-OFT_Endpoint is a viable alternative to conventional OFT or FC-OFT_Kinetic for HS screening in clinical laboratories, as automatic FC enhances assay performance. These findings warrant validation in future multicenter studies with larger sample sizes.

Flow cytometry is a powerful tool for analyzing diverse cellular properties, making it essential in immunology research, clinical trials, and diagnostics. Integrating artificial intelligence (AI) into flow cytometry has the potential to enhance various aspects of assay development and application, including reagent selection, instrument standardization, panel and assay design, data analysis, quality controls, and knowledge dissemination. This paper provides a review of current AI applications in flow cytometry and explores the potential future directions for AI integration in the field.

CD300e is a marker of mature monocytes in flow cytometry; however, there is limited detailed information on staining patterns in conjunction with other monocyte markers. We evaluated the flow cytometric staining patterns of CD64, CD14, and CD300e in 12 negative and 33 positive peripheral blood specimens and 16 negative and 56 positive bone marrow specimens. The positive cases were involved by myeloid neoplasms (increased blasts and/or abnormal monocytes). Flow cytometry plots were reviewed for each case, the monocyte population was identified by bright CD64 expression, and the monocyte maturation pattern was visualized by CD14 versus CD300e plots. Peripheral blood and bone marrow differential counts were collected. A total of 39% (22/56) of the positive bone marrow cases showed a different maturation pattern from the negative bone marrow cases. Of the positive peripheral blood cases, 28/33 (85%) showed a CD14 by CD300e pattern different from that observed in the negative peripheral bloods. When the subset of bone marrow cases involved by monocytic neoplasms was evaluated, there was no significant difference between monocyte percentage by flow cytometry versus morphology and between blast plus promonocyte percentage by flow cytometry versus morphology. We conclude that isolation of monocytes by bright CD64 expression and low side-scatter and subsequent evaluation of the CD14/CD300e maturation pattern may help identify myeloid neoplasms. Quantification of CD64 + CD14- and/or CD64 + CD300e- cells by flow cytometry may aid blast/blast equivalent identification/quantification.