Linden, Michael A.

Abstract 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.

Context.— In 2018 the College of American Pathologists Diagnostic Immunology and Flow Cytometry Committee designed and implemented a new plasma cell neoplasia flow cytometry proficiency testing program—PCNEO—to allow clinical flow cytometry laboratories to monitor and assess their performance compared with a peer group. Objective.— To report the results from the first 4 years of the PCNEO program. Design.— Program participants were sent 2 sets of challenges per year, each including 1 wet challenge and 2 dry challenges, with associated clinical and laboratory findings. The wet challenges were composed of myeloma cell line specimens (with or without dilution in preserved whole blood) for flow cytometric analysis. The dry (paper) challenges were composed of clinical case summaries and images of flow cytometric test results from various flow cytometry laboratories of committee members. Results.— A total of 116 to 145 laboratories from 17 countries enrolled in the proficiency testing program. For the wet challenges, almost all participants (97%–100%; cumulative, 98.2%) correctly identified the presence of neoplastic plasma cell populations based on flow cytometric analysis of undiluted myeloma cell lines. Slightly fewer participants (89.0%–97.4%; cumulative, 95.2%) correctly identified the presence of neoplastic plasma cell populations based on flow cytometric analysis of diluted myeloma cell lines (10% or 50% dilutions into peripheral blood) intended to better represent a typical clinical sample. There was generally agreement among 80% or more of participants for positive or negative staining for CD38, CD138, CD19, CD20, and surface and cytoplasmic κ and λ light chains. Similarly, 84% to 100% of participants were able to correctly identify the presence of neoplastic plasma cell populations in paper challenges, including the presence of small, neoplastic plasma cell populations (0.01%–5.0% clonal plasma cells) and the presence of nonneoplastic plasma cell populations (correctly identified by 91%–96% of participants). Conclusions.— Participant performance in the new proficiency testing program was excellent overall, with the vast majority of participants able to perform flow cytometric analysis and identify neoplastic plasma cell populations and to identify small plasma cell clones or expanded populations of reactive plasma cells in dry challenge flow cytometry results. This program will allow laboratories to verify the accuracy of their testing program and test interpretations for the assessment of patients suspected of having a plasma cell neoplasm.

Context.— Misdiagnosis of antiphospholipid syndrome can occur owing to the wide diversity of antiphospholipid (aPL) assays and a lack of international calibrators and harmonized reference intervals. Objective.— To assess laboratory practices regarding reporting and establishing reference intervals for immunoglobulin (Ig) G/IgM anti-cardiolipin (aCL) and anti–beta-2 glycoprotein I (anti-β2GPI) assays. Design.— Supplemental questions related to reporting and establishing reference ranges for aPL assays were sent as part of the Antiphospholipid Antibody (ACL)-B 2019 College of American Pathologists (CAP) proficiency testing survey. The response rate and methods assessment details were determined, as well as qualitative and quantitative results for 3 test samples. Results.— The number of participants reporting results for IgG aCL (n = 489), IgM aCL (n = 476), IgG anti-β2GPI (n = 354), and IgM anti-β2GPI (n = 331) varied by antibody type. The enzyme-linked immunosorbent assay (ELISA) (up to 58.6%, 260 of 444) was the most used method; others included multiplex (from 18.9% to 23.9%), fluorescence enzyme immunoassay (14.4%–17.6%), and chemiluminescence immunoassay (6.5%–9.0%). More respondents reported quantitative than qualitative results, and manufacturer cutoff ranges were used by 92.9% and 94.2% of respondents for aCL and anti-β2GPI, respectively. Despite variation in the use of semiquantitative ranges, qualitative negative/positive reporting of the test samples achieved almost 100% consensus. Qualitative consensus was met in contrast to the wide range of quantitative results obtained for each analyte across different kits. Conclusions.— ELISA remains the most used method for detecting aPL antibodies, with most laboratories reporting quantitative results based on manufacturers' suggested reference ranges. The categorization of quantitative results as equivocal, weak positive, or positive for responders using kits from the same manufacturer was variable.

Abstract Patients with core-binding factor (CBF) acute myeloid leukemia (AML), caused by either t(8;21)(q22;q22) or inv(16)(p13q22)/t(16;16)(p13;q22), have higher complete remission rates and longer survival than patients with other subtypes of AML. However, ∼40% of patients relapse, and the literature suggests that patients with inv(16) fare differently from those with t(8;21). We retrospectively analyzed 537 patients with CBF-AML, focusing on additional cytogenetic aberrations to examine their impact on clinical outcomes. Trisomies of chromosomes 8, 21, or 22 were significantly more common in patients with inv(16)/t(16;16): 16% vs 7%, 6% vs 0%, and 17% vs 0%, respectively. In contrast, del(9q) and loss of a sex chromosome were more frequent in patients with t(8;21): 15% vs 0.4% for del(9q), 37% vs 0% for loss of X in females, and 44% vs 5% for loss of Y in males. Hyperdiploidy was more frequent in patients with inv(16) (25% vs 9%, whereas hypodiploidy was more frequent in patients with t(8;21) (37% vs 3%. In multivariable analyses (adjusted for age, white blood counts at diagnosis, and KIT mutation status), trisomy 8 was associated with improved overall survival (OS) in inv(16), whereas the presence of other chromosomal abnormalities (not trisomy 8) was associated with decreased OS. In patients with t(8;21), hypodiploidy was associated with improved disease-free survival; hyperdiploidy and del(9q) were associated with improved OS. KIT mutation (either positive or not tested, compared with negative) conferred poor prognoses in univariate analysis only in patients with t(8;21).

Context.— Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a recently emerged, currently pandemic virus, and the etiologic agent of coronavirus disease 2019 (COVID-19). Clinical testing for antibodies to SARS-CoV-2 has rapidly become widespread, but data regarding the interlaboratory performance of these serologic assays are limited. Objective.— To describe the development and initial results of the College of American Pathologists (CAP) SARS-CoV-2 Serology Survey. Design.— Members from the CAP Microbiology and Diagnostic Immunology and Flow Cytometry Committees formed a working group to support development of a new proficiency testing survey for anti–SARS-CoV-2 antibody assays. Supplemental questions in the survey assessed the state of SARS-CoV-2 serologic testing among participating laboratories as of July 2020. Results were analyzed for agreement by immunoglobulin (Ig) isotype tested, assay manufacturer, and methodology. Results.— A total of 4125 qualitative results were received from 1110 laboratories participating in the first survey. Qualitative agreement for assays measuring anti–SARS-CoV-2 total antibodies or IgG was greater than 90% for all 3 samples in the survey. Qualitative agreement for IgM and IgA for the negative sample was greater than 95%, but lacked consensus for the other 2 samples. Conclusions.— These initial data suggest overall excellent agreement and comparable performance for most qualitative anti–SARS-CoV-2 IgG and total antibody assays across all participating clinical laboratories, regardless of specific target antigen or assay methodology.

Background: Multiple myeloma (MM) remains an incurable plasma cell (PC) malignancy. Despite improvements in clinical outcomes, variability in treatment response exists. Some patients experience innate resistance, while others develop resistance over the course of treatment. Identifying signatures of treatment response and resistance is essential to predicting effective treatment strategies. Given the phenotypic clonal heterogeneity observed in MM, we hypothesize that resistant and sensitive subpopulations have unique phenotypic signatures. We used mass cytometry (CyTOF) to characterize primary MM samples and correlated their phenotypic signatures with treatment response. Methods: We characterized 102 primary MM samples by CyTOF using 37 antibodies (see figure). Frozen whole BM specimens were thawed, stained with antibodies, barcoded, and analyzed on a Helios mass cytometer. Data was processed using Cytobank or Pathsetter and analyzed using t-distributed stochastic neighbor embedding (t-SNE) algorithm. T-SNE plots for CD45+ cells were created using lineage defining markers. T-SNE plots of neoplastic PCs (CD138+,CD3-,CD16-,CD19-,cytoplasmic kappa or lambda+) were created using all remaining markers. A differential analysis of each sample's clusters was performed against all other events. Z-score values, representing marker changes from the differential analysis, for each cluster were used to group similar clusters across all samples, allowing us to compare sub populations of PCs between patients (see figure). From these groups of clusters with similar changes in markers, we calculated the proportion of cells with increases or decreases in markers for each sample. Results were compared to IMWG 90-day response criteria using a random forest model. Results: We performed mass cytometry on 102 samples from 68 unique MM patients. Median age was 66 years (range 34-95) with a 1.5:1 male:female ratio. 37 (36%) had NDMM, 55 (54%) had RRMM, 2 (2%) had SMM and 8 cases (8%) had unknown status. FISH studies revealed 47 (46%) had hyperdiploidy without a recurrent primary IgH rearrangement, 31 (30%) had t(11;14), 13 (13%) had t(4;14), 5 (5%) had 14;16 or 14;20, 3 (3%) had hyperhaploidy and 3 (3%) had an undefined primary. 54 (53%) had 1q gain/amp, 22 (22%) had TP53 deletion, 22 (22%) had a MYC rearrangement and 71% had high mSMART risk. Nearly all patients received an immunomodulatory compound, a proteasome inhibitor and dexamethasone. 2 (2%) had complete response (CR), 10 (9.8%) very good partial response (VGPR), 36 (35%) had partial response (PR), 14 (14%) had minimal response (MR), 13 (13%) had stable disease (SD) and 17 (17%) had progressive disease (PD). Characterization of CD45+ cells identified a relatively conserved and reproducible map from each patient. Notable differences included an ~2-fold reduction in the percentage of total B cells (CD45+,CD3-,CD19+)/total CD45+ cells in cases with high risk mSMART, RRMM and TP53 deletion compared to cases with standard risk, NDMM or normal TP53 status. Similar B-cell reductions were found in RRMM vs. NDMM samples from matched-patients. In contrast to the conserved t-SNE structure of the CD45+ population, the neoplastic PC population displayed dramatically reduced t-SNE structural consistency. Heterogeneity between patient samples and between the same patient samples over time was observed. We focused our analysis on 22 patients with serial samples. The proportion of each t-SNE group present in each patient sample was calculated and then correlated to the 90-day response metric. We identified a phenotypic group whose proportion increased in relation to disease progression (R2=0.85). This group had elevated BCL-2, pSTAT3, CD56 levels and reduced CD45 and CD81 levels. Evaluating individual markers, we found an increase in the proportion of cells with elevated BCL-2, pS6, Ki67, and IKZF1 levels in relation to disease progression. We also observed an increase in the proportion of cells with reduced pCREB levels and a reduction in the proportion of cells with reduced CD147 levels in relation to disease progression. Conclusions: We have utilized CyTOF to characterize phenotypic and functional markers in MM cells on a single cell level and can identify unique subgroups that change in relation to disease progression. Future analysis will correlate phenotypic signatures with ISS stage, mSMART risk, cytogenetic abnormality and type of treatment. Figure 1 Disclosures Kumar: Kite Pharma: Consultancy, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; MedImmune: Research Funding; Karyopharm: Consultancy; Merck: Consultancy, Research Funding; Carsgen: Other, Research Funding; Cellectar: Other; Novartis: Research Funding; Adaptive Biotechnologies: Consultancy; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genecentrix: Consultancy; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Tenebio: Other, Research Funding; BMS: Consultancy, Research Funding; Dr. Reddy's Laboratories: Honoraria.

AbstractBackgroundAlthough the prognosis of core‐binding factor (CBF) acute myeloid leukemia (AML) is better than other subtypes of AML, 30% of patients still relapse and may require allogeneic hematopoietic cell transplantation (alloHCT). However, there is no validated widely accepted scoring system to predict patient subsets with higher risk of relapse.MethodsEleven centers in the US and Europe evaluated 247 patients with t(8;21)(q22;q22).ResultsComplete remission (CR) rate was high (92.7%), yet relapse occurred in 27.1% of patients. A total of 24.7% of patients received alloHCT. The median disease‐free (DFS) and overall (OS) survival were 20.8 and 31.2 months, respectively. Age, KIT D816V mutated (11.3%) or nontested (36.4%) compared with KIT D816V wild type (52.5%), high white blood cell counts (WBC), and pseudodiploidy compared with hyper‐ or hypodiploidy were included in a scoring system (named I‐CBFit). DFS rate at 2 years was 76% for patients with a low‐risk I‐CBFit score compared with 36% for those with a high‐risk I‐CBFit score (P < 0.0001). Low‐ vs high‐risk OS at 2 years was 89% vs 51% (P < 0.0001).ConclusionsI‐CBFit composed of readily available risk factors can be useful to tailor the therapy of patients, especially for whom alloHCT is not need in CR1 (ie, patients with a low‐risk I‐CBFit score).