EuroFlow Lymphoid Screening Tube (LST) data base for automated identification of blood lymphocyte subsets

Characterization of Human B Cell Hematological Malignancies Using Protein-Based Approaches

The maturation of B cells is a complex, multi-step process. During B cell differentiation, errors can occur, leading to the emergence of aberrant versions of B cells that, finally, constitute a malignant tumor. These B cell malignancies are classified into three main groups: leukemias, myelomas, and lymphomas, the latter being the most heterogeneous type. Since their discovery, multiple biological studies have been performed to characterize these diseases, aiming to define their specific features and determine potential biomarkers for diagnosis, stratification, and prognosis. The rise of advanced -omics approaches has significantly contributed to this end. Notably, proteomics strategies appear as promising tools to comprehensively profile the final molecular effector of these cells. In this narrative review, we first introduce the main B cell malignancies together with the most relevant proteomics approaches. Then, we describe the core studies conducted in the field and their main findings and, finally, we evaluate the advantages and drawbacks of flow cytometry, mass cytometry, and mass spectrometry for the profiling of human B cell disorders.

Integration of T-cell clonality screening using TRBC-1 in lymphoma suspect samples by flow cytometry

BACKGROUND

The diagnosis of T-cell non-Hodgkin lymphomas (NHL) is challenging. The development of a monoclonal antibody specific for T-cell receptor β constant region 1 (TRBC1) provides an alternative to discriminate clonal T cells. The aim of this study was to evaluate the diagnostic potential of an anti-TRBC1 mAb for the identification of T-NHL.

METHODS

We performed a cross-sectional diagnostic analytic study of samples tested for lymphoma. All samples sent for lymphoma screening were first evaluated using the standard Euroflow LST, to which a second additional custom-designed T-cell clonality assessment tube was added CD45/TRBC1/CD2/CD7/CD4/TCRγδ/CD3. Flow cytometry reports were compared with morphological and molecular tests.

RESULTS

Fifty-nine patient samples were evaluated. Within the T-cell population, cut-off percentages in the CD4+ cells were from 29.4 to 54.6% and from 23.9 to 52.1% in CD8+ cells. Cut-off ratios in CD4+ T cells were from 0.33 to 1.1, and in CD8+ cells between 0.22 and 1.0. Using predefined normal cut-off values, 18 of 59 (30.5%) samples showed a restricted expression of TRBC1. A final diagnosis of a T-NHL was confirmed clinically and/or by histopathological studies in 15 of the 18 cases (83.3%). There were no cases of T-NHL by morphology/IHC with normal TRBC1 expression. Non-neoplastic patient samples behaved between predefined TRBC1 cut-off values.

CONCLUSIONS

Expression of TRBC1 provides a robust method for T-cell clonality assessment, with very high sensitivity and good correlation with complementary methods. TRBC1 can be integrated into routine lymphoma screening strategies via flow cytometry.

Immunophenotypic assessment of clonal plasma cells and B-cells in bone marrow and blood in the diagnostic classification of early stage monoclonal gammopathies: an iSTOPMM study

Monoclonal gammopathy of undetermined significance (MGUS) is the earliest discernible stage of multiple myeloma (MM) and Waldenström's macroglobulinemia (WM). Early diagnosis of MG may be compromised by the low-level infiltration, undetectable to low-sensitive methodologies. Here, we investigated the prevalence and immunophenotypic profile of clonal (c) plasma cells (PC) and/or cB-lymphocytes in bone marrow (BM) and blood of subjects with a serum M-component from the iSTOPMM program, using high-sensitive next-generation flow cytometry (NGF), and its utility in the diagnostic classification of early-stage MG. We studied 164 paired BM and blood samples from 82 subjects, focusing the analysis on: 55 MGUS, 12 smoldering MM (SMM) and 8 smoldering WM (SWM). cPC were detected in 84% of the BM samples and cB-lymphocytes in 45%, coexisting in 39% of cases. In 29% of patients, the phenotypic features of cPC and/or cB-lymphocytes allowed a more accurate disease classification, including: 19/55 (35%) MGUS, 1/12 (8%) SMM and 2/8 (25%) SWM. Blood samples were informative in 49% of the BM-positive cases. We demonstrated the utility of NGF for a more accurate diagnostic classification of early-stage MG.

Immune cell kinetics and antibody response in COVID-19 patients with low-count monoclonal B-cell lymphocytosis

Low-count monoclonal B-cell lymphocytosis (MBLlo ) has been associated with an underlying immunodeficiency and has recently emerged as a new risk factor for severe COVID-19. Here, we investigated the kinetics of immune cell and antibody responses in blood during COVID-19 of MBLlo versus non-MBL patients. For this study, we analyzed the kinetics of immune cells in blood of 336 COVID-19 patients (74 MBLlo and 262 non-MBL), who had not been vaccinated against SARS-CoV-2, over a period of 43 weeks since the onset of infection, using high-sensitivity flow cytometry. Plasma levels of anti-SARS-CoV-2 antibodies were measured in parallel by ELISA. Overall, early after the onset of symptoms, MBLlo COVID-19 patients showed increased neutrophil, monocyte, and particularly, plasma cell (PC) counts, whereas eosinophil, dendritic cell, basophil, and lymphocyte counts were markedly decreased in blood of a variable percentage of samples, and with a tendency toward normal levels from week +5 of infection onward. Compared with non-MBL patients, MBLlo COVID-19 patients presented higher neutrophil counts, together with decreased pre-GC B-cell, dendritic cell, and innate-like T-cell counts. Higher PC levels, together with a delayed PC peak and greater plasma levels of anti-SARS-CoV-2-specific antibodies (at week +2 to week +4) were also observed in MBLlo patients. In summary, MBLlo COVID-19 patients share immune profiles previously described for patients with severe SARS-CoV-2 infection, associated with a delayed but more pronounced PC and antibody humoral response once compared with non-MBL patients.

Automated EuroFlow approach for standardized in-depth dissection of human circulating B-cells and plasma cells

Background

Multiparameter flow cytometry (FC) immunophenotyping is a key tool for detailed identification and characterization of human blood leucocytes, including B-lymphocytes and plasma cells (PC). However, currently used conventional data analysis strategies require extensive expertise, are time consuming, and show limited reproducibility.

Objective

Here, we designed, constructed and validated an automated database-guided gating and identification (AGI) approach for fast and standardized in-depth dissection of B-lymphocyte and PC populations in human blood.

Methods

For this purpose, 213 FC standard (FCS) datafiles corresponding to umbilical cord and peripheral blood samples from healthy and patient volunteers, stained with the 14-color 18-antibody EuroFlow BIgH-IMM panel, were used.

Results

The BIgH-IMM antibody panel allowed identification of 117 different B-lymphocyte and PC subsets. Samples from 36 healthy donors were stained and 14 of the datafiles that fulfilled strict inclusion criteria were analysed by an expert flow cytometrist to build the EuroFlow BIgH-IMM database. Data contained in the datafiles was then merged into a reference database that was uploaded in the Infinicyt software (Cytognos, Salamanca, Spain). Subsequently, we compared the results of manual gating (MG) with the performance of two classification algorithms -hierarchical algorithm vs two-step algorithm- for AGI of the cell populations present in 5 randomly selected FCS datafiles. The hierarchical AGI algorithm showed higher correlation values vs conventional MG (r2 of 0.94 vs. 0.88 for the two-step AGI algorithm) and was further validated in a set of 177 FCS datafiles against conventional expert-based MG. For virtually all identifiable cell populations a highly significant correlation was observed between the two approaches (r2>0.81 for 79% of all B-cell populations identified), with a significantly lower median time of analysis per sample (6 vs. 40 min, p=0.001) for the AGI tool vs. MG, respectively and both intra-sample (median CV of 1.7% vs. 10.4% by MG, p<0.001) and inter-expert (median CV of 3.9% vs. 17.3% by MG by 2 experts, p<0.001) variability.

Conclusion

Our results show that compared to conventional FC data analysis strategies, the here proposed AGI tool is a faster, more robust, reproducible, and standardized approach for in-depth analysis of B-lymphocyte and PC subsets circulating in human blood.

Age- and Sex-Matched Normal Leukocyte Subset Ranges in the General Population Defined with the EuroFlow Lymphocyte Screening Tube (LST) for Monoclonal B-Cell Lymphocytosis (MBL) vs. Non-MBL Subjects

Reference ranges of blood-circulating leukocyte populations by, e.g., age and sex, are required for monitoring immune-cell kinetics. Most previous reports in which flow cytometry has been used to define the reference ranges for leukocyte counts included a limited number of donors and/or cell populations and/or did not consider age and sex simultaneously. Moreover, other factors not previously considered in the definition of normal ranges, such as the presence of chronic-lymphocytic-leukemia (CLL)-like low-count monoclonal B-cell lymphocytosis (MBLlo), might also be associated with an altered distribution of leukocytes in blood in association with an immunodeficiency and increased risk of infection and cancer. Here, we established reference cell-count ranges for the major populations of leukocytes in blood of non-MBL and MBLlo adult Caucasians matched by age and sex using the EuroFlow Lymphocyte Screening Tube (LST). A total of 706 Caucasian adult donors—622 non-MBL and 84 MBLlo—were recruited from the general population. Among non-MBL donors, the total leukocyte, neutrophil, basophil dendritic cell and monocyte counts remained stable through adulthood, while the absolute numbers of T- and B-cell populations and plasma cells decreased with age. The number of eosinophils and NK-cell increased over time, with clear differences according to sex for certain age ranges. In MBLlo subjects, few differences in the absolute cell counts by age (vs. non-MBL) were observed, and MBLlo men and women showed similar trends to non-MBL subjects except for the B-cell count drop observed in >70 y-men, which was more pronounced in MBLlo vs. non-MBL controls. Building robust age- and sex-matched reference ranges for the most relevant immune-cell populations in the blood of non-MBL donors is essential to appropriately identify an altered immune status in different clinical settings and highlight the altered immune-cell profiles of MBLlo subjects.

Development of a standardized and validated flow cytometry approach for monitoring of innate myeloid immune cells in human blood

Innate myeloid cell (IMC) populations form an essential part of innate immunity. Flow cytometric (FCM) monitoring of IMCs in peripheral blood (PB) has great clinical potential for disease monitoring due to their role in maintenance of tissue homeostasis and ability to sense micro-environmental changes, such as inflammatory processes and tissue damage. However, the lack of standardized and validated approaches has hampered broad clinical implementation. For accurate identification and separation of IMC populations, 62 antibodies against 44 different proteins were evaluated. In multiple rounds of EuroFlow-based design-testing-evaluation-redesign, finally 16 antibodies were selected for their non-redundancy and separation power. Accordingly, two antibody combinations were designed for fast, sensitive, and reproducible FCM monitoring of IMC populations in PB in clinical settings (11-color; 13 antibodies) and translational research (14-color; 16 antibodies). Performance of pre-analytical and analytical variables among different instruments, together with optimized post-analytical data analysis and reference values were assessed. Overall, 265 blood samples were used for design and validation of the antibody combinations and in vitro functional assays, as well as for assessing the impact of sample preparation procedures and conditions. The two (11- and 14-color) antibody combinations allowed for robust and sensitive detection of 19 and 23 IMC populations, respectively. Highly reproducible identification and enumeration of IMC populations was achieved, independently of anticoagulant, type of FCM instrument and center, particularly when database/software-guided automated (vs. manual “expert-based”) gating was used. Whereas no significant changes were observed in identification of IMC populations for up to 24h delayed sample processing, a significant impact was observed in their absolute counts after &gt;12h delay. Therefore, accurate identification and quantitation of IMC populations requires sample processing on the same day. Significantly different counts were observed in PB for multiple IMC populations according to age and sex. Consequently, PB samples from 116 healthy donors (8-69 years) were used for collecting age and sex related reference values for all IMC populations. In summary, the two antibody combinations and FCM approach allow for rapid, standardized, automated and reproducible identification of 19 and 23 IMC populations in PB, suited for monitoring of innate immune responses in clinical and translational research settings.

The Euroflow PID Orientation Tube in the diagnostic workup of primary immunodeficiency: Daily practice performance in a tertiary university hospital

Introduction

Multiparameter flow cytometry (FCM) immunophenotyping is an important tool in the diagnostic screening and classification of primary immunodeficiencies (PIDs). The EuroFlow Consortium recently developed the PID Orientation Tube (PIDOT) as a universal screening tool to identify lymphoid-PID in suspicious patients. Although PIDOT can identify different lymphoid-PIDs with high sensitivity, clinical validation in a broad spectrum of patients with suspicion of PID is missing. In this study, we investigated the diagnostic performance of PIDOT, as part of the EuroFlow diagnostic screening algorithm for lymphoid-PID, in a daily practice at a tertiary reference center for PID.

Methods

PIDOT was tested in 887 consecutive patients suspicious of PID at the Ghent University Hospital, Belgium. Patients were classified into distinct subgroups of lymphoid-PID vs. non-PID disease controls (non-PID DCs), according to the IUIS and ESID criteria. For the clinical validation of PIDOT, comprehensive characterization of the lymphoid defects was performed, together with the identification of the most discriminative cell subsets to distinguish lymphoid-PID from non-PID DCs. Next, a decision-tree algorithm was designed to guide subsequent FCM analyses.

Results

The mean number of lymphoid defects detected by PIDOT in blood was 2.87 times higher in lymphoid-PID patients vs. non-PID DCs (p < 0.001), resulting in an overall sensitivity and specificity of 87% and 62% to detect severe combined immunodeficiency (SCID), combined immunodeficiency with associated or syndromic features (CID), immune dysregulation disorder (ID), and common variable immunodeficiency (CVID). The most discriminative populations were total memory and switched memory B cells, total T cells, TCD4+cells, and naive TCD4+cells, together with serum immunoglobulin levels. Based on these findings, a decision-tree algorithm was designed to guide further FCM analyses, which resulted in an overall sensitivity and specificity for all lymphoid-PIDs of 86% and 82%, respectively.

Conclusion

Altogether, our findings confirm that PIDOT is a powerful tool for the diagnostic screening of lymphoid-PID, particularly to discriminate (S)CID, ID, and CVID patients from other patients suspicious of PID. The combination of PIDOT and serum immunoglobulin levels provides an efficient guide for further immunophenotypic FCM analyses, complementary to functional and genetic assays, for accurate PID diagnostics.

Experiences with Glofitamab Administration following CAR T Therapy in Patients with Relapsed Mantle Cell Lymphoma

Mantle cell lymphoma (MCL) is a rare type of B-cell Non-Hodgkin lymphoma (NHL) affecting predominantly male patients. While complete remissions following first-line treatment are frequent, most patients ultimately relapse, with a usually aggressive further disease course. The use of cytarabine-comprising induction chemotherapy and autologous stem cell transplantation, Rituximab maintenance, Bruton’s tyrosine kinase (BTK) inhibitors and CAR T therapy has substantially improved survival. Still, options for patients relapsing after CAR T therapy are limited and recommendations for the treatment of these patients are lacking. We report two cases of patients with mantle cell lymphoma who relapsed after CAR T therapy and were treated with the bispecific CD20/CD3 T cell engaging antibody glofitamab. Both patients showed marked increases of circulating CAR T cells and objective responses after glofitamab administration. Therapy was tolerated without relevant side effects in both patients. One patient completed all 12 planned cycles of glofitamab therapy and was alive and without clinical progression at the last follow-up. The second patient declined further treatment after the first cycle and succumbed to disease progression. We review the literature and investigate possible mechanisms involved in the observed responses after administration of glofitamab, such as proliferation of CAR T cells, anti-tumor effects of the bispecific antibody and the role of other possibly contributing factors. Therapy with bispecific antibodies might offer an effective and well-tolerated option for patients with mantle cell lymphoma relapsing after CAR T therapy.

Evaluation of fixed-panel, multicolour ClearLLab 10C at an academic flow cytometry laboratory in Johannesburg, South Africa

Background

Flow cytometric immunophenotyping is well established for the diagnosis of haematological neoplasms. New commercially available systems offer fixed, pre-aliquoted multi-parameter analysis to simplify sample preparation and standardise data analysis.

Objective

The Beckman Coulter (BC) ClearLLab™ 10C (4-tube) system was evaluated against an existing laboratory developed test (LDT).

Methods

Peripheral blood and bone marrow aspirates (n = 101), tested between August 2019 and November 2019 at an academic pathology laboratory in Johannesburg, South Africa, were analysed. Following daily instrument quality control, samples were prepared for LDT (using > 20 2–4-colour in-house panels and an extensive liquid monoclonal reagent repertoire) or ClearLLab 10C, and respectively analysed using in-house protocols on a Becton Dickinson FACSCalibur, or manufacturer-directed protocols on a BC Navios. Becton Dickinson Paint-a-Gate or BC Kaluza C software facilitated data interpretation. Diagnostic accuracy (concordance) was established by calculating sensitivity and specificity outcomes.

Results

Excellent agreement (clinical diagnostic concordance) with 100% specificity and sensitivity was established between LDT and ClearLLab 10C in 67 patients with a haematological neoplasm and 34 participants with no haematological disease. Similar acceptable diagnostic concordance (97%) was noted when comparing ClearLLab 10C to clinicopathological outcomes. Additionally, the ClearLLab 10C panels, analysed with Kaluza C software, enabled simultaneous discrimination of disease and concurrent background myeloid and lymphoid haematological populations, including assessing stages of maturation or sub-populations.

Conclusion

ClearLLab 10C panels provide excellent agreement to existing LDTs and may reliably be used for immunophenotyping of haematological neoplasms, simplifying and standardising sample preparation and data acquisition.

A Chunking-for-Pooling Strategy for Cytometric Representation Learning for Automatic Hematologic Malignancy Classification

Differentiating types of hematologic malignancies is vital to determine therapeutic strategies for the newly diagnosed patients. Flow cytometry (FC) can be used as diagnostic indicator by measuring the multi-parameter fluorescent markers on thousands of antibody-bound cells, but the manual interpretation of large scale flow cytometry data has long been a time-consuming and complicated task for hematologists and laboratory professionals. Past studies have led to the development of representation learning algorithms to perform sample-level automatic classification. In this work, we propose a chunking-for-pooling strategy to include large-scale FC data into a supervised deep representation learning procedure for automatic hematologic malignancy classification. The use of discriminatively-trained representation learning strategy and the fixed-size chunking and pooling design are key components of this framework. It improves the discriminative power of the FC sample-level embedding and simultaneously addresses the robustness issue due to an inevitable use of down-sampling in conventional distribution based approaches for deriving FC representation. We evaluated our framework on two datasets. Our framework outperformed other baseline methods and achieved 92.3% unweighted average recall (UAR) for four-class recognition on the UPMC dataset and 85.0% UAR for five-class recognition on the hema.to dataset. We further compared the robustness of our proposed framework with that of the traditional downsampling approach. Analysis of the effects of the chunk size and the error cases revealed further insights about different hematologic malignancy characteristics in the FC data.

Quality Assessment of a Large Multi-Center Flow Cytometric Dataset of Acute Myeloid Leukemia Patients-A EuroFlow Study

Flowcytometric analysis allows for detailed identification and characterization of large numbers of cells in blood, bone marrow, and other body fluids and tissue samples and therefore contributes to the diagnostics of hematological malignancies. Novel data analysis tools allow for multidimensional analysis and comparison of patient samples with reference databases of normal, reactive, and/or leukemia/lymphoma patient samples. Building such reference databases requires strict quality assessment (QA) procedures. Here, we compiled a dataset and developed a QA methodology of the EuroFlow Acute Myeloid Leukemia (AML) database, based on the eight-color EuroFlow AML panel consisting of six different antibody combinations, including four backbone markers. In total, 1142 AML cases and 42 normal bone marrow samples were included in this analysis. QA was performed on 803 AML cases using multidimensional analysis of backbone markers, as well as tube-specific markers, and data were compared using classical analysis employing median and peak expression values. Validation of the QA procedure was performed by re-analysis of >300 cases and by running an independent cohort of 339 AML cases. Initial evaluation of the final cohort confirmed specific immunophenotypic patterns in AML subgroups; the dataset therefore can reliably be used for more detailed exploration of the immunophenotypic variability of AML. Our data show the potential pitfalls and provide possible solutions for constructing large flowcytometric databases. In addition, the provided approach may facilitate the building of other databases and thereby support the development of novel tools for (semi)automated QA and subsequent data analysis.

Safety and long-term improvement of mesenchymal stromal cell infusion in critically COVID-19 patients: a randomized clinical trial

Background

COVID-19 is a multisystem disease that presents acute and persistent symptoms, the postacute sequelae (PASC). Long-term symptoms may be due to consequences from organ or tissue injury caused by SARS-CoV-2, associated clotting or inflammatory processes during acute COVID-19. Various strategies are being chosen by clinicians to prevent severe cases of COVID-19; however, a single treatment would not be efficient in treating such a complex disease. Mesenchymal stromal cells (MSCs) are known for their immunomodulatory properties and regeneration ability; therefore, they are a promising tool for treating disorders involving immune dysregulation and extensive tissue damage, as is the case with COVID-19. This study aimed to assess the safety and explore the long-term efficacy of three intravenous doses of UC-MSCs (umbilical cord MSCs) as an adjunctive therapy in the recovery and postacute sequelae reduction caused by COVID-19. To our knowledge, this is one of the few reports that presents the longest follow-up after MSC treatment in COVID-19 patients.

Methods

This was a phase I/II, prospective, single-center, randomized, double-blind, placebo-controlled clinical trial. Seventeen patients diagnosed with COVID-19 who require intensive care surveillance and invasive mechanical ventilation—critically ill patients—were included. The patient infusion was three doses of 5 × 10⁵ cells/kg UC-MSCs, with a dosing interval of 48 h (n = 11) or placebo (n = 6). The evaluations consisted of a clinical assessment, viral load, laboratory testing, including blood count, serologic, biochemical, cell subpopulation, cytokines and CT scan.

Results

The results revealed that in the UC-MSC group, there was a reduction in the levels of ferritin, IL-6 and MCP1-CCL2 on the fourteen day. In the second month, a decrease in the levels of reactive C-protein, D-dimer and neutrophils and an increase in the numbers of TCD3, TCD4 and NK lymphocytes were observed. A decrease in extension of lung damage was observed at the fourth month. The improvement in all these parameters was maintained until the end of patient follow-up.

Conclusions

UC-MSCs infusion is safe and can play an important role as an adjunctive therapy, both in the early stages, preventing severe complications and in the chronic phase with postacute sequelae reduction in critically ill COVID-19 patients.

Trial registration Brazilian Registry of Clinical Trials (ReBEC), UTN code-U1111-1254-9819. Registered 31 October 2020—Retrospectively registered, https://ensaiosclinicos.gov.br/rg/RBR-3fz9yr

Supplementary Information

The online version contains supplementary material available at 10.1186/s13287-022-02796-1.

Comprehensive Laboratory Diagnostic Workup for Patients with Suspected Intraocular Lymphoma including Flow Cytometry, Molecular Genetics and Cytopathology

Background: Intraocular lymphoma (IOL) presents a real challenge in daily diagnostics. Cyto- and/or histopathology of vitreous body represent the diagnostic cornerstones. Yet, false negative results remain common. Therefore, we analyzed the diagnostic significance of flow cytometry (FC) within the workup algorithm of IOL and compared its sensitivity with the results obtained from routine cytopathology and molecular genetics; Methods: Seven patients undergoing vitrectomy due to suspected IOL were investigated by FC and parallel cytopathology and, if available, digital droplet PCR (ddPCR) for MYD88 L265P; Results: Four out of seven patients were finally diagnosed with IOL. Among the IOL patients, cytopathology confirmed the presence of lymphoma cells in only two cases. In contrast, FC was positive for IOL in all four cases, and FC additionally confirmed the lack of IOL in the remaining patients. In IOL patients diagnosed by FC and with available ddPCR, the diagnosis of IOL was confirmed by the presence of the MYD88 L265P mutation in all three patients; Conclusions: The combination with FC was superior to cytopathology alone in the diagnostic work-up of IOL, and it showed an excellent correlation with ddPCR results. A comprehensive diagnostic panel consisting of cytopathology, FC and molecular genetics should be considered for the work-up of suspected IOL.

Contemporary Challenges in Clinical Flow Cytometry: Small Samples, Big Data, Little Time

Background

Immunophenotypic analysis of cell populations by flow cytometry has an established role in primary diagnosis and disease monitoring of many hematologic diseases. A persistent problem in evaluation of specimens is suboptimal cell counts and low cell viability, which results in an undesirable rate of analysis failure. In addition, the increased amount of data generated in flow cytometry challenges existing data analysis and reporting paradigms.

Content

We describe current and emerging technological improvements in cell analysis that allow the clinical laboratory to perform multiparameter analysis of specimens, including those with low cell counts and other quality issues. These technologies include conventional multicolor flow cytometry and new high-dimensional technologies, such as spectral flow cytometry and mass cytometry that enable detection of over 40 antigens simultaneously. The advantages and disadvantages of each approach are discussed. We also describe new innovations in flow cytometry data analysis, including artificial intelligence-aided techniques.

Summary

Improvements in analytical technology, in tandem with innovations in data analysis, data storage, and reporting mechanisms, help to optimize the quality of clinical flow cytometry. These improvements are essential because of the expanding role of flow cytometry in patient care.

Age and Primary Vaccination Background Influence the Plasma Cell Response to Pertussis Booster Vaccination

Pertussis is a vaccine-preventable disease caused by the bacterium Bordetella pertussis. Over the past years, the incidence and mortality of pertussis increased significantly. A possible cause is the switch from whole-cell to acellular pertussis vaccines, although other factors may also contribute. Here, we applied high-dimensional flow cytometry to investigate changes in B cells in individuals of different ages and distinct priming backgrounds upon administration of an acellular pertussis booster vaccine. Participants were divided over four age cohorts. We compared longitudinal kinetics within each cohort and between the different cohorts. Changes in the B-cell compartment were correlated to numbers of vaccine-specific B- and plasma cells and serum Ig levels. Expansion and maturation of plasma cells 7 days postvaccination was the most prominent cellular change in all age groups and was most pronounced for more mature IgG1+ plasma cells. Plasma cell responses were stronger in individuals primed with whole-cell vaccine than in individuals primed with acellular vaccine. Moreover, IgG1+ and IgA1+ plasma cell expansion correlated with FHA-, Prn-, or PT- specific serum IgG or IgA levels. Our study indicates plasma cells as a potential early cellular marker of an immune response and contributes to understanding differences in immune responses between age groups and primary vaccination backgrounds.

[Pericardial and myocardial involvement after SARS-CoV-2 infection: a cross-sectional descriptive study in healthcare workers]

Introduction and objectives The cardiac sequelae of SARS-CoV-2 infection are still poorly documented. We conducted a cross-sectional study in healthcare workers to report evidence of pericardial and myocardial involvement after SARS-CoV-2 infection.Methods We studied 139 healthcare workers with confirmed past SARS-CoV-2 infection. Participants underwent clinical assessment, electrocardiography, and laboratory tests, including immune cell profiling and cardiac magnetic resonance (CMR). Clinically suspected pericarditis was diagnosed when classic criteria were present and clinically suspected myocarditis was based on the combination of at least 2 CMR criteria.Results Median age was 52 (41-57) years, 71.9% were women, and 16.5% were previously hospitalized for COVID-19 pneumonia. On examination (10.4 [9.3-11.0] weeks after infection-like symptoms), participants showed hemodynamic stability. Chest pain, dyspnea or palpitations were present in 41.7% participants, electrocardiographic abnormalities in 49.6%, NT-proBNP elevation in 7.9%, troponin in 0.7%, and CMR abnormalities in 60.4%. A total of 30.9% participants met criteria for either pericarditis and/or myocarditis: isolated pericarditis was diagnosed in 5.8%, myopericarditis in 7.9%, and isolated myocarditis in 17.3%. Most participants (73.2%) showed altered immune cell counts in blood, particularly decreased eosinophil (27.3%; P < .001) and increased cytotoxic T cell numbers (17.3%; P < .001). Clinically suspected pericarditis was associated (P < .005) with particularly elevated cytotoxic T cells and decreased eosinophil counts, while participants diagnosed with clinically suspected myopericarditis or myocarditis had lower (P < .05) neutrophil counts, natural killer-cells, and plasma cells.Conclusions Pericardial and myocardial involvement with clinical stability are frequent after SARS-CoV-2 infection and are associated with specific immune cell profiles.

Expert-independent classification of mature B-cell neoplasms using standardized flow cytometry: a multicentric study

Reproducible expert-independent flow-cytometric criteria for the differential diagnoses between mature B-cell neoplasms are lacking. We developed an algorithm-driven classification for these lymphomas by flow cytometry and compared it to the WHO gold standard diagnosis. Overall, 662 samples from 662 patients representing nine disease categories were analyzed at 9 laboratories using the previously published EuroFlow 5-tube-8-color B-cell chronic lymphoproliferative disease antibody panel. Expression levels of all 26 markers from the panel were plotted by B-cell entity to construct a univariate, fully standardized diagnostic reference library. For multivariate data analysis we subsequently utilized Canonical Correlation Analysis of 176 training cases to project the multi-dimensional space of all 26 immunophenotypic parameters into 36 two-dimensional plots for each possible pair-wise differential diagnosis. Diagnostic boundaries were fitted according to the distribution of the immunophenotypes of a given differential diagnosis. A diagnostic algorithm based on these projections was developed and subsequently validated using 486 independent cases. Negative predictive values exceeding 92.1% were observed for all disease categories except for follicular lymphoma. Particularly high positive predictive values were returned in chronic lymphocytic leukemia (99.1%), hairy cell leukemia (97.2%), follicular lymphoma (97.2%) and mantle cell lymphoma (95.4%). Burkitt and CD10+ diffuse large B-cell lymphomas were difficult to distinguish by the algorithm. A similar ambiguity was observed between marginal zone, lymphoplasmacytic, and CD10- diffuse large B-cell lymphomas. The specificity of the approach exceeded 98% for all entities. The univariate immunophenotypic library and the multivariate expert-independent diagnostic algorithm might contribute to increased reproducibility of future diagnostics in mature B-cell neoplasms.

Pericardial and myocardial involvement after SARS-CoV-2 infection: a cross-sectional descriptive study in healthcare workers

Introduction and objectives

The cardiac sequelae of SARS-CoV-2 infection are still poorly documented. We conducted a cross-sectional study in healthcare workers to report evidence of pericardial and myocardial involvement after SARS-CoV-2 infection.

Methods

We studied 139 healthcare workers with confirmed past SARS-CoV-2 infection. Participants underwent clinical assessment, electrocardiography, and laboratory tests, including immune cell profiling and cardiac magnetic resonance (CMR). Clinically suspected pericarditis was diagnosed when classic criteria were present and clinically suspected myocarditis was based on the combination of at least 2 CMR criteria.

Results

Median age was 52 (41-57) years, 71.9% were women, and 16.5% were previously hospitalized for COVID-19 pneumonia. On examination (10.4 [9.3-11.0] weeks after infection-like symptoms), participants showed hemodynamic stability. Chest pain, dyspnea or palpitations were present in 41.7% participants, electrocardiographic abnormalities in 49.6%, NT-proBNP elevation in 7.9%, troponin in 0.7%, and CMR abnormalities in 60.4%. A total of 30.9% participants met criteria for either pericarditis and/or myocarditis: isolated pericarditis was diagnosed in 5.8%, myopericarditis in 7.9%, and isolated myocarditis in 17.3%. Most participants (73.2%) showed altered immune cell counts in blood, particularly decreased eosinophil (27.3%; P < .001) and increased cytotoxic T cell numbers (17.3%; P < .001). Clinically suspected pericarditis was associated (P < .005) with particularly elevated cytotoxic T cells and decreased eosinophil counts, while participants diagnosed with clinically suspected myopericarditis or myocarditis had lower (P < .05) neutrophil counts, natural killer-cells, and plasma cells.

Conclusions

Pericardial and myocardial involvement with clinical stability are frequent after SARS-CoV-2 infection and are associated with specific immune cell profiles.

Artificial Intelligence and Mapping a New Direction in Laboratory Medicine: A Review

BACKGROUND

Modern artificial intelligence (AI) and machine learning (ML) methods are now capable of completing tasks with performance characteristics that are comparable to those of expert human operators. As a result, many areas throughout healthcare are incorporating these technologies, including in vitro diagnostics and, more broadly, laboratory medicine. However, there are limited literature reviews of the landscape, likely future, and challenges of the application of AI/ML in laboratory medicine.

CONTENT

In this review, we begin with a brief introduction to AI and its subfield of ML. The ensuing sections describe ML systems that are currently in clinical laboratory practice or are being proposed for such use in recent literature, ML systems that use laboratory data outside the clinical laboratory, challenges to the adoption of ML, and future opportunities for ML in laboratory medicine.

SUMMARY

AI and ML have and will continue to influence the practice and scope of laboratory medicine dramatically. This has been made possible by advancements in modern computing and the widespread digitization of health information. These technologies are being rapidly developed and described, but in comparison, their implementation thus far has been modest. To spur the implementation of reliable and sophisticated ML-based technologies, we need to establish best practices further and improve our information system and communication infrastructure. The participation of the clinical laboratory community is essential to ensure that laboratory data are sufficiently available and incorporated conscientiously into robust, safe, and clinically effective ML-supported clinical diagnostics.

Anti-TRBC1 Antibody-Based Flow Cytometric Detection of T-Cell Clonality: Standardization of Sample Preparation and Diagnostic Implementation

A single antibody (anti-TRBC1; JOVI-1 antibody clone) against one of the two mutually exclusive T-cell receptor β-chain constant domains was identified as a potentially useful flow-cytometry (FCM) marker to assess Tαβ-cell clonality. We optimized the TRBC1-FCM approach for detecting clonal Tαβ-cells and validated the method in 211 normal, reactive and pathological samples. TRBC1 labeling significantly improved in the presence of CD3. Purified TRBC1⁺ and TRBC1^- monoclonal and polyclonal Tαβ-cells rearranged TRBJ1 in 44/47 (94%) and TRBJ1+TRBJ2 in 48 of 48 (100%) populations, respectively, which confirmed the high specificity of this assay. Additionally, TRBC1⁺/TRBC1^- ratios within different Tαβ-cell subsets are provided as reference for polyclonal cells, among which a bimodal pattern of TRBC1-expression profile was found for all TCRVβ families, whereas highly-variable TRBC1⁺/TRBC1^- ratios were observed in more mature vs. naïve Tαβ-cell subsets (vs. total T-cells). In 112/117 (96%) samples containing clonal Tαβ-cells in which the approach was validated, monotypic expression of TRBC1 was confirmed. Dilutional experiments showed a level of detection for detecting clonal Tαβ-cells of ≤10^-4 in seven out of eight pathological samples. These results support implementation of the optimized TRBC1-FCM approach as a fast, specific and accurate method for assessing T-cell clonality in diagnostic-FCM panels, and for minimal (residual) disease detection in mature Tαβ⁺ leukemia/lymphoma patients.

Machine learning and augmented human intelligence use in histomorphology for haematolymphoid disorders

Advances in digital pathology have allowed a number of opportunities such as decision support using artificial intelligence (AI). The application of AI to digital pathology data shows promise as an aid for pathologists in the diagnosis of haematological disorders. AI-based applications have embraced benign haematology, diagnosing leukaemia and lymphoma, as well as ancillary testing modalities including flow cytometry. In this review, we highlight the progress made to date in machine learning applications in haematopathology, summarise important studies in this field, and highlight key limitations. We further present our outlook on the future direction and trends for AI to support diagnostic decisions in haematopathology.

Dissection of the Pre-Germinal Center B-Cell Maturation Pathway in Common Variable Immunodeficiency Based on Standardized Flow Cytometric EuroFlow Tools

Introduction

Common Variable Immunodeficiency (CVID) is characterized by defective antibody production and hypogammaglobulinemia. Flow cytometry immunophenotyping of blood lymphocytes has become of great relevance for the diagnosis and classification of CVID, due to an impaired differentiation of mature post-germinal-center (GC) class-switched memory B-cells (MBC) and severely decreased plasmablast/plasma cell (Pb) counts. Here, we investigated in detail the pre-GC B-cell maturation compartment in blood of CVID patients.

Methods

In this collaborative multicentric study the EuroFlow PID 8-color Pre-GC B-cell tube, standardized sample preparation procedures (SOPs) and innovative data analysis tools, were used to characterize the maturation profile of pre-GC B-cells in 100 CVID patients, vs 62 age-matched healthy donors (HD).

Results

The Pre-GC B-cell tube allowed identification within pre-GC B-cells of three subsets of maturation associated immature B-cells and three subpopulations of mature naïve B-lymphocytes. CVID patients showed overall reduced median absolute counts (vs HD) of the two more advanced stages of maturation of both CD5⁺ CD38^+/++ CD21^het CD24⁺⁺ (2.7 vs 5.6 cells/µl, p=0.0004) and CD5⁺ CD38^het CD21⁺ CD24⁺ (6.5 vs 17 cells/µl, p<0.0001) immature B cells (below normal HD levels in 22% and 37% of CVID patients). This was associated with an expansion of CD21^-CD24^- (6.1 vs 0.74 cells/µl, p<0.0001) and CD21^-CD24⁺⁺ (1.8 vs 0.4 cells/µl, p<0.0001) naïve B-cell counts above normal values in 73% and 94% cases, respectively. Additionally, reduced IgMD⁺ (21 vs 32 cells/µl, p=0.03) and IgMD^- (4 vs 35 cells/µl, p<0.0001) MBC counts were found to be below normal values in 25% and 77% of CVID patients, respectively, always together with severely reduced/undetectable circulating blood pb. Comparison of the maturation pathway profile of pre-GC B cells in blood of CVID patients vs HD using EuroFlow software tools showed systematically altered patterns in CVID. These consisted of: i) a normally-appearing maturation pathway with altered levels of expression of >1 (CD38, CD5, CD19, CD21, CD24, and/or smIgM) phenotypic marker (57/88 patients; 65%) for a total of 3 distinct CVID patient profiles (group 1: 42/88 patients, 48%; group 2: 8/88, 9%; and group 3: 7/88, 8%) and ii) CVID patients with a clearly altered pre-GC B cell maturation pathway in blood (group 4: 31/88 cases, 35%).

Conclusion

Our results show that maturation of pre-GC B-cells in blood of CVID is systematically altered with up to four distinctly altered maturation profiles. Further studies, are necessary to better understand the impact of such alterations on the post-GC defects and the clinical heterogeneity of CVID.

Automated identification of leukocyte subsets improves standardization of database-guided expert-supervised diagnostic orientation in acute leukemia: a EuroFlow study

Precise classification of acute leukemia (AL) is crucial for adequate treatment. EuroFlow has previously designed an AL orientation tube (ALOT) to guide toward the relevant classification panel and final diagnosis. In this study, we designed and validated an algorithm for automated (database-supported) gating and identification (AGI tool) of cell subsets within samples stained with ALOT. A reference database of normal peripheral blood (PB, n = 41) and bone marrow (BM; n = 45) samples analyzed with the ALOT was constructed, and served as a reference for the AGI tool to automatically identify normal cells. Populations not unequivocally identified as normal cells were labeled as checks and were classified by an expert. Additional normal BM (n = 25) and PB (n = 43) and leukemic samples (n = 109), analyzed in parallel by experts and the AGI tool, were used to evaluate the AGI tool. Analysis of normal PB and BM samples showed low percentages of checks (<3% in PB, <10% in BM), with variations between different laboratories. Manual analysis and AGI analysis of normal and leukemic samples showed high levels of correlation between cell numbers (r² > 0.95 for all cell types in PB and r² > 0.75 in BM) and resulted in highly concordant classification of leukemic cells by our previously published automated database-guided expert-supervised orientation tool for immunophenotypic diagnosis and classification of acute leukemia (Compass tool). Similar data were obtained using alternative, commercially available tubes, confirming the robustness of the developed tools. The AGI tool represents an innovative step in minimizing human intervention and requirements in expertise, toward a "sample-in and result-out" approach which may result in more objective and reproducible data analysis and diagnostics. The AGI tool may improve quality of immunophenotyping in individual laboratories, since high percentages of checks in normal samples are an alert on the quality of the internal procedures.

Improved Standardization of Flow Cytometry Diagnostic Screening of Primary Immunodeficiency by Software-Based Automated Gating

Background

Multiparameter flow cytometry (FC) is essential in the diagnostic work-up and classification of primary immunodeficiency (PIDs). The EuroFlow PID Orientation tube (PIDOT) allows identification of all main lymphocyte subpopulations in blood. To standardize data analysis, tools for Automated Gating and Identification (AG&I) of the informative cell populations, were developed by EuroFlow. Here, we evaluated the contribution of these innovative AG&I tools to the standardization of FC in the diagnostic work-up of PID, by comparing AG&I against expert-based (EuroFlow-standardized) Manual Gating (MG) strategy, and its impact on the reproducibility and clinical interpretation of results.

Methods

FC data files from 44 patients (13 CVID, 12 PID, 19 non-PID) and 26 healthy donor (HD) blood samples stained with PIDOT were analyzed in parallel by MG and AG&I, using Infinicyt™ software (Cytognos). For comparison, percentage differences in absolute cell counts/µL were calculated for each lymphocyte subpopulation. Data files showing differences >20% were checked for their potential clinical relevance, based on age-matched percentile (p5-p95) reference ranges. In parallel, intra- and inter-observer reproducibility of MG vs AG&I were evaluated in a subset of 12 samples.

Results

The AG&I approach was able to identify the vast majority of lymphoid events (>99%), associated with a significantly higher intra- and inter-observer reproducibility compared to MG. For most HD (83%) and patient (68%) samples, a high degree of agreement (<20% numerical differences in absolute cell counts/µL) was obtained between MG and the AG&I module. This translated into a minimal impact (<5% of observations) on the final clinical interpretation. In all except three samples, extended expert revision of the AG&I approach revealed no error. In the three remaining samples aberrant maturation and/or abnormal marker expression profiles were seen leading in all three cases to numerical alarms by AG&I.

Conclusion

Altogether, our results indicate that replacement of MG by the AG&I module would be associated with a greater reproducibility and robustness of results in the diagnostic work-up of patients suspected of PID. However, expert revision of the results of AG&I of PIDOT data still remains necessary in samples with numerical alterations and aberrant B- and T-cell maturation and/or marker expression profiles.

Computational analysis of flow cytometry data in hematological malignancies: future clinical practice?

PURPOSE OF REVIEW

This review outlines the advancements that have been made in computational analysis for clinical flow cytometry data in hematological malignancies.

RECENT FINDINGS

In recent years, computational analysis methods have been applied to clinical flow cytometry data of hematological malignancies with promising results. Most studies combined dimension reduction (principle component analysis) or clustering methods (FlowSOM, generalized mixture models) with machine learning classifiers (support vector machines, random forest). For diagnosis and classification of hematological malignancies, many studies have reported results concordant with manual expert analysis, including B-cell chronic lymphoid leukemia detection and acute leukemia classification. Other studies, e.g. concerning diagnosis of myelodysplastic syndromes and classification of lymphoma, have shown to be able to increase diagnostic accuracy. With respect to treatment response monitoring, studies have focused on, for example, computational minimal residual disease detection in multiple myeloma and posttreatment classification of healthy or diseased in acute myeloid leukemia. The results of these studies are encouraging, although accurate relapse prediction remains challenging. To facilitate clinical implementation, collaboration and (prospective) validation in multicenter setting are necessary.

SUMMARY

Computational analysis methods for clinical flow cytometry data hold the potential to increase ease of use, objectivity and accuracy in the clinical work-up of hematological malignancies.