Diagnostic Flow Cytometry Research Articles

European flow cytometry quality assurance guidelines for the diagnosis of primary immune deficiencies and assessment of immune reconstitution following B cell depletion therapies and transplantation

AbstractOver the last 15 years activity of diagnostic flow cytometry services have evolved from monitoring of CD4 T cell subsets in HIV‐1 infection to screening for primary and secondary immune deficiencies syndromes and assessment of immune constitution following B cell depleting therapy and transplantation. Changes in laboratory activity in high income countries have been driven by initiation of anti‐retroviral therapy (ART) in HIV‐1 regardless of CD4 T cell counts, increasing recognition of primary immune deficiency syndromes and the wider application of B cell depleting therapy and transplantation in clinical practice. Laboratories should use their experience in standardization and quality assurance of CD4 T cell counting in HIV‐1 infection to provide immune monitoring services to patients with primary and secondary immune deficiencies. Assessment of immune reconstitution post B cell depleting agents and transplantation can also draw on the expertise acquired by flow cytometry laboratories for detection of CD34 stem cell and assessment of MRD in hematological malignancies. This guideline provides recommendations for clinical laboratories on providing flow cytometry services in screening for immune deficiencies and its emerging role immune reconstitution after B cell targeting therapies and transplantation.

Abstract 6409: A multiparametric flow cytometry assay to monitor regeneration of B-cells following anti B-cell therapy in cancer and autoimmune patients

Abstract Purpose Functional dysregulation of B-cells leads to a variety of autoimmune disorders and blood cancers. Multiple B-cell depleting therapies (e.g., BTK inhibitors, antibodies or CAR-Ts) are currently in active clinical trial investigation. Following therapeutic elimination of pathogenic B-cells, it is critical to monitor the productive regeneration of fully functional B-cells as they mediate innate and adaptive immune responses. To this end, we developed a multiparametric flow cytometry assay for exquisite monitoring of early stages of B cell development, maturation, and antibody production to correlate it with treatment outcomes and determine if continuous depletion of B-cells is necessary to maintain clinical benefits for patients. Study Design We designed a high throughput 12-parameter flow cytometry panel incorporating primary differentiation markers namely, CD45, CD3, CD38, CD10, CD27, CD19, CD20, IgD, Lambda & Kappa Light Chains required for identification of different developmental stages of B-cells in peripheral blood using an in vitro diagnostic grade flow cytometry system (BD FACSLyric). The optimized method underwent robust fit-for-purpose analytical validation per CLSI H62 guidelines with emphasis on establishing assay sensitivity, specificity, and reproducibility across experimental days, operators, and instruments. Results We were able to reliably identify different stages of B-cell development, namely, Naïve (CD19+CD20+IgD+CD27-), Unswitched/Marginal (CD19+CD20+IgD+CD27+), Memory (CD19+CD20+IgD-CD27+), Transitional (CD19+CD20+IgD+CD27-CD10+), Antibody Secreting Cells (CD19+CD20-IgD-CD27+CD38hi) as well as clonality (CD19+CD20+Lambda+ or Kappa+). The lower limit of quantitation was determined to be around 60 events, based upon analysis of 90 data points with good reproducibility (CV range: 0-11.7%) across experimental days, operators and instruments demonstrating sensitive detection and robust performance. Conclusion In summary, we have developed and validated a 12-parameter flow cytometry assay focusing on monitoring the regeneration of different subsets of B-cells in various B-cell malignancies (Non-Hodgkin’s Lymphoma, B CLL) and autoimmune disorders (Multiple Sclerosis, Rheumatoid Arthritis, Systemic Lupus Erythematosus). The high reproducibility/robustness of the assay demonstrates its suitability for use in clinical trials as a valuable tool for safety monitoring and disease evaluation enabling development of novel therapeutic agents. Citation Format: Amit Kumar Mehta, Ruby Tandon, Anil Pahuja, Jane Gao, Kevin Nguyen, Naveen Dakappagari, Zeni Alfonso. A multiparametric flow cytometry assay to monitor regeneration of B-cells following anti B-cell therapy in cancer and autoimmune patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6409.

Translating the regulatory landscape of medical devices to create fit-for-purpose artificial intelligence (AI) cytometry solutions.

The implementation of medical software and artificial intelligence (AI) algorithms into routine clinical cytometry diagnostic practice requires a thorough understanding of regulatory requirements and challenges throughout the cytometry software product lifecycle. To provide cytometry software developers, computational scientists, researchers, industry professionals, and diagnostic physicians/pathologists with an introduction to European Union (EU) and United States (US) regulatory frameworks. Informed by community feedback and needs assessment established during two international cytometry workshops, this article provides an overview of regulatory landscapes as they pertain to the application of AI, AI-enabled medical devices, and Software as a Medical Device in diagnostic flow cytometry. Evolving regulatory frameworks are discussed, and specific examples regarding cytometry instruments, analysis software and clinical flow cytometry in-vitro diagnostic assays are provided. An important consideration for cytometry software development is the modular approach. As such, modules can be segregated and treated as independent components based on the medical purpose and risk and become subjected to a range of context-dependent compliance and regulatory requirements throughout their life cycle. Knowledge of regulatory and compliance requirements enhances the communication and collaboration between developers, researchers, end-users and regulators. This connection is essential to translate scientific innovation into diagnostic practice and to continue to shape the development and revision of new policies, standards, and approaches.

Paroxysmal Nocturnal Haemoglobinuria (PNH) Arising from Non-Canonical Mutations

Introduction Acquired somatic mutations in the X-linked PIGA gene are the most commonly described pathological mutations found in the serious haematopoietic disorder paroxysmal nocturnal haemoglobinuria (PNH), though incidental cases of mutations in PIGT, PIGB and PIGV have been reported. Mutations in the family of 20 PIG (phosphatidylinositol glycan) genes can disrupt biosynthesis of glycosylphosphatidylinositol (GPI) anchors, critical for tethering many important proteins, including the vital complement regulators CD55 and CD59, to the cell membrane. Their absence in PNH leads to complement dysregulation and complications including potentially life-threatening haemolysis and thrombosis, which may be mitigated by lifelong anti-complement therapy. From the cohort of 273 PNH patients currently on complement inhibitor therapy at the Leeds National PNH Centre we have identified 37 patients whose diagnostic flow cytometry report or clinical course differs significantly from expectation, particularly with evidence of inflammatory presentations, which may be indicative of an alternative, non- PIGA, aetiology. Methods Patients consented to the Leeds PNH Research Tissue Bank with unusual clinical and laboratory presentations were identified, genomic DNA was extracted from peripheral blood and initially screened by targeted high sensitivity NGS of the PIGA gene. From the first ten patient samples sequenced, three lacked any evidence of PIGA mutations and so whole exome sequencing (WES) was carried out. Results Patient 1:An 80 year old man, diagnosed with MDS with rearrangement of chromosomes 3 and 7 resulting in a dicentric chromosome and loss of chromosome 20q, was diagnosed with PNH following an increase in transfusion requirement. In addition to classical symptoms of PNH he was diagnosed with seronegative rheumatoid arthritis. Flow cytometry showed an unusual PNH phenotype with a large population of partially GPI-anchor deficient cells only (Table 1). Symptoms improved on eculizumab but he remained transfusion dependent and the disease later transformed to acute myeloid leukaemia. WES: exonic frameshift insertion in PIGT (figure1), pathogenic variant rs760395465. Patient 2:A 34 year old woman presented with a 13 year history of intermittent episodes of generalized urticaria associated with nausea, vomiting, general malaise and myalgia, increasing in intensity and latterly being associated with haemoglobinuria, lethargy and jaundice leading to a PNH diagnosis. Episodes were triggered by pregnancy or infections, but she remained asymptomatic between attacks. Flow cytometry revealed a PNH clone with a majority of cells being partially GPI deficient. She responds well to C5 inhibition with no further symptoms, including urticaria. WES: exonic frameshift insertion in PIGT (figure 1), pathogenic variant rs760395465. Patient 3: A 14 year old girl presented with intermittent episodes of urticaria and severe lethargy and was diagnosed with symptomatic significant transfusion-dependent PNH, with completely GPI-deficient cells. Diagnosis followed an episode of massive haemolysis resulting in transient acute renal failure requiring haemodialysis. She commenced anticoagulation initially until eculizumab was approved 2 years later; despite occasional episodes of breakthrough haemolysis she displays no further urticaria. She has also had symptoms of diffuse arthralgia. WES: stopgain mutation in PIGV (figure1), pathogenic variant rs145160045. Conclusions These cases add to the emerging picture of non- PIGA associated PNH cases and suggest that the presence of joint problems and episodic urticaria may be sufficient indication to prompt screening for alternative causative mutations. Similar to the previously reported PIGB mutated case, the patients with PIGT mutations only had partially deficient cells. It is important to fully characterise these emerging non-canonical variants in order to improve our understanding of the pathophysiology of this disorder and to provide more individualised care.

T-cell lymphoma involving the rectum of a dog

A mediastinal mass was diagnosed in a 7-year-4-month-old neutered female mixed breed dog following a 3-week history of lethargy, hyporexia and pyrexia. Bi-cavitary imaging, needle aspirate cytology and flow cytometry confirmed WHO clinical stage IVb, intermediate to large T-cell lymphoma involving the mediastinum, liver and spleen. The dog initially responded to a multidrug chemotherapy protocol but clinical deterioration occurred 3 months later. The dog presented with anorexia, vomiting and diarrhoea, associated with marked faecal tenesmus and haematochezia, initially believed by the primary care practitioner to be related to chemotherapy toxicity. However, rectal examination revealed multiple sessile and pedunculated masses. Further diagnostic imaging, cytology and flow cytometry confirmed progressive disease, including T-cell lymphoma of the rectum. Histology and immunohistochemistry confirmed an infiltrate of intermediate-sized CD3-positive neoplastic cells that expanded the rectal mucosa. Rectal lymphoma is uncommon in dogs and previous cases have been B cell in origin. In this report we describe the clinical presentation and macro- and microscopic findings of a case of canine T-cell lymphoma involving the rectum.

PCNEO, a New Proficiency Testing Program for Flow Cytometric Analysis of Plasma Cell Neoplasms From the College of American Pathologists Diagnostic Immunology and Flow Cytometry Committee.

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. To report the results from the first 4 years of the PCNEO program. 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. 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). 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.

Abstract 3231: Temporal changes in intratumoral and systemic lymphocytes in response to short and long course radiotherapy regimens in locally advanced rectal cancer

Abstract Background. Two pre-operative radiotherapy (RT) regimens are in common use for patients (pts) with locally advanced rectal cancer (LARC): Conventionally fractionated, long course chemoradiation (LCCRT, 25x1.8Gy with concomitant chemotherapy) or hypofractionated short-course RT (5X5Gy) followed by systemic chemotherapy (SCRT-C). RT is thought to induce immune responses to cellular damage, but the understanding of their evolution and relation to fractionation is limited. We are conducting a serial biospecimen collection in such pts with baseline, 2, 6 and 12 week (wk) sampling. We report serial measurement of tumor and peripheral blood lymphocyte responses for each regimen. Method. Multiplex immunofluorescence quantified tumor infiltrating lymphocytes (CD8, FOXP3). Routine diagnostic flow cytometry quantified circulating lymphocytes. A multiplex ELISA quantified cytokines in blood plasma. Bulk RNA-sequencing (QuantSeq) quantified gene expression within the tumor. Result. We report results for 20pts who received RT for stage III/IV LARC (13 LCCRT, 7 SCRT-C). Biopsy results are available for 10pts, circulating lymphocytes for 20pts and peripheral blood cytokines for 16pts. In LCCRT patients (n=8), relative to baseline, tumor infiltrating cytotoxic (CD8+) T cells were uniformly decreased during (2wks, P<0.05) and directly after treatment (6wks, P<0.05) before returning to baseline at 12wks. T regulatory cells (FOXP3+) similarly significantly decreased at 2wks and 6wks but remained below baseline at 12wks (P<0.05). Circulating lymphocytes also fell at wk2 and wk6 after commencing LCCRT and had begun recovering by wk12(n=13; P<0.05). The concentrations of circulating interleukins secreted by (IL2, IL8) or which activate T-lymphocytes (IL2, IL15) were reduced in the circulation at wk2 (n= 9; P<0.05) and wk6 (NS). In SCRT-C patients, we noted an increase in CD8 T cells at 2wks in 2/2 pts, also reflected in gene expression data, and an increase in FOXP3 T cells in 1/2 pts. Circulating lymphocytes were similarly decreased at wk2 in both the SCRT-C (n=7) and LCCRT (n=13) pts, but this reduction was less marked within the SCRT-C cohort at wk6 (P<0.01) and wk12 (P<0.05) relative to LCCRT patients. IL2, IL8 and IL15 did not change during or after SCRT-C (n=7; NS). Conclusion. LCCRT caused a drop in T cells during treatment, whilst SCRT-C appears to induce intra-tumoral T cell responses from wk2 and abrogates systemic reactions to a lesser extent. These results require evaluation in a larger cohort but have implications for understanding how RT induces microenvironmental changes and impacts pelvic bone marrow. We show in vivo that SCRT may be more immunostimulatory in LARC, with implications for trials combining RT with immunotherapy. Citation Format: Lily V. Hillson, Ross K. McMahon, Kathryn A. Pennel, Jean A. Quinn, Leia Jones, Raheleh Amirkhah, Aula Ammar, Phimmada Hatthakarnkul, Annabelle Ferguson, Simon W. Milling, Alec McDonald, Philip D. Dunne, Joanne Edwards, Sean M. O'Cathail, Campbell S. Roxburgh. Temporal changes in intratumoral and systemic lymphocytes in response to short and long course radiotherapy regimens in locally advanced rectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3231.

Highly sensitive single tube B-lymphoblastic leukemia/lymphoma minimal/measurable residual disease test robust to surface antigen directed therapy.

Measurement of minimal/measurable residual disease (MRD) in B-lymphoblastic leukemia/lymphoma (B-ALL) has become a routine clinical evaluation tool and remains the strongest predictor of treatment outcome. In recent years, new targeted anti-CD19 and anti-CD22 antibody-based and cellular therapies have revolutionized the treatment of the high-risk B-ALL. The new treatments raise challenges for diagnostic flow cytometry, which relies on the presence of specific surface antigens to identify the population of interest. So far, reported flow cytometry-based assays are developed to either achieve a deeper MRD level or to accommodate the loss of surface antigens post-target therapies, but not both. We developed a single tube flow cytometry assay (14-color-16-parameters). The method was validated using 94 clinical samples as well as spike-in and replicate experiments. The assay was well suited for monitoring response to targeted therapies and reached a sensitivity below 10-5 with acceptable precision (coefficient of variation < 20%), accuracy, and interobserver variability (κ = 1). The assay allows for sensitive disease detection of B-ALL MRD independent of CD19 and CD22 expression and allows uniform analysis of samples regardless of anti-CD19 and CD22 therapy.

Use of anti-JOVI.1 antibodies to detect clonal T cell populations: implementation into a diagnostic flow cytometry laboratory and correlation with clinical findings

Background: The determination of clonal T-cell populations in diagnostic flow cytometry has been more complex than that of B cells, hindering widespread availability. T-cells with αẞ T-cell receptor express a TCR ẞ-chain constant region encoded by either TRBC1, named JOVI.1, or TRBC2. We investigated the use of anti-JOVI.1 monoclonal antibodies in a large tertiary diagnostic flow cytometry laboratory.

Clinical outcome and prognosis of patients with acute myeloid leukemia submitted to chemotherapy with 5 years of follow-up

ObjectiveThe purpose of this study was to evaluate the clinical-epidemiological profile, associated risk factors and clinical outcomes of patients with acute myeloid leukemia (AML), identifying the main causes of morbidity and mortality and overall survival rate of patients at five years of follow-up. MethodThis was a retrospective cohort study evaluating the prognosis and clinical outcomes of 222 patients diagnosed with AML at three large hematology centers in Ceará (northeastern Brazil) over a period of five years. ResultsThe mean age at diagnosis was 44.1 ± 16 years, with a female prevalence of 1.3:1. No additional relevant risk factors associated with the development of AML were found, except for the well-established cytogenetic assessment. The overall 5-year survival rate was 39.4% (95%CI: 35.47 - 42.17). The main causes of death were disease progression (37.72%; n = 84) and sepsis (31.58%; n = 70). ConclusionThe clinical outcomes in our sample of AML patients were similar to those of other reported groups. Disease progression and infection were the main causes of death. Access to diagnostic flow cytometry and karyotyping was greater in our sample than in the national average. As expected, overall survival differed significantly according to the risk, as determined by cytogenetic testing.

Artificial Intelligence Enhances Diagnostic Flow Cytometry Workflow in the Detection of Minimal Residual Disease of Chronic Lymphocytic Leukemia.

Simple SummaryFlow cytometric immunophenotyping is critical in detecting minimal residual disease (MRD) in patients with chronic lymphocytic leukemia (CLL). However, flow cytometric analysis is complicated and time-consuming. Herein, we evaluated the performance of a deep neural network (DNN) in detecting CLL MRD and whether it could improve the diagnostic workflow in a clinical laboratory setting. Our findings demonstrated that a hybrid DNN approach had high accuracy in detecting CLL MRD; it standardized the gating strategy and dramatically reduced gating time, and it could be fully integrated into the existing clinical laboratory.Flow cytometric (FC) immunophenotyping is critical but time-consuming in diagnosing minimal residual disease (MRD). We evaluated whether human-in-the-loop artificial intelligence (AI) could improve the efficiency of clinical laboratories in detecting MRD in chronic lymphocytic leukemia (CLL). We developed deep neural networks (DNN) that were trained on a 10-color CLL MRD panel from treated CLL patients, including DNN trained on the full cohort of 202 patients (F-DNN) and DNN trained on 138 patients with low-event cases (MRD < 1000 events) (L-DNN). A hybrid DNN approach was utilized, with F-DNN and L-DNN applied sequentially to cases. “Ground truth” classification of CLL MRD was confirmed by expert analysis. The hybrid DNN approach demonstrated an overall accuracy of 97.1% (95% CI: 84.7–99.9%) in an independent cohort of 34 unknown samples. When CLL cells were reported as a percentage of total white blood cells, there was excellent correlation between the DNN and expert analysis [r > 0.999; Passing–Bablok slope = 0.997 (95% CI: 0.988–0.999) and intercept = 0.001 (95% CI: 0.000–0.001)]. Gating time was dramatically reduced to 12 s/case by DNN from 15 min/case by the manual process. The proposed DNN demonstrated high accuracy in CLL MRD detection and significantly improved workflow efficiency. Additional clinical validation is needed before it can be fully integrated into the existing clinical laboratory practice.

Acute Leukemia and COVID-19: The Johns Hopkins Experience

Introduction: At the beginning of the COVID-19 pandemic in the United States, some states combated viral spread via lockdowns. In Maryland, where Johns Hopkins Hospital (JHH) is located, the closures began with public schools (March 12, 2020; 3/12/20); followed by bars, restaurants, movie theaters, gyms and gatherings of >50 people (3/16/20) with 250 Maryland State Police troopers being activated to aid in enforcement. All non-essential businesses were closed on 3/23/20, with a statewide “stay-at-home order” announced on 3/30/20. At this time, we anecdotally noted a decline in the number of adult patients presenting to JHH with new diagnoses of acute leukemia (AL). In this retrospective study, we quantified changes in new AL diagnoses over this period.Methods: The study was approved by the JHH IRB. All patients with new presentations of AL undergo diagnostic flow cytometry (FC) analysis at our institution on peripheral blood and/or bone marrow samples.The FC database was searched for new diagnoses of adult (≥ 18 years) and pediatric (<18 years) AL during the following timeframes: [1] 3/13-6/10/20 (90 days after the first announced restriction) and [2] 2/11-3/12/20 (30 days prior to the first restriction). The database was searched for the same time periods in 2019 (3/13-6/10/19 and 2/10-3/12/19). A diagnosis of AL was considered new if the patient had not previously been diagnosed with AL or evolved to AL from an underlying myeloid neoplasm. Clinical data were collected from the electronic medical record. We used a Fisher's exact test to compare the distribution of new patients in the 30 days prior and 90 days following the announced COVID-19 restrictions in Maryland in 2020 to that of new patients in the corresponding time periods for 2019. The Cochran-Armitage test was used to compare trends in new patients with AL in the 30 days prior and 90 days following COVID-19 restrictions, as compared to the same time period in 2019. Statistical significance was defined as a p-value <0.05.Results: Between 3/13- 6/10/20, there were 25 new diagnoses of AL (11 women/14 men) with a median age of 51 years (range: 2.6 - 89 years; 10 pediatric/15 adult). During the same 90 day period in 2019, there were 32 new diagnoses of AL (18 women/14 men) with a median age of 63 years (range: 8 - 93 years; 2 pediatric/30 adult). Figure 1 shows the distribution of new AL diagnoses in adult patients by date of presentation. This decrease was most pronounced in the first 30 days, in which only one new adult patient with AL presented to JHH. The distribution of adult patients diagnosed in the 30 days prior and 90 days following the March 2020 restrictions was significantly different from the corresponding time period in 2019 (p=0.03); however, the overall trend of new adult AL diagnoses in the 30 days prior and the 90 days following the March 2020 restrictions was not significantly different from the corresponding time period in 2019 (p= 0.77). Of note, many patients with AL reported symptoms that overlapped with those of COVID-19 including fatigue (40%), dyspnea (35%) and fever (22%). 35.1% of patients diagnosed with AL after restrictions had no characteristic symptoms of COVID-19, as compared to 12.5% of patients diagnosed with AL during this period in 2019 (Table 1).Discussion: These data suggest that new presentations of adult AL were delayed by COVID-19-related restrictions. Given the acuity of AL, this delay may have affected clinical outcomes. Interestingly, pediatric new AL cases did not decrease during this time period. The reasons are unclear, though parents appear to have remained willing to seek care for their children even during the uncertain days at the beginning of the pandemic, perhaps due to the media reporting that COVID-19 infection was less aggressive in young people.Given the possibility of additional lockdowns due to COVID-19 variants or new pandemics, these data highlight the importance of encouraging patients to seek care in the event of illness, screening patients for both infectious and non-infectious disease, and ensuring that routine medical care remains accessible. [Display omitted] DisclosuresBrown: Kura: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; KIte: Membership on an entity's Board of Directors or advisory committees. Webster: AmGen: Consultancy; Pfizer: Consultancy.

Comparison of five diagnostic flow cytometry scores in patients with myelodysplastic syndromes: Diagnostic power and prognostic impact.

Flow cytometry (FCM) is a co-criterion in myelodysplastic syndromes (MDS) diagnostics according to the WHO classification. The presented study compared diagnostic power and prognostic impact of different FCM-based scores. A total of 807 bone marrow (BM) samples of patients with cytopenia (543 MDS, 153 non-clonal cytopenias, 111 non-MDS myeloid malignancies) and 78 healthy controls have been investigated using a standardized 8-color-FCM procedure. FCSS, Ogata-score, iFS, RED-score, and ELN-NEC were analyzed for sensitivity and specificity in comparison to standard diagnostic tools. Median follow up for patients was 26 month (range: 0.2-89). The iFS showed the highest accuracy (80%) with the best balance between sensitivity (79%) and specificity (86%). This was also valid in MDS with very low IPSS-R and even in MDS without ring sideroblasts, with normal blast count and karyotype, where iFS could confirm diagnosis in 62% and 65% of patients. Besides the high diagnostic power, the established iFS category "consistent with MDS" was associated with inferior overall survival (OS) independent from WHO classification (median: 51 month vs. not reached, p < 0.0001). Remarkably, this iFS category redefined a subgroup of patients with worse OS within IPSS-R low-risk category (73 month vs. not reached, p=0.0433). Finally, multivariable analysis showed that iFS added independent prognostic information regarding OS besides IPSS-R. The iFS separates non-clonal cytopenias and MDS with the highest accuracy, provided information in addition to standard diagnostic procedures, and refined established prognostic tools for outcome prediction.

Cryptococcal antigen carriage among HIV infected children aged 6 months to 15 years at Laquintinie Hospital in Douala

Up to 15% of deaths of people living with HIV is attributable to meningeal cryptococcosis, with nearly 75% occuring in sub-Saharan Africa. Although rare in children, it is a major cause of morbidity and mortality in people living with HIV. A strong association between cryptococcal antigenemia and the development of meningeal cryptococcosis has been shown in adults. Thus, in 2018, the World Health Organization published an updated version of its guidelines for the diagnosis, prevention and management of cryptococcal infection in adults, adolescents and the HIV-infected child. To determine the prevalence of cryptococcal antigenemia and to identify its determinants in children infected with HIV. An analytical cross-sectional study was carried out at the approved treatment center of Laquintinie hospital in Douala over a period of 4 months. Children were recruited consecutively after informed parental consent. Cryptococcal antigenemia and CD4 assay were performed using a Cryptops® immunochromatographic rapid diagnostic test and flow cytometry, respectively. The data collected included the socio-demographic, clinical and paraclinical variables of the children, as well as their antecedents. Data analysis was performed using Epiinfo software version 3.1 and SPSS 21.0. The significance threshold was set at 5%. A total of 147 children were enrolled. The mean age was 9.8 ± 4.09 years. The majority were on antiretroviral therapy (142, 96.60%). Only 13 (8.80%) were in severe immunosuppression. No child showed signs of meningeal cryptococcosis. The prevalence of cryptococcal antigenemia was 6.12%. Severe immunosuppression [OR: 10.03 (1.52-65.91), p = 0.016] and contact with pigeons [OR: 9.76 (1.14-83.65), p = 0.037] were independent factors significantly associated with the carriage of the cryptococcal antigen. We recommend screening for cryptococcal antigenemia and routine treatment with fluconazole of all HIV positive children with cryptococcal antigen whether symptomatic or not.

Mesothelin Is a Novel Disease Marker and Potential Therapeutic Target in Pediatric Acute Myeloid Leukemia

Acute myeloid leukemia (AML) remains a significant therapeutic challenge in children with only 50% cure rate with highly intensive cytotoxic chemotherapy. Further intensification is limited by acute and late effects, including severe infectious and cardiac toxicities; therefore, alternative therapeutic strategies are needed. As part of the NCI/COG TARGET AML Initiative, using transcriptome sequencing (RNA Seq) in 635 children and 178 adult AML, we demonstrated that mesothelin (MSLN) was highly-overexpressed in over one-third of pediatric AML. This transcript is not expressed in normal hematopoiesis, making it an ideal target for therapeutic intervention. MSLN is a cell-surface protein normally found in pleura and peritoneum and overexpressed in a variety of solid tumors, such as mesothelioma. The protein product of the MSLN gene exists in 4 forms in the body, including cell surface MSLN, soluble MSLN, and soluble megakaryocyte potentiating factor (MPF), which is the N-terminus of the MSLN pro-protein. Elevated serum soluble MSLN is an established diagnostic test for mesothelioma, with an FDA-approved ELISA-based assay (Mesomark™).Three different AML RNA Seq data sets totaling 813 cases, including TARGET validation cohort (n= 475), TARGET discovery phase (n= 160), and TCGA AML (n= 178), were interrogated for expression of MSLN, with normal marrow cases as a control. MSLN transcript expression at >5 transcripts per million (TPM) was observed in 268 patients (range 0-1225 TPM) with observed prevalence of 48% in TARGET discovery set, 33% in TARGET validation and 15% in adult TCGA set with a collective prevalence of 33% in the entire cohort. MSLN expression was enriched in patients with t(8;21), inv(16), and KMT2A fusions and rare in those with common AML-associated mutations (FLT3- ITD, NPM1, CEBPa mutations). MSLN was not expressed in 20 normal marrow samples (<1 TPM in all cases).We conducted orthogonal validation of the transcriptome data by evaluating diagnostic specimens from an independent cohort of 323 newly diagnosed pediatric AML patients for the presence of MSLN using quantitative RT-PCR and ELISA. RNA extracted from leukemic blasts or plasma obtained from diagnostic specimens were tested for MSLN expression by quantitative RT-PCR or sandwich ELISA, respectively. Optimized q-RT-PCR identified 36% of patients with MSLN expression. Similarly, sandwich ELISA (similar to Mesomark™) confirmed expression of soluble MSLN in 34% of patients tested, with strong concordance between the two tests (p <0.0001). We have also optimized diagnostic multi-dimensional flow cytometry (MDF) and MPF ELISA for evaluation of MSLN.Mesothelin is a cell surface protein highly expressed in AML blasts but absent in other hematopoietic cells, making it an attractive target for immunotherapy. We sought to test the principle of MSLN targeting in leukemia with antibody-drug conjugate (ADC) anetumab ravtansine (AR; BAY94-9343), comprised of an anti-MSLN antibody conjugated to tubulin inhibitor DM4. MSLN -overexpressing cells were created by lentivirally-transducing MSLN into K562 cells (K562+ MSLN). K562+ MSLN exhibited exquisite sensitivity to AR in vitro with an IC50 of 1.4 nM, compared to 360 nM in the non-transduced K562 and 250-260 nM in isotype control conditions (Fig. 1). In vitro cytotoxicity of AR in two primary pediatric MSLN + AML samples also demonstrated MSLN -dependent killing. Additionally, mice bearing K562+ MSLN xenografts were treated in vivo with AR, which demonstrated significant MSLN -dependent efficacy, resulting in median survival of 87 days compared to 32-41 days in control conditions, including chemotherapy with daunorubicin and cytarabine (Fig. 2).MSLN is a cell-surface protein uniquely overexpressed in one-third of pediatric AML, as well as a subset of adult AML. We have shown that MSLN can be detected through several sensitive diagnostic mechanisms including MDF, q-RT-PCR and serum soluble MSLN, making it an optimal marker for disease monitoring. The leukemic expression of MSLN and absence from normal hematopoietic tissue make it an ideal target for immunotherapeutic targeting, and our findings demonstrate that MSLN can be exploited for therapeutic benefit using ADCs. Further studies in MSLN + AML on optimal detection and immunotherapeutic strategies are needed, as MSLN shows great promise for enhanced disease monitoring and leukemia-specific therapeutic targeting. [Display omitted] DisclosuresLoken:Hematologics Inc: Employment, Equity Ownership. Pardo:Hematologics Inc: Employment.

High Prevalence of Multiple B Cell Clones in Patients with Chronic Lymphocytic Leukemia

INTRODUCTIONStudies suggest that the first clonal events in chronic lymphocytic leukemia (CLL) may be acquired at hematopoietic stem cell stage. Consistently, it has been reported that CD34+cells from CLL patients engrafted in immunodeficient mice give rise to clonal B cell lymphoproliferation while CD34+ cells from healthy donors did not (Kikushige, Cancer Cell 2011). Furthermore, in rare patients with early CLL or monoclonal B cell lymphocytosis two clonal populations can be demonstrated. We hypothesized that immunofixation electrophoresis could serve as a sensitive tool to assess the prevalence of a second, clonally distinct, lymphoproliferative event in CLL patients. METHODSWe studied 262 treatment-naïve patients with a diagnosis of chronic lymphocytic leukemia (CLL) enrolled in our natural history study (NCT00923507). All patients had diagnostic peripheral blood flow cytometry testing (Laboratory of Pathology, NCI) and serum immunofixation electrophoresis (Department of Laboratory Medicine, Clinical Center, NIH) done. RESULTSOf the 262 patients, 148 (56.49%) were male and 114 (43.51%) were female. The median age of the study population was 65 years. Amongst the 262 patients, 243 (92.74%) were Caucasians, 8 (3.05%) were African Americans, 3 (1.14%) were Asians and 3 (1.14%) were multiracial. The race was undisclosed for 5 patients. Two of the 262 CLL patients had another B-cell malignancy on diagnostic workup, Waldenstrom's macroglobulinemia (Lymphoplasmacytic Lymphoma) and Hairy Cell Leukemia. Nine (3.44%) patients had two distinct clones of CLL by flow cytometry. In 4 both kappa and lambda clones were present. In 5, the two clones expressed the same light chains but had a distinct immunophenotype resulting in bi-phenotypic clones. By serum IFE, 62 (23.66%) of 262 patients had monoclonal gammopathy; in 44 (16.8%) patients one monoclonal band was detected, while 18 (6.9%) patients had 2 or more bands. Among patients with one monoclonal band 25 were kappa and 19 lambda light chain. In 19 of 25 patients with kappa clonal CLL by flow cytometry, the monoclonal band on IFE was kappa (concordant flow and IFE): IgM Kappa (in 8), IgG Kappa (10), and IgA Kappa (1); and in 6 patients with kappa clonal CLL the monoclonal band was lambda (discordant flow and IFE): IgM Lambda (in 2), and IgG Lambda (4). In 15 of 19 patients with lambda clonal CLL, flow cytometry and IFE were concordant: IgM Lambda (in 6), IgG Lambda (6), IgA Lambda (1), free lambda light chain (2), and discordant in 4: IgM Kappa (in 2), IgG Kappa (2). Amongst the 18 patients with 2 or more bands on IFE, only 5 patients had concordant flow cytometry and IFE, while 13 had discordant findings. In summary, using IFE we detected a second clonal event in 23 (8.8%) of 262 CLL patients. Considering the 11 patients with two distinct clones by flow cytometry, 34 (13%) of 262 treatment-naive CLL patients had at least one additional clonal B cell process. In addition, 18 patients with concordant flow and IFE findings had IgG or IgA type gammopathy, consistent with a concurrent plasma cell dyscrasia of the same light chain restriction as the CLL clone. CONCLUSIONIn 13% of CLL patients we found evidence for a second B cell lymphoproliferative process. The prevalence of biclonal CLL by flow cytometry at 3.4% is comparable to findings by others, reporting between 0.7% and 3.4%. In contrast, the prevalence of monoclonal gammopathy (23.7%) in our patients (median age 65) was much higher than reported in the general population: 3.2 % at age 50 and above, and 5.3% at age 70 and above (Kyle, NEJM 2006). Importantly, in 8.8% of all patients the monoclonal gammopathy was discordant with the CLL clone. These data support the existence of a genetic event in an early progenitor cell that predisposes to the development of clonal B cell expansions.This research was supported by the Intramural Research Program of NHLBI and NCI. DisclosuresWiestner:Pharmacyclics: Research Funding; Acerta Pharma: Research Funding.

Issue Highlights — May 2021

Issue Highlights — May 2021

Interlaboratory Agreement of Anti-Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Serologic Assays in the Expedited College of American Pathologists Proficiency Testing Program.

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. To describe the development and initial results of the College of American Pathologists (CAP) SARS-CoV-2 Serology Survey. 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. 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. 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.

Augmented Human Intelligence and Automated Diagnosis in Flow Cytometry for Hematologic Malignancies.

Clinical flow cytometry is laborious, time-consuming, and expensive given the need for data review by highly trained personnel such as technologists and pathologists as well as the significant number of normal cases. Given these issues, automation in analysis and diagnosis holds the key to major efficiency gains. The objective was to design an automated pipeline for the diagnosis of B-cell malignancies in flow cytometry and evaluate its performance against our standard clinical diagnostic flow cytometry process. Using 3,417 cases of peripheral blood data over 6 months from our 10-color B-cell screening tube, we used a newly described method for feature extraction and dimensionality reduction called UMAP on the raw flow cytometry data followed by random forest classification to classify cases without gating on specific population. Our automated classifier was able to achieve greater than 95% accuracy in diagnosing all B-cell malignancies, and even better performance for specific malignancies for which the panel was designed, such as chronic lymphocytic leukemia. By adjusting classifier cutoffs, 100% sensitivity could be achieved with an albeit low 14% specificity. Hypothetically, this would allow 11% of the cases to be autoverified without human intervention. These results suggest that a clinical implementation of this pipeline can greatly assist in quality control, improve turnaround time, and decrease staff workloads.

Machine Learning-Based Flow Cytometry Diagnostics in Myelodysplastic Syndromes: Validation in the HOVON89 Clinical Trial (EudraCT 2008-002195-10)

Introduction Flow cytometry is a recommended tool in the diagnostic work-up of cytopenic patients suspected for myelodysplastic syndromes. Currently used flow cytometry scores rely on human assessment of dysplastic features in the bone marrow. Although proven useful, these methods are labor intensive and require a high level of expertise. Therefore, we previously developed a machine learning-based workflow for flow cytometry diagnostics in MDS by combining computational cell detection and a machine learning-classifier. This workflow outperformed traditional diagnostic scores with respect to accuracy (sensitivity 85-97%, specificity 93-97%), time investment (&amp;lt;30 seconds) and required materials (manuscript submitted). In the present study, we validated sensitivity of the workflow in a well-characterized clinical trial cohort (HOVON89 EudraCT 2008-002195-10) of lower risk MDS patients. Method Patient inclusion and characteristics Very low to intermediate risk MDS patients enrolled in the HOVON89 clinical trial (EudraCT 2008-002195-10) were included. 53 patients met the additional inclusion criteria, concerning written consent for add-on studies and availability of required flow cytometry data. Sample preparation Bone marrow samples were processed for flow cytometry analysis according to the European Leukemia Net guidelines. This study focused on the antibody combination optimized for assessment of myeloid progenitors and erythroid dysplasia (CD45, CD34, CD117, HLA-DR, CD71, CD36, CD105, CD33, sideward light scatter (SSC) and forward light scatter (FSC)). Machine learning-based workflow The machine learning-based workflow was developed in a prior study based on a reference cohort consisting of MDS patients without excess of blasts(n=67) and non-MDS cases (n=81) (Figure 1). MDS patients were diagnosed based on (cyto)morphology, cytogenetics and clinical follow-up. Non-MDS cases were patients with confirmed non-neoplastic cytopenias (n=69) and age-matched healthy individuals (n=12). Results In the validation cohort, the machine learning-based diagnostic workflow classified 49 out of 53 patients correctly, reaching a sensitivity of 92%. The workflow outperformed two currently used diagnostic tools for MDS flow cytometry, the Ogata score and integrated flow cytometry score (iFS). The former obtained 72% sensitivity (McNemar: p = 0.001) and the latter 83% sensitivity (McNemar: p = 0.06) in the validation cohort. Per patient, time required for automated analysis was less than 30 seconds. All four MDS patients that classified false negatively had a normal karyotype and (very) low risk disease according to the IPSS-r. In three out of four patients, no mutations or MDS-associated immunophenotypic features were detected. One patients was diagnosed as MDS-MLD and three patients as MDS-RS-SLD according to the WHO 2016 classification. The ten most relevant cellular features that discriminated between MDS and non-MDS patients in the reference data were confirmed in the current validation cohort. All ten features of MDS patients in the validation cohort were significantly different from non-MDS patients of the reference cohort (all features, p &amp;lt; 0.00001) (Figure 2). Seven out of ten features were similar in MDS patients of the validation cohort compared to those of the MDS patients of the reference cohort (p&amp;gt;0.05) (Figure 2). Conclusion In this validation study, we confirmed accuracy of machine learning-based flow cytometry diagnostics in lower risk MDS. The workflow obtained 92% sensitivity, which is in accordance with results from our previous study (85-97%), and outperformed currently used diagnostic flow cytometry scores for MDS (i.e. Ogata score and iFS). In our previous study specificity was 95% in both reference and test cohorts. Cellular features, most discriminative for diagnosis, were confirmed in the validation cohort, emphasizing robustness of the method. Additional benefits of this approach are the reduction in analysis time to less than thirty seconds per patient, reduction of required antibodies and increased reproducibility. Disclosures van de Loosdrecht: celgene: Honoraria; novartis: Honoraria.