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Objective: This study aims to comprehensively investigate immune‐cell landscapes in ankylosing spondylitis (AS) patients and explore longitudinal immunophenotyping changes induced by biological agents. Methods: We employed mass cytometry with 35 cellular markers to analyze blood samples from 34 AS patients and 13 healthy controls (HC). Eleven AS patients were re‐evaluated 1 month (4 patients) and 3 months (7 patients) after treatment with biological agents. Flow Self‐Organizing Maps (FlowSOM) clustering was performed to identify specific cellular metaclusters. We compared cellular abundances across distinct subgroups and validated subset differences using gating strategies in flow cytometry scatter plots, visualized with FlowJo software. The proportions of differential subsets were then used for intercellular and clinical correlation analysis, as well as for constructing diagnostic models based on the random forest algorithm. Results: In AS patients, we identified and validated nine different immune‐cell subsets compared to HC. Three subsets increased: helper T‐cell 17 (Th17), mucosa‐associated invariant T‐cell (MAIT), and classical monocytes (CM). Six subsets decreased: effector memory T‐cell (TEM), naïve B cells, transitional B cells, IL10+ memory B cells, non‐classical monocytes (NCM), and neutrophils. Treatments with biological agents could rectify cellular abnormalities, particularly the imbalance of CM/NCM. Furthermore, these subsets may serve as biomarkers for assessing disease activity and constructing effective diagnostic models for AS. Conclusion: These findings provide novel insights into the specific patterns of immune cell in AS, facilitating the further development of novel biomarkers and potential therapeutic targets for AS patients. [ABSTRACT FROM AUTHOR]

Senescence is an irreversible arrest of the cell cycle that can be characterized by markers of senescence such as p16, p21, and KI‐67. The characterization of different senescence‐associated phenotypes requires selection of the most relevant senescence markers to define reliable cytometric methodologies. Mass cytometry (a.k.a. Cytometry by time of flight, CyTOF) can monitor up to 40 different cell markers at the single‐cell level and has the potential to integrate multiple senescence and other phenotypic markers to identify senescent cells within a complex tissue such as skeletal muscle, with greater accuracy and scalability than traditional bulk measurements and flow cytometry‐based measurements. This article introduces an analysis framework for detecting putative senescent cells based on clustering, outlier detection, and Boolean logic for outliers. Results show that the pipeline can identify putative senescent cells in skeletal muscle with well‐established markers such as p21 and potential markers such as GAPDH. It was also found that heterogeneity of putative senescent cells in skeletal muscle can partly be explained by their cell type. Additionally, autophagy‐related proteins ATG4A, LRRK2, and GLB1 were identified as important proteins in predicting the putative senescent population, providing insights into the association between autophagy and senescence. It was observed that sex did not affect the proportion of putative senescent cells among total cells. However, age did have an effect, with a higher proportion observed in fibro/adipogenic progenitors (FAPs), satellite cells, M1 and M2 macrophages from old mice. Moreover, putative senescent cells from muscle of old and young mice show different expression levels of senescence‐related proteins, with putative senescent cells of old mice having higher levels of p21 and GAPDH, whereas putative senescent cells of young mice had higher levels of IL‐6. Overall, the analysis framework prioritizes multiple senescence‐associated proteins to characterize putative senescent cells sourced from tissue made of different cell types. [ABSTRACT FROM AUTHOR]

Background: Angong Niuhuang Wan (AGNHW, 安宫牛黄丸), is a classical medicinal formula in Traditional Chinese Medicine (TCM) that has been appreciated for its neuroprotective properties in ischemic cerebral injuries, yet its intricate mechanisms remain only partially elucidated. Aims: This study leverages advanced Mass cytometry (CyTOF) to analyze AGNHW's multifaceted immunomodulation effects in‐depth, emphasizing previously underexplored areas. Results: AGNHW mitigated monocyte‐derived macrophages (MoDM) infiltration in the brain, distinguishing its effects on those from microglia. While the vehicle group exhibited elevated inflammatory markers like CD4, CD8a, and CD44 in ischemic brains, the AGNHW‐treated group attenuated their expressions, indicating AGNHW's potential to temper the post‐ischemic inflammatory response. Systemically, AGNHW modulated fundamental immune cell dynamics, notably augmenting CD8+ T cells, B cells, monocytes, and neutrophil counts in the peripheral blood under post‐stroke conditions. Intracellularly, AGNHW exhibited its targeted modulation of the signaling pathways, revealing a remarked inhibition of key markers like IκBα, indicating potential suppression of inflammatory responses in ischemic brain injuries. Conclusion: This study offers a comprehensive portrait of AGNHW's immunomodulation effects on ischemic stroke, illuminating its dual sites of action—both cerebral and systemic—and its nuanced modulation of cellular and molecular dynamics. [ABSTRACT FROM AUTHOR]

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis with a 5‐year survival of less than 10%. More knowledge of the immune response developed in patients with PDAC is pivotal to develop better combination immune therapies to improve clinical outcome. In this study, we used mass cytometry time‐of‐flight to undertake an in‐depth characterization of PBMCs from patients with PDAC and examine the differences with healthy controls and patients with benign diseases of the biliary system or pancreas. Peripheral blood mononuclear cells from patients with PDAC or benign disease are characterized by the increase of pro‐inflammatory cells, as CD86+ classical monocytes and memory T cells expressing CCR6+ and CXCR3+, associated with T helper 1 (Th1) and Th17 immune responses, respectively. However, PBMCs from patients with PDAC present also an increase of CD39+ regulatory T cells and CCR4+CCR6−CXCR3− memory T cells, suggesting Th2 and regulatory responses. Concluding, our results show PDAC develops a multifaceted immunity, where a proinflammatory component is accompanied by regulatory responses, which could inhibit potential antitumor mechanisms. [ABSTRACT FROM AUTHOR]

Objectives: Data on peripheral blood mononuclear cells (PBMCs) characteristics of aquaporin‐4 (AQP4)‐IgG seropositive neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody‐associated disease (MOGAD) are lacking. In this study, we describe the whole PBMCs landscape of the above diseases using cytometry by time‐of‐flight mass spectrometry (CyTOF). Methods: The immune cell populations were phenotyped and clustered using CyTOF isolated from 27 AQP4‐IgG seropositive NMOSD, 11 MOGAD patients, and 15 healthy individuals. RNA sequencing was employed to identify critical genes. Fluorescence cytometry and qPCR analysis were applied to further validate the algorithm‐based results that were obtained. Results: We identified an increased population of CD11b+ mononuclear phagocytes (MNPs) in patients with high expression of CCR2, whose abundance may correlate with brain inflammatory infiltration. Using fluorescence cytometry, we confirmed the CCR2+ monocyte subsets in a second cohort of patients. Moreover, there was a wavering of B, CD4+ T, and NKT cells between AQP4‐IgG seropositive NMOSD and MOGAD. Conclusions: Our findings describe the whole landscape of PBMCs in two similar demyelinated diseases and suggest that, besides MNPs, T, NK and B, cells were all involved in the pathogenesis. The identified cell population may be used as a predictor for monitoring disease development or treatment responses. [ABSTRACT FROM AUTHOR]

Systemic Lupus Erythematosus (SLE) etiopathogenesis highlights the contributions of overproduction of CD4+ T cells and loss of immune tolerance. However, the involvement of CD8+ T cells in SLE pathology and disease progression remains unclear. Here, the comprehensive immune cell dysregulation in total 263 clinical peripheral blood samples composed of active SLE (aSLE), remission SLE (rSLE) and healthy controls (HCs) is investigated via mass cytometry, flow cytometry and single‐cell RNA sequencing. This is observed that CD8+CD27+CXCR3− T cells are increased in rSLE compare to aSLE. Meanwhile, the effector function of CD8+CD27+CXCR3− T cells are overactive in aSLE compare to HCs and rSLE, and are positively associated with clinical SLE activity. In addition, the response of peripheral blood mononuclear cells (PBMCs) is monitored to interleukin‐2 stimulation in aSLE and rSLE to construct dynamic network biomarker (DNB) model. It is demonstrated that DNB score‐related parameters can faithfully predict the remission of aSLE and the flares of rSLE. The abundance and functional dysregulation of CD8+CD27+CXCR3− T cells can be potential biomarkers for SLE prognosis and concomitant diagnosis. The DNB score with accurate prediction to SLE disease progression can provide clinical treatment suggestions especially for drug dosage determination. [ABSTRACT FROM AUTHOR]

Objective: The importance of inflammation in atherosclerosis is well accepted, but the role of the adaptive immune system is not yet fully understood. To further explore this, we assessed the circulating immune cell profile of patients with coronary artery disease (CAD) to identify discriminatory features by mass cytometry. Methods: Mass cytometry was performed on patient samples from the BioHEART‐CT study, gated to detect 82 distinct cell subsets. CT coronary angiograms were analysed to categorise patients as having CAD (CAD+) or having normal coronary arteries (CAD−). Results: The discovery cohort included 117 patients (mean age 61 ± 12 years, 49% female); 79 patients (68%) were CAD+. Mass cytometry identified changes in 15 T‐cell subsets, with higher numbers of proliferating, highly differentiated and cytotoxic cells and decreases in naïve T cells. Five T‐regulatory subsets were related to an age and gender‐independent increase in the odds of CAD incidence when expressing CCR2 (OR 1.12), CCR4 (OR 1.08), CD38 and CD45RO (OR 1.13), HLA‐DR (OR 1.06) and Ki67 (OR 1.22). Markers of proliferation and differentiation were also increased within B cells, while plasmacytoid dendritic cells were decreased. This combination of changes was assessed using SVM models in discovery and validation cohorts (area under the curve = 0.74 for both), confirming the robust nature of the immune signature detected. Conclusion: We identified differences within immune subpopulations of CAD+ patients which are indicative of a systemic immune response to coronary atherosclerosis. This immune signature needs further study via incorporation into risk scoring tools for the precision diagnosis of CAD. [ABSTRACT FROM AUTHOR]

Characterization of target abundance on cells has broad translational applications. Among the approaches for assessing membrane target expression is quantification of the number of target‐specific antibody (Ab) bound per cell (ABC). ABC determination on relevant cell subsets in complex and limited biological samples necessitates multidimensional immunophenotyping, for which the high‐order multiparameter capabilities of mass cytometry provide considerable advantages. In the present study, we describe the implementation of CyTOF® for the concomitant quantification of membrane markers on diverse types of immune cells in human whole blood. Specifically, our protocol relies on establishing Bmax of Ab saturable binding on cells, then converted into ABC according to a metal's transmission efficiency and number of metal atoms per Ab. Using this method, we calculated ABC values for CD4 and CD8 within the expected range for circulating T cells and in concordance with the ABC obtained in the same samples by flow cytometry. Furthermore, we successfully conducted multiplex measurements of the ABC for CD28, CD16, CD32a, and CD64, on >15 immune cell subsets in human whole blood samples. We developed a high‐dimensional data analysis workflow enabling semi‐automated Bmax calculation in all examined cell subsets to facilitate ABC reporting across populations. In addition, we investigated impacts of the type of metal isotope and acquisition batch effect on the ABC evaluation with CyTOF®. In summary, our findings demonstrate mass cytometry is a valuable tool for concurrent quantitative analysis of multiple targets in specific and rare cell types, thus increasing the numbers of biomeasures obtained from a single sample. [ABSTRACT FROM AUTHOR]

Acute erythroid leukemia (AEL) is a disease continuum between Myelodysplastic syndrome (MDS) and Acute myeloid leukemia (AML) with the cellular hallmark of uncontrolled proliferation and impaired differentiation of erythroid progenitor cells. First described by Giovanni di Guglielmo in 1917 AEL accounts for less than 5% of all de novo AML cases. There have been efforts to characterize AEL at a molecular level, describing recurrent alterations in TP53, NPM1 and FLT3 genes. A genomic analysis of AEL cases confirmed its complexity. Despite these advances, the biology underlying erythroid proliferations remains unclear and the prognosis is dismal with a median survival of only 3 months for pure erythroid leukemia (PEL). Marker combinations suitable for the identification and characterization of leukemic stem cell (LSC) candidates, monitoring measurable residual disease (MRD) during chemotherapy treatment and the development of innovative targeted therapies are missing. Here, we developed a mass cytometry panel for an in‐depth characterization of erythroid and myeloid blast cell populations from human AEL bone marrow samples in comparison to other AML subtypes and healthy counterparts. A total of 8 AEL samples were analyzed and compared to 28 AML samples from different molecular subtypes, healthy bone marrow counterparts (n = 5) and umbilical cord blood (n = 6) using high‐dimensional mass cytometry. Identification of erythroid and myeloid blast populations in high‐dimensional mass cytometry data enabled a refined view on erythroblast differentiation stages present in AEL erythroid blasts and revealed immunophenotypical profiles specific to AEL. Profiling of phenotypic LSCs revealed aberrant erythroid marker expression in the CD34+CD38− stem cell compartment. In addition, the identification of novel candidate surface marker combinations and aberrancies might enhance clinical diagnostics of AEL. We present a high‐parameter mass cytometry approach feasible for immunophenotypical analysis of blast and stem cell populations in myeloid neoplasms with erythroid predominance laying the foundation for more precise experimental approaches in the future. [ABSTRACT FROM AUTHOR]

Triple‐negative breast cancer (TNBC) is an aggressive and complex subtype of breast cancer that lacks targeted therapy. TNBC manifests characteristic, extensive intratumoral heterogeneity that promotes disease progression and influences drug response. Single‐cell techniques in combination with next‐generation computation provide an unprecedented opportunity to identify molecular events with therapeutic potential. Here, we describe the generation of a comprehensive mass cytometry panel for multiparametric detection of 23 phenotypic markers and 13 signaling molecules. This single‐cell proteomic approach allowed us to explore the landscape of TNBC heterogeneity, with particular emphasis on the tumor microenvironment. We prospectively profiled freshly resected tumors from 26 TNBC patients. These tumors contained phenotypically distinct subpopulations of cancer and stromal cells that were associated with the patient's clinical status at the time of surgery. We further classified the epithelial‐mesenchymal plasticity of tumor cells, and molecularly defined phenotypically diverse populations of tumor‐associated stroma. Furthermore, in a retrospective tissue‐microarray TNBC cohort, we showed that the level of CD97 at the time of surgery has prognostic potential. [ABSTRACT FROM AUTHOR]

A 41‐year‐old man with oral pemphigus vulgaris (PV) presented to our clinic with a history of no response to numerous immunosuppressant agents and was referred for extracorporeal photopheresis (ECP) therapy. Although the patient underwent a high‐intensity ECP regimen for 5 months, which included two different photopheresis systems, his oral dysesthesia continued to interfere with oral intake, leading to continued weight loss and other adverse events. The intervention was associated with changes in several immune cell subpopulations without modifying the anti‐epidermal antibody titers, aligned with his poor clinical outcome. To the best of the authors' knowledge, this is the first report to examine immunophenotyping of a PV patient who was refractory to previous immunosuppression and recalcitrant to high‐intensity ECP therapy. [ABSTRACT FROM AUTHOR]

Background: Sleep loss (SL) is a health issue associated with the higher risk of autoimmune and inflammatory disorders. However, the connection between SL, the immune system, and autoimmune diseases remains unknown. Methods: We conducted mass cytometry, single‐cell RNA sequencing, and flow cytometry to analyze how SL influences immune system and autoimmune disease development. Peripheral blood mononuclear cells from six healthy subjects before and after SL were collected and analyzed by mass cytometry experiments and subsequent bioinformatic analysis to identify the effects of SL on human immune system. Sleep deprivation and experimental autoimmune uveitis (EAU) mice model were constructed, and scRNA‐seq data from mice cervical draining lymph nodes were generated to explore how SL influences EAU development and related autoimmune responses. Results: We found compositional and functional changes in human and mouse immune cells after SL, especially in effector CD4+ T and myeloid cells. SL upregulated serum GM‐CSF levels in healthy individuals and in patients with SL‐induced recurrent uveitis. Experiments in mice undergoing SL or EAU demonstrated that SL could aggravate autoimmune disorders by inducing pathological immune cell activation, upregulating inflammatory pathways, and promoting intercellular communication. Furthermore, we found that SL promoted Th17 differentiation, pathogenicity, and myeloid cells activation through the IL‐23Th17GM‐CSF feedback mechanism, thus promoting EAU development. Lastly, an anti‐GM‐CSF treatment rescued SL‐induced EAU aggravation and pathological immune response. Conclusions: SL promoted Th17 cells pathogenicity and autoimmune uveitis development, especially through the interaction between Th17 and myeloid cells involving GM‐CSF signaling, providing possible therapeutic targets for the SL‐related pathological disorders. [ABSTRACT FROM AUTHOR]

Waldenström macroglobulinemia (WM) is a rare subtype of non‐Hodgkin lymphoma characterized by malignant lymphoplasmacytic cells in the bone marrow (BM). To dissect the pathophysiology of WM, we evaluated clonal cells by mapping of B cell lymphomagenesis with adaptive and innate immune tumor microenvironment (TME) in the BM of WM patients using mass cytometry (CyTOF). In‐depth immunophenotypic profiling of WM cells exhibited profound expansion of clonal cells in both unswitched and switched memory B cells and also plasma cells with aberrant expression variations. WM B lymphomagenesis was associated with reduction of most B cell precursors assessed with the same clonally restricted light chain and phenotypic changes. The immune TME was infiltrated by mature monocytes, neutrophils and adaptive T cells, preferentially subsets of effector T helper, effector CTL and effector memory CTL cells that were associated with superior overall survival (OS), in contrast to progenitors of T cells and myeloid/monocytic lineage subsets that were suppressed in WM cohort. Moreover, decrease in immature B and NKT cells was related to worse OS in WM patients. Innate and adaptive immune subsets of WM TME were modulated by immune checkpoints, including PD‐1/PD‐L1&PD‐L2, TIGIT/PVR, CD137/CD137‐L, CTLA‐4, BTLA and KIR expression. The response of ibrutinib treatment to the reduction of clonal memory B cell was associated with high levels of immature B cells and effector memory CTL cells. Our study demonstrates that CyTOF technology is a powerful approach for characterizing the pathophysiology of WM at various stages, predicting patient risk and monitoring the effectiveness of treatment strategies. [ABSTRACT FROM AUTHOR]

Technologies for single‐cell profiling of the immune system have enabled researchers to extract rich interconnected networks of cellular abundance, phenotypical and functional cellular parameters. These studies can power machine learning approaches to understand the role of the immune system in various diseases. However, the performance of these approaches and the generalizability of the findings have been hindered by limited cohort sizes in translational studies, partially due to logistical demands and costs associated with longitudinal data collection in sufficiently large patient cohorts. An evolving challenge is the requirement for ever‐increasing cohort sizes as the dimensionality of datasets grows. We propose a deep learning model derived from a novel pipeline of optimal temporal cell matching and overcomplete autoencoders that uses data from a small subset of patients to learn to forecast an entire patient's immune response in a high dimensional space from one timepoint to another. In our analysis of 1.08 million cells from patients pre‐ and post‐surgical intervention, we demonstrate that the generated patient‐specific data are qualitatively and quantitatively similar to real patient data by demonstrating fidelity, diversity, and usefulness. [ABSTRACT FROM AUTHOR]

We developed a highly reproducible 32‐marker mass cytometry panel able to measure all canonical immune lineages and perform detailed characterization of both CD4 and CD8 T cells in human peripheral blood mononuclear cells. In this panel, we identify six different T cell memory subsets, as well as markers of activation, cell cycling, and survival. In addition, this panel classifies all major CD4 T cell helper subsets. This panel enables detailed monitoring of CD4 and CD8 T cells in the context of infectious disease, cancer or autoimmunity with limited patient sample use. Detailed methods for standardization and optimization of the panel can be found in Supporting Information. [ABSTRACT FROM AUTHOR]

Sleep loss (SL) is a health problem that affects autoimmune and inflammatory diseases. However, the relationship between SL, the immune system and autoimmune diseases remains unclear. This commentary summarizes and discusses the key findings of the study by Liu et al. published in Clinical and Translational Medicine. In this study, they analysed the effects of SL on autoimmune uveitis using mass cytometry, single‐cell RNA sequencing, and flow cytometry. They identified changes in the composition and function of human and mouse immune cells following SL that primarily involved effector CD4+ T cells and myeloid cells. Furthermore, they demonstrated that SL promoted Th17 differentiation, pathogenicity, and Interleukin‐23 (IL‐23)–Th17– granulocyte macrophage colony stimulating factor (GM‐CSF) feedback mechanism in autoimmunity. Finally, they attenuated SL‐induced EAU exacerbation using anti‐GM‐CSF treatment, providing a novel therapeutic approach for SL‐related autoimmune diseases. [ABSTRACT FROM AUTHOR]

High‐dimensional single‐cell data has become an important tool in unraveling the complexity of the immune system and its involvement in homeostasis and a large array of pathologies. As technological tools are developed, researchers are adopting them to answer increasingly complex biological questions. Up until recently, mass cytometry (MC) has been the main technology employed in cytometric assays requiring more than 29 markers. Recently, however, with the introduction of full spectrum flow cytometry (FSFC), it has become possible to break the fluorescence barrier and go beyond 29 fluorescent parameters. In this study, in collaboration with the Stanford Human Immune Monitoring Center (HIMC), we compared five patient samples using an established immune panel developed by the HIMC using their MC platform. Using split samples and the same antibody panel, we were able to demonstrate highly comparable results between the two technologies using multiple data analysis approaches. We report here a direct comparison of two technology platforms (MC and FSFC) using a 32‐marker flow cytometric immune monitoring panel that can identify all the previously described and anticipated immune subpopulations defined by this panel. [ABSTRACT FROM AUTHOR]

Single‐cell multiplexing is key to exploration of the heterogeneous cell populations in biological systems. Although the state‐of‐the‐art mass cytometry (CyTOF) possesses high resolution and multiple dimensions, the lack of suitable marker materials prohibits fully exploiting the available CyTOF detection channels. Here we report a new design strategy for CyTOF markers using functionalized mesoporous porphyrinic frameworks (MPFs) as scaffolds for chelating metals that have been unachievable by conventional approaches. We developed surface modification for stably dispersing the MPF nanoparticles (<40 nm) during the metalation and antibody conjugation processes. Our markers exhibit higher sensitivity and comparable specificity compared with a polymer‐based commercial benchmark. Compatibility with commercial markers during co‐staining was also confirmed. Furthermore, our markers show promising performance for immunophenotyping and potential implementation in CyTOF systems. [ABSTRACT FROM AUTHOR]

Inflammatory bowel disease (IBD) is characterized by dysregulated intestinal immune responses. Using mass cytometry (CyTOF) to analyze the immune cell composition in the lamina propria (LP) of patients with ulcerative colitis (UC) and Crohn's disease (CD), we observed an enrichment of CD4+ effector T cells producing IL‐17A and TNF, CD8+ T cells producing IFNγ, T regulatory (Treg) cells, and innate lymphoid cells (ILC). The function of these immune cells is regulated by store‐operated Ca2+ entry (SOCE), which results from the opening of Ca2+ release‐activated Ca2+ (CRAC) channels formed by ORAI and STIM proteins. We observed that the pharmacologic inhibition of SOCE attenuated the production of proinflammatory cytokines including IL‐2, IL‐4, IL‐6, IL‐17A, TNF, and IFNγ by human colonic T cells and ILCs, reduced the production of IL‐6 by B cells and the production of IFNγ by myeloid cells, but had no effect on the viability, differentiation, and function of intestinal epithelial cells. T cell‐specific deletion of CRAC channel genes in mice showed that Orai1, Stim1, and Stim2‐deficient T cells have quantitatively distinct defects in SOCE, which correlate with gradually more pronounced impairment of cytokine production by Th1 and Th17 cells and the severity of IBD. Moreover, the pharmacologic inhibition of SOCE with a selective CRAC channel inhibitor attenuated IBD severity and colitogenic T cell function in mice. Our data indicate that SOCE inhibition may be a suitable new approach for the treatment of IBD. Synopsis: The immune cell composition, signaling cascades, and cytokine networks controlling inflammation in therapy‐refractory inflammatory bowel diseases (IBD) remain incompletely understood. The colon lamina propria (LP) of ulcerative colitis (UC) and Crohn's disease (CD) patients is enriched with CD4+ and CD8+ T cells, IL‐17‐producing innate immune cells (ILC) and Treg cells.Pharmacological inhibition of store‐operated Ca2+ Entry (SOCE) inhibits the production of proinflammatory cytokines and certain activation markers by human LP T cells, B cells, ILCs and myeloid cells.Inhibition of SOCE does not impair the differentiation and function of human or mouse intestinal epithelial cells in colonic organoid cultures.Pharmacologic inhibition of SOCE or T cell‐specific deletion of the SOCE genes Orai1 and Stim1 in T cells ameliorates intestinal inflammation in mouse models of colitis.SOCE is an important regulator of intestinal immune cell function and a potential drug target for the treatment of IBD. [ABSTRACT FROM AUTHOR]

B cells play a major role in multiple sclerosis (MS), with many successful therapeutics capable of removing them from circulation. One such therapy, alemtuzumab, is thought to reset the immune system without the need for ongoing therapy in a proportion of patients. The exact cells contributing to disease pathogenesis and quiescence remain to be identified. We utilized mass cytometry to analyze B cells from the blood of patients with relapse‐remitting MS (RRMS) before and after alemtuzumab treatment, and during relapse. A complementary RRMS cohort was analyzed by single‐cell RNA sequencing. The R package "Spectre" was used to analyze these data, incorporating FlowSOM clustering, sparse partial least squares‐discriminant analysis and permutational multivariate analysis of variance. Immunoglobulin (Ig)A+ and IgG1+ B‐cell numbers were altered, including higher IgG1+ B cells during relapse. B‐cell linker protein (BLNK), CD40 and CD210 expression by B cells was lower in patients with RRMS compared with non‐MS controls, with similar results at the transcriptomic level. Finally, alemtuzumab restored BLNK, CD40 and CD210 expression by IgA+ and IgG1+ B cells, which was altered again during relapse. These data suggest that impairment of IgA+ and IgG1+ B cells may contribute to MS pathogenesis, which can be restored by alemtuzumab. [ABSTRACT FROM AUTHOR]

Background: Changes in immune cell composition during the immunological window within the first years after birth are not fully understood, especially the effect that different lifestyles might have on immune cell functionality. Methods: Peripheral blood mononuclear cells from mothers and their children at birth and at two anvd five years were analyzed by mass cytometry. Immune cell composition and functionality was analyzed according to family lifestyle (anthroposophic and non‐anthroposophic). Results: We found no significant differences in the proportions of major immune lineages between anthroposophic and non‐anthroposophic children at each time point, but there were clear changes over time in the proportions of mononuclear leukocytes, especially in B‐cells and T lymphocytes. Phenotypic distances between cord blood and maternal blood were high at birth but decreased sharply the first two years, indicating strong phenotypic convergence with maternal cells. We found that children exhibited similar stimulation responses at birth, but subsequently segregated into two discrete functional trajectories. Trajectory 1 was associated with a decrease in tumor necrosis factor alpha (TNFa) production by CD4+ T‐ and NK‐cells, while Trajectory 2 depicted an increase in the production of IL‐2 and interferon gamma (INFg) by T‐cells. In both trajectories, there was an increase in IL‐17A production by T‐cells resulting in prominent differences at five years of age. Conclusions: This exploratory study suggests that leukocyte frequencies and cell phenotypes change with age in the same way across all children, while functional development follows one of two discrete trajectories that largely segregate by family lifestyle, supporting the hypothesis that early environmental exposures imprint immune cell function which may contribute to IgE sensitization. Our results also support that the first two years are critical for the environmental exposures to imprint the immune cells. Further studies with larger sample sizes are required to validate our findings. [ABSTRACT FROM AUTHOR]

In cytometry analysis, a large number of markers is measured for thousands or millions of cells, resulting in high‐dimensional datasets. During the measurement of these samples, erroneous events can occur such as clogs, speed changes, slow uptake of the sample etc., which can influence the downstream analysis and can even lead to false discoveries. As these issues can be difficult to detect manually, an automated approach is recommended. In order to filter these erroneous events out, we created a novel quality control algorithm, Peak Extraction And Cleaning Oriented Quality Control (PeacoQC), that allows for automated cleaning of cytometry data. The algorithm will determine density peaks per channel on which it will remove low quality events based on their position in the isolation tree and on their mean absolute deviation distance to these density peaks. To evaluate PeacoQC's cleaning capability, it was compared to three other existing quality control algorithms (flowAI, flowClean and flowCut) on a wide variety of datasets. In comparison to the other algorithms, PeacoQC was able to filter out all different types of anomalies in flow, mass and spectral cytometry data, while the other methods struggled with at least one type. In the quantitative comparison, PeacoQC obtained the highest median balanced accuracy and a similar running time compared to the other algorithms while having a better scalability for large files. To ensure that the parameters chosen in the PeacoQC algorithm are robust, the cleaning tool was run on 16 public datasets. After inspection, only one sample was found where the parameters should be further optimized. The other 15 datasets were analyzed correctly indicating a robust parameter choice. Overall, we present a fast and accurate quality control algorithm that outperforms existing tools and ensures high‐quality data that can be used for further downstream analysis. An R implementation is available. [ABSTRACT FROM AUTHOR]

As the size and complexity of high‐dimensional (HD) cytometry data continue to expand, comprehensive, scalable, and methodical computational analysis approaches are essential. Yet, contemporary clustering and dimensionality reduction tools alone are insufficient to analyze or reproduce analyses across large numbers of samples, batches, or experiments. Moreover, approaches that allow for the integration of data across batches or experiments are not well incorporated into computational toolkits to allow for streamlined workflows. Here we present Spectre, an R package that enables comprehensive end‐to‐end integration and analysis of HD cytometry data from different batches or experiments. Spectre streamlines the analytical stages of raw data pre‐processing, batch alignment, data integration, clustering, dimensionality reduction, visualization, and population labelling, as well as quantitative and statistical analysis. Critically, the fundamental data structures used within Spectre, along with the implementation of machine learning classifiers, allow for the scalable analysis of very large HD datasets, generated by flow cytometry, mass cytometry, or spectral cytometry. Using open and flexible data structures, Spectre can also be used to analyze data generated by single‐cell RNA sequencing or HD imaging technologies, such as Imaging Mass Cytometry. The simple, clear, and modular design of analysis workflows allow these tools to be used by bioinformaticians and laboratory scientists alike. Spectre is available as an R package or Docker container. R code is available on Github (https://github.com/immunedynamics/spectre). [ABSTRACT FROM AUTHOR]

Gluten‐specific CD4+ T cells being drivers of celiac disease (CeD) are obvious targets for immunotherapy. Little is known about how cell markers harnessed for T‐cell‐directed therapy can change with time and upon activation in CeD and other autoimmune conditions. In‐depth characterization of gluten‐specific CD4+ T cells and CeD‐associated (CD38+ and CD103+) CD8+ and γδ+ T cells in blood of treated CeD patients undergoing a 3 day gluten challenge is reported. The phenotypic profile of gluten‐specific cells changes profoundly with gluten exposure and the cells adopt the profile of gluten‐specific cells in untreated disease (CD147+, CD70+, programmed cell death protein 1 (PD‐1)+, inducible T‐cell costimulator (ICOS)+, CD28+, CD95+, CD38+, and CD161+), yet with some markers being unique for day 6 cells (C‐X‐C chemokine receptor type 6 (CXCR6), CD132, and CD147) and with integrin α4β7, C‐C motif chemokine receptor 9 (CCR9), and CXCR3 being expressed stably at baseline and day 6. Among gluten‐specific CD4+ T cells, 52% are CXCR5+ at baseline, perhaps indicative of germinal‐center reactions, while on day 6 all are CXCR5−. Strikingly, the phenotypic profile of gluten‐specific CD4+ T cells on day 6 largely overlaps with that of CeD‐associated (CD38+ and CD103+) CD8+ and γδ+ T cells. The antigen‐induced shift in phenotype of CD4+ T cells being shared with other disease‐associated T cells is relevant for development of T‐cell‐directed therapies. [ABSTRACT FROM AUTHOR]

Tacrolimus (FK506) and rapamycin (RAPA) are widely used to maintain long‐term immunosuppression after organ transplantation. However, the impact of accumulative drug administration on the recipients' immune systems remains unclear. We investigated the impact of 3‐year FK506 or RAPA treatment after renal transplantation on the human immune systems. A discovery cohort of 30 patients was first recruited, and we discovered two distinctive T lineage suppressive regulatory patterns induced by chronic treatment of FK506 and RAPA. The increased percentage of senescent CD8+CD57+ T lineages and less responsive T cell receptor (TCR) pathway in the FK506 group indicate better graft acceptance. Meanwhile, percentages of regulatory T cells (Tregs) and expression of CTLA‐4 were both up to two‐fold higher in the RAPA group, suggesting the inconsistent reactivation potential of the FK506 and RAPA groups when an anti‐tumour or anti‐infection immune response is concerned. Additionally, up‐regulation of phosphorylated signaling proteins in T lineages after in vitro CD3/CD28 stimulation suggested more sensitive TCR‐signaling pathways reserved in the RAPA group. An independent validation cohort of 100 renal transplantation patients was further investigated for the hypothesis that long‐term RAPA administration mitigates the development of tumours and infections during long‐term intake of immunosuppressants. Our results indicate that RAPA administration indeed results in less clinical oncogenesis and infection. The deep phenotyping of T‐cell lineages, as educated by the long‐term treatment of different immunosuppressants, provides new evidence for personalized precision medicine after renal transplantations. [ABSTRACT FROM AUTHOR]

Background: Patients with relapsed/refractory (R/R) acute myeloid leukemia (AML) have limited treatment options. In preclinical models of AML, inhibition of the PD‐1/PD‐L1 axis demonstrated antileukemic activity. Avelumab is an anti–PD‐L1 immune checkpoint inhibitor (ICI) approved in multiple solid tumors. The authors conducted a phase 1b/2 clinical trial to assess the safety and efficacy of azacitidine with avelumab in patients with R/R AML. Methods: Patients aged ≥18 years who had R/R AML received azacitidine 75 mg/m2 on days 1 through 7 and avelumab on days 1 and 14 of 28‐day cycles. Results: Nineteen patients were treated. The median age was 66 years (range, 22‐83 years), 100% had European LeukemiaNet 2017 adverse‐risk disease, and 63% had prior exposure to a hypomethylating agent. Avelumab was dosed at 3 mg/kg for the first 7 patients and at 10 mg/kg for the subsequent 12 patients. The most common grade ≥3 treatment‐related adverse events were neutropenia and anemia in 2 patients each. Two patients experienced immune‐related adverse events of grade 2 and grade 3 pneumonitis, respectively. The overall complete remission rate was 10.5%, and both were complete remission with residual thrombocytopenia. The median overall survival was 4.8 months. Bone marrow blasts were analyzed for immune‐related markers by mass cytometry and demonstrated significantly higher expression of PD‐L2 compared with PD‐L1 both pretherapy and at all time points during therapy, with increasing PD‐L2 expression on therapy. Conclusions: Although the combination of azacitidine and avelumab was well tolerated, clinical activity was limited. High expression of PD‐L2 on bone marrow blasts may be an important mechanism of resistance to anti–PD‐L1 therapy in AML. Lay Summary: This report describes the results of a phase 1b/2 study of azacitidine with the anti–PD‐L1 immune checkpoint inhibitor avelumab for patients with relapsed/refractory acute myeloid leukemia (AML).The clinical activity of the combination therapy was modest, with an overall response rate of 10.5%.However, mass cytometry analysis revealed significantly higher expression of PD‐L2 compared with PD‐L1 on AML blasts from all patients who were analyzed at all time points.These data suggest a novel potential role for PD‐L2 as a means of AML immune escape. Azacitidine combined with the anti–PD‐L1 immune checkpoint inhibitor avelumab does not produce significant clinical efficacy for patients with relapsed/refractory acute myeloid leukemia (AML). However, an analysis of AML blasts reveals PD‐L2 surface expression as a novel mechanism of immune escape. [ABSTRACT FROM AUTHOR]

Background: Ovarian cancer (OC) is typically diagnosed late, associated with high rates of metastasis and the onset of ascites during late stage disease. Understanding the tumor microenvironment and how it impacts the efficacy of current treatments, including immunotherapies, needs effective in vivo models that are fully characterized. In particular, understanding the role of immune cells within the tumor and ascitic fluid could provide important insights into why OC fails to respond to immunotherapies. In this work, we comprehensively described the immune cell infiltrates in tumor nodules and the ascitic fluid within an optimized preclinical model of advanced ovarian cancer. Methods: Green Fluorescent Protein (GFP)‐ID8 OC cells were injected intraperitoneally into C57BL/6 mice and the development of advanced stage OC monitored. Nine weeks after tumor injection, mice were sacrificed and tumor nodules analyzed to identify specific immune infiltrates by immunohistochemistry. Ascites, developed in tumor bearing mice over a 10‐week period, was characterized by mass cytometry (CyTOF) to qualitatively and quantitatively assess the distribution of the immune cell subsets, and their relationship to ascites from ovarian cancer patients. Results: Tumor nodules in the peritoneal cavity proved to be enriched in T cells, antigen presenting cells and macrophages, demonstrating an active immune environment and cell‐mediated immunity. Assessment of the immune landscape in the ascites showed the predominance of CD8+, CD4+, B–, and memory T cells, among others, and the coexistance of different immune cell types within the same tumor microenvironment. Conclusions: We performed, for the first time, a multiparametric analysis of the ascitic fluid and specifically identify immune cell populations in the peritoneal cavity of mice with advanced OC. Data obtained highlights the impact of CytOF as a diagnostic tool for this malignancy, with the opportunity to concomitantly identify novel targets, and define personalized therapeutic options. [ABSTRACT FROM AUTHOR]

Background: Flow cytometry is a well‐accepted approach for immune profiling; however, its value is restricted by the limited number of markers that can be analyzed simultaneously. Mass cytometry/CyTOF offers broad‐scale immune characterization integrating large number of parameters. While partial blood phenotyping was reported in atopic dermatitis (AD), patients' comprehensive profiling, critical for leveraging new targeted treatments, is not available. IL‐21 may be involved in inflammatory skin diseases but its role in AD is not well established. Methods: We studied T‐cell polarization in the blood of 20 moderate‐to‐severe AD and 15 controls. Using CyTOF and an unsupervised analysis, we measured the frequencies and mean metal intensities of activated polar CD4+/CD8+ T‐cell subsets. Immunohistochemistry, immunofluorescence, and qRT‐PCR were used to analyze skin samples. Results: Examining 24 surface, intracellular markers, and transcription factors, we identified six CD4+ and five CD8+ T‐cell metaclusters. A CD4+ skin‐homing IL‐13+monocytokine and a novel IL‐13+IL‐21+ multicytokine metaclusters were increased in AD vs. controls (p <.01). While IL‐13 signature characterized both clusters, levels were significantly higher in the IL‐21+ group. Both clusters correlated with AD severity (r = 0.49, p =.029). Manual gating corroborated these results and identified additional multicytokine subsets in AD. Immunohistochemistry and immunofluorescence, validated by mRNA expression, displayed significantly increasedIL‐21 counts and colocalization with IL‐13/IL‐4R in AD skin. Conclusion: A multicytokine signature characterizes moderate‐to‐severe AD, possibly explaining partial therapeutic responses to one cytokine targeting, particularly in severe patients. Prominent IL‐21 signature in blood and skin hints for a potential pathogenic role of IL‐21 in AD. [ABSTRACT FROM AUTHOR]

Recent technological developments allow us to measure the status of dozens of proteins in individual cells. This opens the way to understand the heterogeneity of complex multi‐signaling networks across cells and cell types, with important implications to understand and treat diseases such as cancer. These technologies are, however, limited to proteins for which antibodies are available and are fairly costly, making predictions of new markers and of existing markers under new conditions a valuable alternative. To assess our capacity to make such predictions and boost further methodological development, we organized the Single Cell Signaling in Breast Cancer DREAM challenge. We used a mass cytometry dataset, covering 36 markers in over 4,000 conditions totaling 80 million single cells across 67 breast cancer cell lines. Through four increasingly difficult subchallenges, the participants predicted missing markers, new conditions, and the time‐course response of single cells to stimuli in the presence and absence of kinase inhibitors. The challenge results show that despite the stochastic nature of signal transduction in single cells, the signaling events are tightly controlled and machine learning methods can accurately predict new experimental data. SYNOPSIS: This study presents the results and conclusions of the 'Single Cell Signaling in Breast Cancer DREAM challenge', where teams were challenged to use state‐of‐the‐art methods for predicting single‐cell signaling from single‐cell and bulk proteomics, transcriptomics and genomics data. Over 80 million single‐cell multiplexed measurements across 67 cell lines, 54 conditions and 10 time points are used to benchmark predictive models of single‐cell signaling.73 approaches are used by 27 teams for predicting responses to kinase inhibitors on single cell level, and dynamic responses from unperturbed basal omics data.Top models of whole signaling response models perform almost as well as a biological replicate.Cell‐line specific variation in dynamics can be partially predicted from basal omics. [ABSTRACT FROM AUTHOR]

The identification and discrimination of viable cells is important to understand how experimental variables may influence biochemical processes such as cell metabolism, cell cycle, and signaling pathways. Cisplatin is commonly used as a viability stain in mass cytometry studies, however, recent work by Mei et al. has demonstrated that cisplatin can also be used to label antibodies, complicating the simultaneous use of the platinum measurement channels for both antibody and viability staining. This study demonstrates that other metal salts (hafnium chloride, niobium chloride, and zirconium chloride) can serve as substitutes for cisplatin in viability staining. These stains yield similar fractions of live and dead cells and stain the same dead cells in parallel high parameter analyses. In addition, this study demonstrates how a variety of protein antigen viability markers (pRb, Ki‐67, Histone H1, cleaved PARP, and GAPDH) can be used to discriminate live and dead cell populations, without the need for a separate viability staining step. As few as two of these protein antigen viability markers can help identify live and dead cell populations in fixed samples and can identify the same viable cells in high dimensional analyses with or without use of viability stain information. This study demonstrates several alternative approaches to mass cytometry viability assessment that can facilitate use of platinum isotopes for antibody staining and enables identification of live and dead cell populations in samples for which a separate viability stain is not practical. [ABSTRACT FROM AUTHOR]

Mass‐tag cell barcoding has increased the throughput, multiplexing, and robustness of multiple cytometry approaches. Previously, we adapted mass cytometry for cells to analyze synaptosome preparations (mass synaptometry or SynTOF), extending mass cytometry to these smaller, anuclear particles. To improve throughput and individual event resolution, we report here the application of palladium‐based barcoding in human synaptosomes. Up to 20 individual samples, each with a unique combinatorial barcode, were pooled for labeling with an antibody cocktail. Our synaptosome protocol used six palladium‐based barcoding reagents, and in combination with sequential gating increased the identification of presynaptic events approximately fourfold. These same parameters also efficiently resolved two other anuclear particles: human red blood cells and platelets. The addition of palladium‐based mass‐tag barcoding to our approach improves mass cytometry of synaptic particles. [ABSTRACT FROM AUTHOR]

Signal intensity measured in a mass cytometry (CyTOF) channel can often be affected by the neighboring channels due to technological limitations. Such signal artifacts are known as spillover effects and can substantially limit the accuracy of cell population clustering. Current approaches reduce these effects by using additional beads for normalization purposes known as single‐stained controls. While effective in compensating for spillover effects, incorporating single‐stained controls can be costly and require customized panel design. This is especially evident when executing large‐scale immune profiling studies. We present a novel statistical method, named CytoSpill that independently quantifies and compensates the spillover effects in CyTOF data without requiring the use of single‐stained controls. Our method utilizes knowledge‐guided modeling and statistical techniques, such as finite mixture modeling and sequential quadratic programming, to achieve optimal error correction. We evaluated our method using five publicly available CyTOF datasets obtained from human peripheral blood mononuclear cells (PBMCs), C57BL/6J mouse bone marrow, healthy human bone marrow, chronic lymphocytic leukemia patient, and healthy human cord blood samples. In the PBMCs with known ground truth, our method achieved comparable results to experiments that incorporated single‐stained controls. In datasets without ground‐truth, our method not only reduced spillover on likely affected markers, but also led to the discovery of potentially novel subpopulations expressing functionally meaningful, cluster‐specific markers. CytoSpill (developed in R) will greatly enhance the execution of large‐scale cellular profiling of tumor immune microenvironment, development of novel immunotherapy, and the discovery of immune‐specific biomarkers. The implementation of our method can be found at https://github.com/KChen-lab/CytoSpill.git. [ABSTRACT FROM AUTHOR]

We constructed an original platform to determine whether identification of CAR-T cells and immune cells lacking CAR (non-CAR) and their functional states in peripheral blood would be possible in a single-pass mass cytometry assay. (A) t-Distributed stochastic neighbour embedding (t-SNE) overview of identity and activity of chimaeric antigen receptor (CAR) and non-CAR immune cells over time after CAR-T-cell administration, analyzed with the OMIQ software in order to obtain the t-SNE maps. These data also allowed to convert CAR-T cells detected by mass or flow cytometry into the absolute value of viable CD3+ cells, as measured by single-platform flow cytometry (right panel). Keywords: chimaeric antigen receptor-T cells; immunomonitoring; mass cytometry EN chimaeric antigen receptor-T cells immunomonitoring mass cytometry 788 792 5 08/18/21 20210815 NES 210815 By reprograming T-cell specificity, chimaeric antigen receptors' (CARs) function and persistence have changed the landscape of cancer immunotherapy with remarkable efficacy against a range of B-cell malignancies and have many prospective applications.1,2 Investigating the immune mechanisms that underlie the success of CAR-T-cell therapy is a crucial challenge.3,4,5 The advent of time-of-flight mass cytometry (CyTOF) has enabled high-dimensional and unbiased examination of complex systems.6,7 We present here the first contribution of mass cytometry to the comprehensive immunomonitoring of CAR-T-cell therapies. [Extracted from the article]

High‐dimensional cytometry represents an exciting new era of immunology research, enabling the discovery of new cells and prediction of patient responses to therapy. A plethora of analysis and visualization tools and programs are now available for both new and experienced users; however, the transition from low‐ to high‐dimensional cytometry requires a change in the way users think about experimental design and data analysis. Data from high‐dimensional cytometry experiments are often underutilized, because of both the size of the data and the number of possible combinations of markers, as well as to a lack of understanding of the processes required to generate meaningful data. In this article, we explain the concepts behind designing high‐dimensional cytometry experiments and provide considerations for new and experienced users to design and carry out high‐dimensional experiments to maximize quality data collection. [ABSTRACT FROM AUTHOR]

Objective: The loss of LOXL1 expression reportedly leads to the prolapse of pelvic organs or to exfoliation syndrome glaucoma. Increasing evidence suggests that LOXL1 deficiency is associated with the pathogenesis of several other diseases. However, the characterization of the systemic functions of LOXL1 is limited by the lack of relevant investigative technologies. Materials and Methods: To determine the functions of LOXL1, a novel method for body‐wide organ transcriptome profiling, combined with single‐cell mass cytometry, was developed. A body‐wide organ transcriptomic (BOT) map was created by RNA‐Seq of tissues from 17 organs from both Loxl1 knockout (KO) and wild‐type mice. Results: The BOT results indicated the systemic upregulation of genes encoding proteins associated with the immune response and proliferation processes in multiple tissues of KO mice, and histological and immune staining confirmed the hyperplasia and infiltration of local immune cells in the tissues of KO mice. Furthermore, mass cytometry analysis of peripheral blood samples revealed systemic immune changes in KO mice. These findings were well correlated with results obtained from cancer databases. Patients with tumours had higher Loxl1 mutation frequencies, and patients with Loxl1‐mutant tumours showed the upregulation of immune processes and cell proliferation and lower survival rates. Conclusion: This study provides an effective strategy for the screening of gene functions in multiple organs and also illustrates the important biological roles of LOXL1 in the cells of multiple organs as well as in systemic immunity. [ABSTRACT FROM AUTHOR]

Mass cytometry (CyTOF) represents one of the most powerful tools in immune phenotyping, allowing high throughput quantification of over 40 parameters at single‐cell resolution. However, wide deployment of CyTOF‐based immune phenotyping studies are limited by complex experimental workflows and the need for specialized CyTOF equipment and technical expertise. Furthermore, differences in cell isolation and enrichment protocols, antibody reagent preparation, sample staining, and data acquisition protocols can all introduce technical variation that can confound integrative analyses of large data‐sets of samples processed across multiple labs. Here, we present a streamlined whole blood CyTOF workflow which addresses many of these sources of experimental variation and facilitates wider adoption of CyTOF immune monitoring across sites with limited technical expertise or sample‐processing resources or equipment. Our workflow utilizes commercially available reagents including the Fluidigm MaxPar Direct Immune Profiling Assay (MDIPA), a dry tube 30‐marker immunophenotyping panel, and SmartTube Proteomic Stabilizer, which allows for simple and reliable fixation and cryopreservation of whole blood samples. We validate a workflow that allows for streamlined staining of whole blood samples with minimal processing requirements or expertise at the site of sample collection, followed by shipment to a central CyTOF core facility for batched downstream processing and data acquisition. We apply this workflow to characterize 184 whole blood samples collected longitudinally from a cohort of 72 hospitalized COVID‐19 patients and healthy controls, highlighting dynamic disease‐associated changes in circulating immune cell frequency and phenotype. [ABSTRACT FROM AUTHOR]

Whole blood is often collected for large‐scale immune monitoring studies to track changes in cell frequencies and responses using flow (FC) or mass cytometry (MC). In order to preserve sample composition and phenotype, blood samples should be analyzed within 24 h after bleeding, restricting the recruitment, analysis protocols, as well as biobanking. Herein, we have evaluated two whole blood preservation protocols that allow rapid sample processing and long‐term stability. Two fixation buffers were used, Phosphoflow Fix and Lyse (BD) and Proteomic Stabilizer (PROT) to fix and freeze whole blood samples for up to 6 months. After analysis by an 8‐plex panel by FC and a 26‐plex panel by MC, manual gating of circulating leukocyte populations and cytokines was performed. Additionally, we tested the stability of a single sample over a 13‐months period using 45 consecutive aliquots and a 34‐plex panel by MC. We observed high correlation and low bias toward any cell population when comparing fresh and 6 months frozen blood with FC and MC. This correlation was confirmed by hierarchical clustering. Low coefficients of variation (CV) across studied time points indicate good sample preservation for up to 6 months. Cytokine detection stability was confirmed by low CVs, with some differences between fresh and fixed conditions. Thirteen months regular follow‐up of PROT samples showed remarkable sample stability. Whole blood can be preserved for phenotyping and cytokine‐response studies provided the careful selection of a compatible antibody panel. However, possible changes in cell morphology, differences in antibody affinity, and changes in cytokine‐positive cell frequencies when compared to fresh blood should be considered. Our setting constitutes a valuable tool for multicentric and retrospective studies. © 2020 International Society for Advancement of Cytometry [ABSTRACT FROM AUTHOR]

Problem: Prenatal exposure to metabolic dysregulation arising from maternal obesity can have negative health consequences in post‐natal life. To date, the specific effects of maternal obesity on fetal immunity at a cellular level have not been well characterized. Method of Study: Using cord blood mononuclear cells (CBMCs) and cord plasma (n = 9/group) isolated from infants born to women with a high body mass index (BMI>25kg/m2) compared to women with a normal BMI (18‐25kg/m2), we evaluated differences in immune cell populations using single‐cell mass cytometry (CyTOF). CBMCs were matched according to potentially confounding variables, such as maternal and gestational age, ethnicity, smoking status, and gravidity. Statistical results were adjusted for fetal sex. Data were analyzed by viSNE and FlowSOM softwares in Cytobank™. Results: In newborn CBMCs from women with high BMI, we observed changes in frequency and phenotype of immune cell populations, including significant increases in CD4+ T cells and decreases in myeloid cell populations. IL‐12p40 and MDC concentrations were significantly elevated in the high BMI group compared to control. Conclusion: This study demonstrates an association between maternal obesity and fetal immunity. Our results warrant following long‐term immunologic outcomes and associated clinical risks in children born to women with a high pre‐pregnancy BMI. [ABSTRACT FROM AUTHOR]

Psoriasis is a chronic immune‐mediated skin disease accompanied by systemic inflammation and comorbidities. We analyzed peripheral blood mononuclear cells (PBMCs) in the search for immune signatures and biomarkers related to psoriasis severity and treatment effect. Thirty‐two patients with psoriasis and 10 matched healthy controls were included. PBMCs were collected before and after initiation of anti‐TNF, anti‐IL‐17 or anti‐IL‐12/23 treatment and analyzed utilizing 26‐parameter mass cytometry. The number of circulating Th17, Th22, Th9, and cytotoxic T cells were increased in severe psoriasis. Intracellular pp38 and pERK in T helper cells were associated with disease severity. Differences between responders and nonresponders regarding cell composition and intracellular signaling were identifiable already at inclusion. Biological treatment induced memory cells, restored inhibitory PD‐1 function of T cells, and reduced a potential pro‐atherogenic profile in monocytes. In conclusion, these results indicate amelioration of systemic inflammation in psoriasis after biological treatment. Such broad immune profiling may enable prospective stratification of patients regarding future treatment response. Successful early intervention may lead to a healthier trajectory with favorable implications on later comorbidities. [ABSTRACT FROM AUTHOR]

CD56+ T cells are a group of pro‐inflammatory CD3+ lymphocytes with characteristics of natural killer cells, being involved in antimicrobial immune defense. Here, we performed deep phenotypic profiling of CD3+CD56+ cells in peripheral blood of normal human donors and individuals sensitized to birch‐pollen or/and house dust mite by high‐dimensional mass cytometry combined with manual and computational data analysis. A co‐regulation between major conventional T‐cell subsets and their respective CD3+CD56+ cell counterparts appeared restricted to CD8+, MAIT, and TCRγδ+ T‐cell compartments. Interestingly, we find a co‐regulation of several CD3+CD56+ cell subsets in allergic but not in healthy individuals. Moreover, using FlowSOM, we distinguished a variety of CD56+ T‐cell phenotypes demonstrating a hitherto underestimated heterogeneity among these cells. The novel CD3+CD56+ subset description comprises phenotypes superimposed with naive, memory, type 1, 2, and 17 differentiation stages, in part represented by a phenotypical continuum. Frequencies of two out of 19 CD3+CD56+ FlowSOM clusters were significantly diminished in allergic individuals, demonstrating less frequent presence of cells with cytolytic, presumably protective, capacity in these donors consistent with defective expansion or their recruitment to the affected tissue. Our results contribute to defining specific cell populations to be targeted during therapy for allergic conditions. [ABSTRACT FROM AUTHOR]

Mass cytometry is attracting significant attention for enabling spatiotemporal high‐throughput single‐cell analysis. As the first demonstration of the simultaneous detection of single‐cell proteins and untargeted metabolites, a multi‐dimensional organic mass‐cytometry system was established by a simple microfluidic chip connected to a nanoelectrospray mass spectrometer, providing useful heterogeneous information about the cells. A series of mass probes with online‐dissociated mass tags were developed, ensuring the semi‐quantification of cell‐surface proteins and the compatibility of endogenous metabolite detection at the single‐cell level. Six cell surface antigens and ≈100 metabolites from three ovarian‐cancer cell types and two breast‐cancer cell types were successfully monitored and contributed to highly sensitive and specific cell typing. Doxorubicin‐resistant cancer‐cell analysis confirmed the applications in distinguishing rare cell phenotypes. The proposed system is simple, extensible, and promising for cell typing, drug‐resistance analysis of tumor cells, and clinical diagnosis and therapy at the single‐cell level. [ABSTRACT FROM AUTHOR]

In the last decade, there has been a tremendous development of technologies focused on analysing various molecular attributes in single cells, with an ever‐increasing number of parameters becoming available at the DNA, RNA and protein levels. Much of this progress has involved cells in suspension, but also in situ analysis of tissues has taken great leaps. Paralleling the development in the laboratory, and because of increasing complexity, the analysis of single‐cell data is also constantly being updated with new algorithms and analysis platforms. Our immune system shares this complexity, and immunologists have therefore been in the forefront of this technological development. These technologies clearly open new avenues for immunology research, maybe particularly within autoimmunity where the interaction between the faulty immune system and the thymus or the target organ is important. However, the technologies currently available can seem overwhelming and daunting. The aim of this review is to remedy this by giving a balanced overview of the prospects of using single‐cell analysis in basal and clinical autoimmunity research, with an emphasis on endocrine autoimmunity. [ABSTRACT FROM AUTHOR]

Microglia, the resident innate immune cells of the central nervous system (CNS), play an important role in brain development and homoeostasis, as well as in neuroinflammatory, neurodegenerative and psychiatric diseases. Studies in animal models have been used to determine the origin and development of microglia, and how these cells alter their transcriptional and phenotypic signatures during CNS pathology. However, little is known about their human counterparts. Recent studies in human brain samples have harnessed the power of multiplexed single‐cell technologies such as single‐cell RNA sequencing (scRNA‐seq) and mass cytometry (cytometry by time‐of‐flight [CyTOF]) to provide a comprehensive molecular view of human microglia in healthy and diseased brains. CyTOF is a powerful tool to study high‐dimensional protein expression of human microglia (huMG) at the single‐cell level. This technology widens the possibilities of high‐throughput quantification (of over 60 targeted molecules) at a single‐cell resolution. CyTOF can be combined with scRNA‐seq for comprehensive analysis, as it allows single‐cell analysis of post‐translational modifications of proteins, which provides insights into cell signalling dynamics in targeted cells. In addition, imaging mass cytometry (IMC) has recently become commercially available, and will be useful for analysing multiple cell types in human brain sections. IMC leverages mass spectrometry to acquire spatial data of cell–cell interactions on tissue sections, using (theoretically) over 40 markers at the same time. In this review, we summarise recent studies of huMG using CyTOF and IMC analyses. The uses and limitations as well as future directions of these technologies are discussed. [ABSTRACT FROM AUTHOR]

Recently emerged mass cytometry (cytometry by time-of-flight [CyTOF]) technology permits the identification and quantification of inherently diverse cellular systems, and the simultaneous measurement of functional attributes at the single-cell resolution. By virtue of its multiplex ability with limited need for compensation, CyTOF has led a critical role in immunological research fields. Here, we present an overview of CyTOF, including the introduction of CyTOF principle and advantages that make it a standalone tool in deciphering immunemysteries. We then discuss the functional assays, introduce the bioinformatics to interpret the data yield via CyTOF, and depict the emerging clinical and research applications of CyTOF technology in sketching immune landscape in a wide variety of diseases. [ABSTRACT FROM AUTHOR]

Macrophages, which are highly diverse in different tissues, play a complex and vital role in tissue development, homeostasis, and inflammation. The origin and heterogeneity of tissue‐resident monocytes and macrophages in ovaries remains unknown. Here we identify three tissue‐resident monocyte populations and five macrophage populations in the adult ovaries using high‐dimensional single cell mass cytometry. Ontogenic analyses using cell fate mapping models and cell depletion experiments revealed the infiltration of ovaries by both yolk sac and fetal liver‐derived macrophages already during the embryonic development. Moreover, we found that both embryonic and bone marrow‐derived macrophages contribute to the distinct ovarian macrophage subpopulations in the adults. These assays also showed that fetal‐derived MHC II‐negative macrophages differentiate postnatally in the maturing ovary to MHC II‐positive cells. Our analyses further unraveled that the developmentally distinct macrophage types share overlapping distribution and scavenging function in the ovaries under homeostatic conditions. In conclusion, we report here the first comprehensive analyses of ovarian monocytes and macrophages. In addition, we show that the mechanisms controlling monocyte immigration, the phenotype of different pools of interstitial macrophages, and the interconversion capacity of fetal‐derived macrophages in ovaries are remarkably different from those seen in other tissue niches. [ABSTRACT FROM AUTHOR]

The application of machine learning and artificial intelligence to high‐dimensional cytometry data sets has increasingly become a staple of bioinformatic data analysis over the past decade. This is especially true in the field of cancer biology, where protocols for collecting multiparameter single‐cell data in a high‐throughput fashion are rapidly developed. As the use of machine learning methodology in cytometry becomes increasingly common, there is a need for cancer biologists to understand the basic theory and applications of a variety of algorithmic tools for analyzing and interpreting cytometry data. We introduce the reader to several keystone machine learning‐based analytic approaches with an emphasis on defining key terms and introducing a conceptual framework for making translational or clinically relevant discoveries. The target audience consists of cancer cell biologists and physician‐scientists interested in applying these tools to their own data, but who may have limited training in bioinformatics. © 2020 International Society for Advancement of Cytometry [ABSTRACT FROM AUTHOR]

The arrival of mass cytometry (MC) and, more recently, spectral flow cytometry (SFC) has revolutionized the study of cellular, functional and phenotypic diversity, significantly increasing the number of characteristics measurable at the single‐cell level. As a consequence, new computational techniques such as dimensionality reduction and/or clustering algorithms are necessary to analyze, clean, visualize, and interpret these high‐dimensional data sets. In this small comparison study, we investigated splenocytes from the same sample by either MC or SFC and compared both high‐dimensional data sets using expert gating, t‐distributed stochastic neighbor embedding (t‐SNE), uniform manifold approximation and projection (UMAP) analysis and FlowSOM. When we downsampled each data set to their equivalent cell numbers and parameters, our analysis yielded highly comparable results. Differences between the data sets only became apparent when the maximum number of parameters in each data set were assessed, due to differences in the number of recorded events or the maximum number of assessed parameters. Overall, our small comparison study suggests that mass cytometry and spectral flow cytometry both yield comparable results when analyzed manually or by high‐dimensional clustering or dimensionality reduction algorithms such as t‐SNE, UMAP, or FlowSOM. However, large scale studies combined with an in‐depth technical analysis will be needed to assess differences between these technologies in more detail. © 2020 International Society for Advancement of Cytometry [ABSTRACT FROM AUTHOR]

Cell cycle analysis by mass cytometry (MC) is hampered by the poor resolution of the Iridium‐labeled DNA intercalator compared to DNA‐specific fluorescent dyes. We report here a minimum cell cycle panel for MC consisting of Ir‐intercalator (DNA content), IdU (S phase), anti‐pS28HistoneH3 (mitosis), anti‐CDT1 (G1 phase) and anti‐Geminin (non‐G1 phases). Cell cycle distributions obtained by MC were not significantly different from fluorescence flow cytometry results (r2 = 0.98, P < 0.001). Further subdivision of the G1 and G2 phases could be done with anti‐pS780RB1 (late G1) and anti‐PLK1 (late G2), respectively. A disadvantage of MC is that aggregates of cells cannot easily be removed while retaining all single cells. We have developed an analysis pipeline including unsupervised clustering by FlowSOM and subsequent single‐cell gating. When performed on cells stained with the cell cycle panel, this analysis pipeline successfully identified debris, dead/apoptotic cells, nonsingle‐cell populations and the major cell cycle phases. The presented cell cycle panel and analysis pipeline thus achieves true single‐cell analysis at the same time as any additional channels in the panel are open for phenotyping and cell cycle‐resolved expression or modification analysis. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals LLC. on behalf of International Society for Advancement of Cytometry. [ABSTRACT FROM AUTHOR]

The spatial heterogeneity of immune microenvironment in hepatocellular carcinoma (HCC) remains elusive. Here, a single‐cell study involving 17 432 600 immune cells of 39 matched HCC (T), nontumor (N), and leading‐edge (L) specimens by mass cytometry is conducted. The tumor‐associated CD4/CD8 double‐positive T (DPT) cells are found enriched in L regions with synergetic expression of PD‐1/HLA‐DR/ICOS/CD45RO and exhibit a higher level of IFN‐γ, TNF‐α, and PD‐1 upon stimulation. The enrichment of DPT and PD‐1+DPT in L regions indicates favorable prognosis. These tumor‐associated DPT cells with similar phenotype are also verified in other tumors and HCC animal models. Single‐cell RNA‐seq further characterizes the molecular features of DPT cells and uncovers 11 clusters with different cytotoxicity, exhaustion, and activation scores. TCR‐based trajectory analysis reveals that tumor‐associated DPT clusters share separated ancestries with local CD4+ or CD8+SPT cells rather than CD3+PBMC cells. TCR clones with frequency above 10 are mainly found coexisting in DPT and CD8+SPT cells. Specifically, PD‐1highDPT cluster (TDPT_10) shares the same ancestry with exhausted CD8+SPT cluster (TCD8T_2) and shows higher expression similarity and closer pathological location to PD‐1+CD8+ than PD‐1+CD4+T cells. Together, this study systematically characterizes the unique distribution of PD‐1+DPTs in HCC and puts forward new insights for the function and origin of tumor‐associated DPT cells. [ABSTRACT FROM AUTHOR]