Unravelling B cell heterogeneity: insights into flow cytometry-gated B cells from single-cell multi-omics data.

Introduction: B cells play a pivotal role in adaptive immunity which has been extensively characterised primarily via flow cytometry-based gating strategies. This study addresses the discrepancies between flow cytometry-defined B cell subsets and their high-confidence molecular signatures using single-cell multi-omics approaches. Methods: By analysing multi-omics single-cell data from healthy individuals and patients across diseases, we characterised the level and nature of cellular contamination within standard flow cytometric-based gating, resolved some of the ambiguities in the literature surrounding unconventional B cell subsets, and demonstrated the variable effects of flow cytometric-based gating cellular heterogeneity across diseases. Results: We showed that flow cytometric-defined B cell populations are heterogenous, and the composition varies significantly between disease states thus affecting the implications of functional studies performed on these populations. Importantly, this paper draws caution on findings about B cell selection and function of flow cytometric-sorted populations, and their roles in disease. As a solution, we developed a simple tool to identify additional markers that can be used to increase the purity of flow-cytometric gated immune cell populations based on multi-omics data (AlliGateR). Here, we demonstrate that additional non-linear CD20, CD21 and CD24 gating can increase the purity of both naïve and memory populations. Discussion: These findings underscore the need to reconsider B cell subset definitions within the literature and propose leveraging single-cell multi-omics data for refined characterisation. We show that single-cell multi-omics technologies represent a powerful tool to bridge the gap between surface marker-based annotations and the intricate molecular characteristics of B cell subsets.

Detection of clonal plasma cells in POEMS syndrome using multiparameter flow cytometry.

POEMS syndrome (polyneuropathy, organomegaly, endocrinopathy, monoclonal protein [M-protein], and skin changes) is a rare systemic disorder characterized by various symptoms caused by underlying plasma cell (PC) dyscrasia. Detection of monoclonal PCs is mandatory for the diagnosis of POEMS syndrome; however, the usefulness of EuroFlow-based next-generation flow cytometry (EuroFlow-NGF) in POEMS syndrome for detecting monoclonal PCs in bone marrow (BM) and the gating strategy suitable for flow cytometry study of POEMS syndrome remain unknown. We employed EuroFlow-NGF-based single-tube eight-color multiparameter flow cytometry (MM-flow) and established a new gating strategy (POEMS-flow) to detect the monoclonal PCs in POEMS syndrome, gating CD38 broadly from dim to bright and CD45 narrowly from negative to dim compared to MM-flow. MM-flow detected monoclonal PCs in 9/25 (36.0%) cases, including 2/2 immunofixation electrophoresis (IFE)-negative cases (100%). However, POEMS-flow detected monoclonal PCs in 18/25 cases (72.0%), including 2/2 IFE-negative cases (100%). POEMS-flow detected monoclonal PCs with immunophenotypes of CD19- in 17/18 (94.4%). In six cases where post-treatment samples were available, the size of the clones was significantly reduced after the treatment (P = 0.031). POEMS-flow can enhance the identification rate of monoclonal PCs in POEMS syndrome and become a valuable tool for the diagnosis of POEMS syndrome.

Harmonized analysis of PBMC by mass cytometry.

Mass cytometry permits the high dimensional analysis of cellular systems at single-cell resolution with high throughput in various areas of biomedical research. Here, we provide a state-of-the-art protocol for the analysis of human peripheral blood mononuclear cells (PBMC) by mass cytometry. We focus on the implementation of measures promoting the harmonization of large and complex studies to aid robustness and reproducibility of immune phenotyping data.

Immunophenotyping challenging tissue types using high-dimensional full spectrum flow cytometry.

Technological advancements in fluorescence flow cytometry and an ever-expanding understanding of the complexity of the immune system, have led to the development of large flow cytometry panels, reaching up to 40 markers at the single-cell level. Full spectrum flow cytometry, that measures the full emission range of all the fluorophores present in the panel instead of only the emission peaks is now routinely used in many laboratories internationally, and the demand for this technology is rapidly increasing. With the capacity to use larger and more complex staining panels, optimized protocols are required for the best panel design, panel validation and high-dimensional data analysis outcomes. In addition, for ex vivo experiments, tissue preparation methods for single-cell analysis should also be optimized to ensure that samples are of the highest quality and are truly representative of tissues in situ. Here we provide optimized step-by-step protocols for full spectrum flow cytometry panel design, tissue digestion and panel optimization to facilitate the analysis of challenging tissue types.

Coupling imaging mass cytometry with Alcian blue histochemical staining for a single-slide approach.

Imaging mass cytometry (IMC) is a metal mass spectrometry-based method allowing highly multiplex immunophenotyping of cells within tissue samples. However, some limitations of IMC are its 1-µm resolution and its time and costs of analysis limiting respectively the detailed histopathological analysis of IMC-produced images and its application to small selected tissue regions of interest (ROI) of one to few square millimeters. Coupling on a single-tissue section, IMC and histopathological analyses could permit a better selection of the ROI for IMC analysis as well as co-analysis of immunophenotyping and histopathological data until the single-cell level. The development of this method is the aim of the present study in which we point to the feasibility of applying the IMC process to tissue sections previously Alcian blue-stained and digitalized before IMC tissue destructive analyses. This method could help to improve the process of IMC in terms of ROI selection, time of analysis, and the confrontation between histopathological and immunophenotypic data of cells.

Comprehensive analysis of human monocyte subsets using full-spectrum flow cytometry and hierarchical marker clustering.

Introduction: Exploring monocytes' roles within the tumor microenvironment is crucial for crafting targeted cancer treatments. Methods: This study unveils a novel methodology utilizing four 20-color flow cytometry panels for comprehensive peripheral immune system phenotyping, specifically targeting classical, intermediate, and non-classical monocyte subsets. Results: By applying advanced dimensionality reduction techniques like t-distributed stochastic neighbor embedding (tSNE) and FlowSom analysis, we performed an extensive profiling of monocytes, assessing 50 unique cell surface markers related to a wide range of immunological functions, including activation, differentiation, and immune checkpoint regulation. Discussion: This in-depth approach significantly refines the identification of monocyte subsets, directly supporting the development of personalized immunotherapies and enhancing diagnostic precision. Our pioneering panel for monocyte phenotyping marks a substantial leap in understanding monocyte biology, with profound implications for the accuracy of disease diagnostics and the success of checkpoint-inhibitor therapies. Key findings include revealing distinct marker expression patterns linked to tumor progression and providing new avenues for targeted therapeutic interventions.

Multiparameter Flow Cytometry Monitoring of T Cell Responses.

Multiparameter flow cytometry is a common tool for assessing responses of T, B, and other cells to pathogens or vaccines. Such responses are likely to be important for predicting the efficacy of an HIV vaccine, despite the elusive findings in HIV vaccine trials to date. Fortunately, flow cytometry has evolved to be capable of readily measuring 30-40 parameters, providing the ability to dissect detailed phenotypes and functions that may be correlated with disease protection. Nevertheless, technical hurdles remain, and standardization of assays is still largely lacking. Here an optimized protocol for antigen-specific T cell monitoring is presented, with specific variations for particular markers. It covers the analysis of multiple cytokines, cell surface proteins, and other functional markers such as CD107, CD154, CD137, etc. References are given to published panels of 8-28 colors.

Clinical Characteristics and Diagnosis of Ph-Positive Mixed Phenotype Acute Leukemia.

BACKGROUND: The goal was to improve the clinical cognition of Ph-positive mixed phenotype acute leukemia and avoid misdiagnosis or delayed diagnosis. METHODS: The clinical manifestations and laboratory results (bone marrow cell morphology, multiparameter flow cytometry, and cytogenetics) of a case of Ph-positive mixed phenotype acute leukemia were analyzed, and related literature was reviewed. RESULTS: Blood routine: WBC 386.35 x 109/L, HGB 117.00 g/L, PLT 31 x 109/L; 80% of the original cells can be seen by artificial classification. Morphological examination of bone marrow cells showed that the proliferation of nucleated cells was obviously active, and the original cells accounted for 76%. The size of the original cells was somewhat uniform, most of the cells had less mass, were stained light grayish blue, the cytoplasm particles were not obvious, the nuclei were mostly round or quasi-round, some of them showed distortion and nuclear notch, and the chromatin was coarse. Some of the cells were rich in mass, small azurin granules were seen, the nuclei were regular, most of them were round, the chromatin was fine, the myeloperoxidase and esterase staining were negative, the eosinophils accounted for 2.5%, and the basophils accounted for 0.5%. Flow cytometry immunotyping: Two groups of abnormal cells were seen in the bone marrow. 1. A group included 12.32% of nuclear cells and showed abnormal myeloid primitive cell phenotype. Main expression: CD117, CD34, CD38, HLA-DR, CD33, CD64, CD123, weak expression: CD13, CD19. 2. The other group included 45.61% of the nuclear cells and had a B-lymphoblastic phenotype. Main expression: CD34, CD38, HLA-DR, CD123, CD19, CD10, CD9, cCD79a, TDT, weak expression of CD13, CD22. Mixed phenotype acute leukemia (M/B) immunophenotype was considered. Chromosome: 46,XY,t(9; 22)(q34;q11.2) [20]. BCR-ABL (P210) fusion gene was positive. CONCLUSIONS: Mixed phenotype acute leukemia (MPAL) is a rare type of malignant hematologic disease. Its diagnosis is based on the comprehensive evaluation of bone marrow cell morphology, immunophenotype, molecular and cytogenetic features.

Research and Analysis of Molecules such as CD28, CD45RA, CD45RO, CD38, HLA-DR, and CD57 on T Cells in Multiple Myeloma.

BACKGROUND: For many years it has been postulated that the immune system controls the progress of multiple myeloma (MM). However, the phenotypes of T cells in MM remain to be elucidated. In this study, we compared the phenotypes of T cells, which were obtained from the peripheral blood, in MM patients with those in healthy donors (HD). The expression of CCR7, CD57, CD28, HLA-DR, CD38, CD45RA, and CD45RO were assessed on T cells from MM patients and HDs using multicolor flow cytometry (MFC). METHODS: For this study, 17 newly diagnosed MM patients were selected, and 20 healthy people were selected as a control group. MFC was used to detect the markers on T cells. RESULTS: We detected significant increases in the expression levels of HLA-DR, CD38, and CD57on CD8+ T cells, significant decreases in the expression levels of CD28 and CD45RA on CD8+ T cells, and a decrease of CD4+ effec-tor T cells in MM patients, compared to the HD group. CONCLUSIONS: Our study shows that the accumulation of peripheral CD8+CD57+T cells, CD8+CD38high T cells, and CD8+HLA-DR+CD38high T cells is reflective of an ongoing antitumor T cell response and a progressive immune dysfunction in MM. During chemotherapy, the recovery of immune function can be monitored by detecting the proportion of activated molecules of T lymphocytes.

TRBC1 in flow cytometry: Assay development, validation, and reporting considerations.

The assessment of T-cell clonality by flow cytometry has long been suboptimal, relying on aberrant marker expression and/or intensity. The introduction of TRBC1 shows much promise for improving the diagnosis of T-cell neoplasms in the clinical flow laboratory. Most laboratories considering this marker already have existing panels designed for T-cell workups and will be determining how best to incorporate TRBC1. We present this comprehensive summary of TRBC1 and supplemental case examples to familiarize the flow cytometry community with its potential for routine application, provide examples of how to incorporate it into T-cell panels, and signal caution in interpreting the results in certain diagnostic scenarios where appropriate.

Technical, gating and interpretation recommendations for the partitioning of circulating monocyte subsets assessed by flow cytometry.

The monocyte subset partitioning by flow cytometry, known as "monocyte assay," is now integrated into the new classifications as a supporting criterion for CMML diagnosis, if a relative accumulation of classical monocytes above 94% of total circulating monocytes is observed. Here we provide clinical flow cytometry laboratories with technical support adapted for the most commonly used cytometers. Step-by-step explanations of the gating strategy developed on whole peripheral blood are presented while underlining the most common difficulties. In a second part, interpretation recommendations of circulating monocyte partitioning from the dedicated French working group "CytHem-LMMC" are shared as well as the main pitfalls, including false positive and false negative cases. The particular flow-defined inflammatory profile is described and the usefulness of the nonclassical monocyte specific marker, namely slan, highlighted. Examples of reporting to the physician with frequent situations encountered when using the monocyte assay are also presented.

The causal role of circulating immunity-inflammation in preeclampsia: A Mendelian randomization.

Patients with systemic autoimmune diseases, such as systemic lupus erythematosus, were at a higher risk for preeclampsia. The causal relationship between immunological inflammation and preeclampsia (PE) remains uncertain. We aimed to investigate the causal relationship between circulating immune inflammation and PE. Genetically predicted blood immune cells and circulating inflammatory proteins were identified using two genome-wide association studies (GWAS). We used a two-sample Mendelian randomization (MR) method to determine whether circulating immunological inflammation causes PE. Our findings indicated that ten immunophenotypes were identified to be significantly associated with PE risk: CD62L- Dendritic Cell Absolute Count, CD86+ myeloid Dendritic Cell %Dendritic Cell, CD62L- myeloid Dendritic Cell Absolute Count, CD86+ myeloid Dendritic Cell Absolute Count, CD62L- myeloid Dendritic Cell %Dendritic Cell, CD62L- CD86+ myeloid Dendritic Cell %Dendritic Cell, CD62L- CD86+ myeloid Dendritic Cell Absolute Count, CD16 on CD14+ CD16+ monocyte, HLA DR+ Natural Killer Absolute Count, and T cell Absolute Count. Ninety-one inflammation-related proteins had no statistically significant effect on PE following false discovery rate (FDR) correction. Certain proteins exhibited unadjusted low p-values that merited mention. These proteins include interleukin-10 (OR = 0.76, 95%CI = 0.63-0.93, p = .006), fibroblast growth factor 21 (OR = 1.23, 95%CI = 1.01-1.47, p = .035), and Caspase 8 (OR = 0.65, 95%CI = 0.50-0.85, p = .001). The ELISA analysis demonstrated elevated levels of FGF-21 and decreased levels of IL-10 and Caspase-8 in the plasma of patients with PE. These findings reveal that immunophenotypes and circulating inflammatory proteins may induce PE, confirming the importance of peripheral Immunity-Inflammation in PE. The discovery has the potential to lead to earlier detection and more effective treatment techniques.

Faster clinical decisions in B-cell acute lymphoblastic leukaemia: A single flow cytometric 12-colour tube improves diagnosis and minimal residual disease follow-up.

Assessing minimal residual disease (MRD) in B-cell precursor acute lymphoblastic leukaemia (BCP-ALL) is essential for adjusting therapeutic strategies and predicting relapse. Quantitative polymerase chain reaction (qPCR) is the gold standard for MRD. Alternatively, flow cytometry is a quicker and cost-effective method that typically uses leukaemia-associated immunophenotype (LAIP) or different-from-normal (DFN) approaches for MRD assessment. This study describes an optimized 12-colour flow cytometry antibody panel designed for BCP-ALL diagnosis and MRD monitoring in a single tube. This method robustly differentiated hematogones and BCP-ALL cells using two specific markers: CD43 and CD81. These and other markers (e.g. CD73, CD66c and CD49f) enhanced the specificity of BCP-ALL cell detection. This innovative approach, based on a dual DFN/LAIP strategy with a principal component analysis method, can be used for all patients and enables MRD analysis even in the absence of a diagnostic sample. The robustness of our method for MRD monitoring was confirmed by the strong correlation (r = 0.87) with the qPCR results. Moreover, it simplifies and accelerates the preanalytical process through the use of a stain/lysis/wash method within a single tube (<2 h). Our flow cytometry-based methodology improves the BCP-ALL diagnosis efficiency and MRD management, offering a complementary method with considerable benefits for clinical laboratories.

From the archives of MD Anderson Cancer Center: Monomorphic epitheliotropic intestinal T-cell lymphoma: A case with an unusual immunophenotype and discussion of differential diagnosis.

Monomorphic epitheliotropic intestinal T-cell lymphoma (MEITL) is a rare and aggressive T-cell neoplasm associated with poor survival. We report a case of MEITL that presented as an ulcerated mass in the jejunum with perforation. Microscopic examination showed that the neoplasm involved the full thickness of the intestinal wall, extended into the mesentery, and was composed of monomorphic, small to medium-size cells. Immunohistochemical analysis showed that the neoplastic cells were positive for T-cell receptor (TCR) delta, CD3, CD7, CD8 (small subset), BCL-2 and TIA-1, and negative for TCR beta, CD4, CD5, CD10, CD20, CD30, CD34, CD56, CD57, CD99, ALK, cyclin D1, granzyme B, MUM1/IRF4, and TdT. The Ki-67 proliferation index was approximately 50 %. In situ hybridization for Epstein-Barr virus-encoded RNA (EBER ISH) was negative. Next-generation sequencing (NGS) analysis showed mutations involving SETD2 and STAT5B. The patient was treated with aggressive chemotherapy and consolidative autologous stem cell transplant and had clinical remission, but relapsed after about one year. Retreatment led to another one-year interval of clinical remission, but at last follow up the patient has relapsed disease involving the ileum and colon. We also discuss the differential diagnosis of MEITL.

Machine learning aided single cell image analysis improves understanding of morphometric heterogeneity of human mesenchymal stem cells.

The multipotent stem cells of our body have been largely harnessed in biotherapeutics. However, as they are derived from multiple anatomical sources, from different tissues, human mesenchymal stem cells (hMSCs) are a heterogeneous population showing ambiguity in their in vitro behavior. Intra-clonal population heterogeneity has also been identified and pre-clinical mechanistic studies suggest that these cumulatively depreciate the therapeutic effects of hMSC transplantation. Although various biomarkers identify these specific stem cell populations, recent artificial intelligence-based methods have capitalized on the cellular morphologies of hMSCs, opening a new approach to understand their attributes. A robust and rapid platform is required to accommodate and eliminate the heterogeneity observed in the cell population, to standardize the quality of hMSC therapeutics globally. Here, we report our primary findings of morphological heterogeneity observed within and across two sources of hMSCs namely, stem cells from human exfoliated deciduous teeth (SHEDs) and human Wharton jelly mesenchymal stem cells (hWJ MSCs), using real-time single-cell images generated on immunophenotyping by imaging flow cytometry (IFC). We used the ImageJ software for identification and comparison between the two types of hMSCs using statistically significant morphometric descriptors that are biologically relevant. To expand on these insights, we have further applied deep learning methods and successfully report the development of a Convolutional Neural Network-based image classifier. In our research, we introduced a machine learning methodology to streamline the entire procedure, utilizing convolutional neural networks and transfer learning for binary classification, achieving an accuracy rate of 97.54%. We have also critically discussed the challenges, comparisons between solutions and future directions of machine learning in hMSC classification in biotherapeutics.

Streamlined measurement of chimeric antigen receptor T-cell concentration, size, viability and two-color phenotyping during manufacturing.

BACKGROUND AIMS: The successful development of CD19-targeted chimeric antigen receptor (CAR) T-cell therapies has led to an exponential increase in the number of patients recieving treatment and the advancement of novel CAR T products. Therefore, there is a strong need to develop streamlined platforms that allow rapid, cost-effective, and accurate measurement of the key characteristics of CAR T cells during manufacturing (i.e., cell number, cell size, viability, and basic phenotype). METHODS: In this study, we compared the novel benchtop cell analyzer Moxi GO II (ORFLO Technologies), which enables simultaneous evaluation of all the aforementioned parameters, with current gold standards in the field: the Multisizer Coulter Counter (cell counter) and the BD LSRFortessa (flow cytometer). RESULTS: Our results demonstrated that the Moxi GO II can accurately measure cell number and cell size (i.e., cell volume) while simultaneously assessing simple two-color flow cytometry parameters, such as CAR T-cell viability and CD4 or CAR expression. CONCLUSIONS: These measurements are comparable with those of gold standard instruments, demonstrating that the Moxi GO II is a promising platform for quickly monitoring CAR T-cell growth and phenotype in research-grade and clinical samples.

Extended characterization of anti-CD19 CAR T cell products manufactured at the point of care using the CliniMACS Prodigy system: comparison of donor sources and process duration.

BACKGROUND AIMS: The CliniMACS Prodigy closed system is widely used for the manufacturing of chimeric antigen receptor T cells (CAR-T cells). Our study presents an extensive immunophenotypic and functional characterization and comparison of the properties of anti-CD19 CAR-T cell products obtained during long (11 days) and short (7 days) manufacturing cycles using the CliniMACS Prodigy system, as well as cell products manufactured from different donor sources of T lymphocytes: from patients, from patients who underwent HSCT, and from haploidentical donors. We also present the possibility of assessing the efficiency of transduction by an indirect method. METHODS: Seventy-six CD19 CAR-T cell products were manufactured using the CliniMACS Prodigy automated system. Immunophenotypic properties, markers of cell activation and exhaustion, antitumor, anti-CD19 specific activity in vitro of the manufactured cell products were evaluated. As an indirect method for assessing the efficiency of transduction, we used the method of functional assessment of cytokine secretion and expression of the CD107a marker after incubation of CAR-T cells with tumor targets. RESULTS: The CliniMACS Prodigy platform can produce a product of CD19 CAR-T cells with sufficient cell expansion (4.6 × 109 cells-median for long process [LP] and 1.6 × 109-for short process [SP]), transduction efficiency (43.5%-median for LP and 41.0%-for SP), represented mainly by T central memory cell population, with low expression of exhaustion markers, and with high specific antitumor activity in vitro. We did not find significant differences in the properties of the products obtained during the 7- and 11-day manufacturing cycles, which is in favor of reducing the duration of production to 7 days, which may accelerate CAR-T therapy. We have shown that donor sources for CAR-T manufacturing do not significantly affect the composition and functional properties of the cell product. CONCLUSIONS: This study demonstrates the possibility of using the CliniMACS Prodigy system with a shortened 7-day production cycle to produce sufficient amount of functional CAR-T cells. CAR transduction efficiency can be measured indirectly via functional assays.

Automated tumor immunophenotyping predicts clinical benefit from anti-PD-L1 immunotherapy.

Cancer immunotherapy has transformed the clinical approach to patients with malignancies, as profound benefits can be seen in a subset of patients. To identify this subset, biomarker analyses increasingly focus on phenotypic and functional evaluation of the tumor microenvironment to determine if density, spatial distribution, and cellular composition of immune cell infiltrates can provide prognostic and/or predictive information. Attempts have been made to develop standardized methods to evaluate immune infiltrates in the routine assessment of certain tumor types; however, broad adoption of this approach in clinical decision-making is still missing. We developed approaches to categorize solid tumors into 'desert', 'excluded', and 'inflamed' types according to the spatial distribution of CD8+ immune effector cells to determine the prognostic and/or predictive implications of such labels. To overcome the limitations of this subjective approach, we incrementally developed four automated analysis pipelines of increasing granularity and complexity for density and pattern assessment of immune effector cells. We show that categorization based on 'manual' observation is predictive for clinical benefit from anti-programmed death ligand 1 therapy in two large cohorts of patients with non-small cell lung cancer or triple-negative breast cancer. For the automated analysis we demonstrate that a combined approach outperforms individual pipelines and successfully relates spatial features to pathologist-based readouts and the patient's response to therapy. Our findings suggest that tumor immunophenotype generated by automated analysis pipelines should be evaluated further as potential predictive biomarkers for cancer immunotherapy. © 2024 The Pathological Society of Great Britain and Ireland.