Analyzing high-dimensional cytometry data using FlowSOM

Immune cell profiles associated with human exposure to perfluorinated compounds (PFAS) suggest changes in natural killer, T helper, and T cytotoxic cell subpopulations

Per- and polyfluoroalkyl substances (PFAS) constitutes a group of highly persistent man-made substances. Recent evidence indicates that PFAS negatively impact the immune system. However, it remains unclear how different PFAS are associated with alterations in circulating leukocyte subpopulations. More detailed knowledge of such potential associations can provide better understanding into mechanisms of PFAS immunotoxicity in humans. In this exploratory study, associations of serum levels of common PFAS (perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluorononanoic acid (PFNA), and perfluorohexane sulfonic acid (PFHxS)) and immune cell profiles of peripheral blood mononuclear cells, both with and without immunostimulation, were investigated. High-dimensional single cell analysis by mass cytometry was done on blood leukocytes from fifty participants in the Norwegian human biomonitoring EuroMix study. Different PFAS were associated with changes in various subpopulations of natural killer (NK), T helper (Th), and cytotoxic T (Tc) cells. Broadly, PFAS concentrations were related to increased frequencies of NK cells and activated subpopulations of NK cells. Additionally, increased levels of activated T helper memory cell subpopulations point to Th2/Th17 and Treg-like skewed profiles. Finally, PFAS concentrations were associated with decreased frequencies of T cytotoxic cell subpopulations with CXCR3+ effector memory (EM) phenotypes. Several of these observations point to biologically plausible mechanisms that may contribute to explaining the epidemiological reports of immunosuppression by PFAS. Our results suggest that PFAS exposures even at relatively low levels are associated with changes in immune cell subpopulations, a finding which should be explored more thoroughly in a larger cohort. Additionally, causal relationships should be confirmed in experimental studies. Overall, this study demonstrates the strength of profiling by mass cytometry in revealing detailed changes in immune cells at a single cell level.

Automated quantification of measurable residual disease in chronic lymphocytic leukemia using an artificial intelligence-assisted workflow

Detection of measurable residual disease (MRD) in chronic lymphocytic leukemia (CLL) is an important prognostic marker. The most common CLL MRD method in current use is multiparameter flow cytometry, but availability is limited by the need for expert manual analysis. Automated analysis has the potential to expand access to CLL MRD testing. We evaluated the performance of an artificial intelligence (AI)-assisted multiparameter flow cytometry (MFC) workflow for CLL MRD. We randomly selected 113 CLL MRD FCS files and divided them into training and validation sets. The training set (n = 41) was gated by expert manual analysis and used to train the AI model. We then compared the validation set (n = 72) MRD results obtained by the AI-assisted analysis versus those by expert manual analysis using the Pearson correlation coefficient and Bland-Altman plot method. In the validation set, the AI-assisted analysis correctly categorized cases as MRD-negative versus MRD-positive in 96% of cases. When comparing the AI-assisted analysis versus the expert manual analysis, the Pearson r was 0.8650, mean bias was 0.2237 log10 units, and the 95% limit of agreement (LOA) was ±1.0282 log10 units. The AI-assisted analysis performed sub-optimally in atypical immunophenotype CLL and in cases lacking residual normal B cells. When excluding these outlier cases, the mean bias improved to 0.0680 log10 units and the 95% LOA to ±0.2926 log10 units. An automated AI-assisted workflow allows for the quantification of MRD in CLL with typical immunophenotype. Further work is required to improve performance in atypical immunophenotype CLL.

Comparison of three machine learning algorithms for classification of B-cell neoplasms using clinical flow cytometry data

Multiparameter flow cytometry data is visually inspected by expert personnel as part of standard clinical disease diagnosis practice. This is a demanding and costly process, and recent research has demonstrated that it is possible to utilize artificial intelligence (AI) algorithms to assist in the interpretive process. Here we report our examination of three previously published machine learning methods for classification of flow cytometry data and apply these to a B-cell neoplasm dataset to obtain predicted disease subtypes. Each of the examined methods classifies samples according to specific disease categories using ungated flow cytometry data. We compare and contrast the three algorithms with respect to their architectures, and we report the multiclass classification accuracies and relative required computation times. Despite different architectures, two of the methods, flowCat and EnsembleCNN, had similarly good accuracies with relatively fast computational times. We note a speed advantage for EnsembleCNN, particularly in the case of addition of training data and retraining of the classifier.

Transient inhibition of type I interferon enhances CD8 + T cell stemness and vaccine protection

Developing vaccines that promote CD8 + T cell memory is a challenge for infectious disease and cancer immunotherapy. TCF-1 + stem cell-like memory T (T SCM ) cells are important determinants of long-lived memory. Yet, the developmental requirements for T SCM formation are unclear. Here, we identify the temporal window for type I interferon (IFN-I) receptor (IFNAR) blockade to drive T SCM cell generation. T SCM cells were transcriptionally distinct and emerged from a transitional precursor of exhausted (T PEX ) cellular state concomitant with viral clearance. T SCM differentiation correlated with T cell retention within the lymph node paracortex, due to increased CXCR3 chemokine abundance which disrupted gradient formation. These affects were due a counterintuitive increase in IFNψ, which controlled cell location. Combining IFNAR inhibition with mRNA-LNP vaccination promoted specific T SCM differentiation and enhanced protection against chronic infection. These finding propose a new approach to vaccine design whereby modulation of inflammation promotes memory formation and function.

HIGHLIGHTS

Early, transient inhibition of the type I interferon (IFN) receptor (IFNAR) during acute viral infection promotes stem cell-like memory T (T SCM ) cell differentiation without establishing chronic infection. T SCM and precursor of exhausted (T PEX ) cellular states are distinguished transcriptionally and by cell surface markers. Developmentally, T SCM cell differentiation occurs via a transition from a T PEX state coinciding with viral clearance. Transient IFNAR blockade increases IFNψ production to modulate the ligands of CXCR3 and couple T SCM differentiation to cell retention within the T cell paracortex of the lymph node. Specific promotion of T SCM cell differentiation with nucleoside-modified mRNA-LNP vaccination elicits enhanced protection against chronic viral challenge.

Immune cells at the feto-maternal interface: Comprehensive characterization and insights into term labor

Immune cells at the feto-maternal interface play an important role in pregnancy; starting at implantation, maintenance of pregnancy, and parturition. The role of decidual immune cells in induction of labor still needs to be understood. Published reports on this topic show heterogeneity in methods of cell isolation, assay, analysis and cellular characterization making it difficult to collate available information in order to understand the contribution of immune cells at term leading to parturition. In the present study, available literature was reviewed to study the differences in immune cells between the decidua basalis and decidua parietalis, as well as between immune cells in term and preterm labor. Additionally, immune cells at the decidua parietalis were isolated from term not in labor (TNL) or term in labor (TL) samples and characterized via flow cytometry using a comprehensive, high-dimensional antibody panel. This allowed a full view of immune cell differences without combining multiple studies, which must include variation in isolation and analysis methods, for more conclusive data. The ratio of cells found in decidua parietalis in this study generally matched those reported in the literature, although we report a lower percentage of natural killer (NK) cells at term. We report that CD4 expression on CD8- NK cells decreased in term labor compared to not in labor samples, suggesting that natural killer cells may be migrating to other sites during labor. Also, we report a decrease in CD38 expression on CD8+ CD57+ T cells in labor, indicative of cytotoxic T cell senescence. Our study provides a comprehensive status of immune cells at the decidua-chorion interface at term.

Immunophenotyping with (phospho)protein profiling and fluorescent cell barcoding for single-cell signaling analysis and biomarker discovery

The microenvironment of hematologic cancers contributes to tumor cell survival and proliferation, as well as treatment resistance. Understanding tumor- and drug-induced changes to the immune cell composition and functionality is therefore critical for implementing optimal treatment strategies and for the development of novel cancer therapies. The liquid nature of peripheral blood makes this organ uniquely suited for single-cell studies by flow cytometry. (Phospho)protein profiles detected by flow cytometry analyses have been shown to correlate with ex vivo drug sensitivity and to predict treatment outcomes in hematologic cancers, demonstrating that this method is suitable for pre-clinical studies. Here, we present a flow cytometry protocol that combines multi-parameter immunophenotyping with single-cell (phospho)protein profiling. The protocol makes use of fluorescent cell barcoding, which means that multiple cell samples, either collected from different donors or exposed to different treatment conditions, can be combined and analyzed as one experiment. This reduces variability between samples, increases the throughput of the experiment, and lowers experimental costs. This protocol may serve as a guide for the use and further development of assays to study immunophenotype and cell signaling at single-cell resolution in normal and malignant cells. The read-outs may provide biological insight into cancer pathogenesis, identify novel drug targets, and ultimately serve as a biomarker to guide clinical decision-making.

Lack of functional TCR-epitope interaction is associated with herpes zoster through reduced downstream T cell activation

The role of T cell receptor (TCR) diversity in infectious disease susceptibility is not well understood. We use a systems immunology approach on three cohorts of herpes zoster (HZ) patients and controls to investigate whether TCR diversity against varicella-zoster virus (VZV) influences the risk of HZ. We show that CD4+ T cell TCR diversity against VZV glycoprotein E (gE) and immediate early 63 protein (IE63) after 1-week culture is more restricted in HZ patients. Single-cell RNA and TCR sequencing of VZV-specific T cells shows that T cell activation pathways are significantly decreased after stimulation with VZV peptides in convalescent HZ patients. TCR clustering indicates that TCRs from HZ patients co-cluster more often together than TCRs from controls. Collectively, our results suggest that not only lower VZV-specific TCR diversity but also reduced functional TCR affinity for VZV-specific proteins in HZ patients leads to lower T cell activation and consequently affects the susceptibility for viral reactivation.

PPARγ attenuates cellular senescence of alveolar macrophages in asthma-COPD overlap

BACKGROUND

Asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) represents a complex condition characterized by shared clinical and pathophysiological features of asthma and COPD in older individuals. However, the pathophysiology of ACO remains unexplored. We aimed to identify the major inflammatory cells in ACO, examine senescence within these cells, and elucidate the genes responsible for regulating senescence.

METHODS

Bioinformatic analyses were performed to investigate major cell types and cellular senescence signatures in a public single-cell RNA sequencing (scRNA-Seq) dataset derived from the lung tissues of patients with ACO. Similar analyses were carried out in an independent cohort study Immune Mechanisms Severe Asthma (IMSA), which included bulk RNA-Seq and CyTOF data from bronchoalveolar lavage fluid (BALF) samples.

RESULTS

The analysis of the scRNA-Seq data revealed that monocytes/ macrophages were the predominant cell type in the lung tissues of ACO patients, constituting more than 50% of the cells analyzed. Lung monocytes/macrophages from patients with ACO exhibited a lower prevalence of senescence as defined by lower enrichment scores of SenMayo and expression levels of cellular senescence markers. Intriguingly, analysis of the IMSA dataset showed similar results in patients with severe asthma. They also exhibited a lower prevalence of senescence, particularly in airway CD206 + macrophages, along with increased cytokine expression (e.g., IL-4, IL-13, and IL-22). Further exploration identified alveolar macrophages as a major subtype of monocytes/macrophages driving cellular senescence in ACO. Differentially expressed genes related to oxidation-reduction, cytokines, and growth factors were implicated in regulating senescence in alveolar macrophages. PPARγ (Peroxisome Proliferator-Activated Receptor Gamma) emerged as one of the predominant regulators modulating the senescent signature of alveolar macrophages in ACO.

CONCLUSION

The findings suggest that senescence in macrophages, particularly alveolar macrophages, plays a crucial role in the pathophysiology of ACO. Furthermore, PPARγ may represent a potential therapeutic target for interventions aimed at modulating senescence-associated processes in ACO.Key words ACO, Asthma, COPD, Macrophages, Senescence, PPARγ.

Efficient cytometry analysis with FlowSOM in Python boosts interoperability with other single-cell tools

MOTIVATION

We describe a new Python implementation of FlowSOM, a clustering method for cytometry data.

RESULTS

This implementation is faster than the original version in R, better adapted to work with single-cell omics data including integration with current single-cell data structures and includes all the original visualizations, such as the star and pie plot.

AVAILABILITY AND IMPLEMENTATION

The FlowSOM Python implementation is freely available on GitHub: https://github.com/saeyslab/FlowSOM_Python.

SpiDe-Sr: blind super-resolution network for precise cell segmentation and clustering in spatial proteomics imaging

Spatial proteomics elucidates cellular biochemical changes with unprecedented topological level. Imaging mass cytometry (IMC) is a high-dimensional single-cell resolution platform for targeted spatial proteomics. However, the precision of subsequent clinical analysis is constrained by imaging noise and resolution. Here, we propose SpiDe-Sr, a super-resolution network embedded with a denoising module for IMC spatial resolution enhancement. SpiDe-Sr effectively resists noise and improves resolution by 4 times. We demonstrate SpiDe-Sr respectively with cells, mouse and human tissues, resulting 18.95%/27.27%/21.16% increase in peak signal-to-noise ratio and 15.95%/31.63%/15.52% increase in cell extraction accuracy. We further apply SpiDe-Sr to study the tumor microenvironment of a 20-patient clinical breast cancer cohort with 269,556 single cells, and discover the invasion of Gram-negative bacteria is positively correlated with carcinogenesis markers and negatively correlated with immunological markers. Additionally, SpiDe-Sr is also compatible with fluorescence microscopy imaging, suggesting SpiDe-Sr an alternative tool for microscopy image super-resolution.

FlowSOM clustering - A novel pattern recognition approach for water research: Application to a hyper-arid coastal aquifer system

Monitoring and understanding of water resources have become essential in designing effective and sustainable management strategies to overcome the growing water quality challenges. In this context, the utilization of unsupervised learning techniques for evaluating environmental tracers has facilitated the exploration of sources and dynamics of groundwater systems through pattern recognition. However, conventional techniques may overlook spatial and temporal non-linearities present in water research data. This paper introduces the adaptation of FlowSOM, a pioneering approach that combines self-organizing maps (SOM) and minimal spanning trees (MST), with the fast-greedy network clustering algorithm to unravel intricate relationships within multivariate water quality datasets. By capturing connections within the data, this ensemble tool enhances clustering and pattern recognition. Applied to the complex water quality context of the hyper-arid transboundary Caplina/Concordia coastal aquifer system (Peru/Chile), the FlowSOM network and clustering yielded compelling results in pattern recognition of the aquifer salinization. Analyzing 143 groundwater samples across eight variables, including major ions, the approach supports the identification of distinct clusters and connections between them. Three primary sources of salinization were identified: river percolation, slow lateral aquitard recharge, and seawater intrusion. The analysis demonstrated the superiority of FlowSOM clustering over traditional techniques in the case study, producing clusters that align more closely with the actual hydrogeochemical pattern. The outcomes broaden the utilization of multivariate analysis in water research, presenting a comprehensive approach to support the understanding of groundwater systems.

PPARγ Attenuates Cellular Senescence of Alveolar Macrophages in Asthma- COPD Overlap

Asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) represents a complex condition characterized by shared clinical and pathophysiological features of asthma and COPD in older individuals. However, the pathophysiology of ACO remains unexplored. We aimed to identify the major inflammatory cells in ACO, examine senescence within these cells, and elucidate the genes responsible for regulating senescence. Bioinformatic analyses were performed to investigate major cell types and cellular senescence signatures in a public single-cell RNA sequencing (scRNA-Seq) dataset derived from the lung tissues of patients with ACO. Similar analyses were carried out in an independent cohort study Immune Mechanisms Severe Asthma (IMSA), which included bulk RNA-Seq and CyTOF data from bronchoalveolar lavage fluid (BALF) samples. The analysis of the scRNA-Seq data revealed that monocytes/ macrophages were the predominant cell type in the lung tissues of ACO patients, constituting more than 50% of the cells analyzed. Lung monocytes/macrophages from patients with ACO exhibited a lower prevalence of senescence as defined by lower enrichment scores of SenMayo and expression levels of cellular senescence markers. Intriguingly, analysis of the IMSA dataset showed similar results in patients with severe asthma. They also exhibited a lower prevalence of senescence, particularly in airway CD206 + macrophages, along with increased cytokine expression (e.g., IL-4, IL-13, and IL-22). Further exploration identified alveolar macrophages as a major subtype of monocytes/macrophages driving cellular senescence in ACO. Differentially expressed genes related to oxidation-reduction, cytokines, and growth factors were implicated in regulating senescence in alveolar macrophages. PPARγ (Peroxisome Proliferator-Activated Receptor Gamma) emerged as one of the predominant regulators modulating the senescent signature of alveolar macrophages in ACO. Collectively, the findings suggest that senescence in macrophages, particularly alveolar macrophages, plays a crucial role in the pathophysiology of ACO. Furthermore, PPARγ may represent a potential therapeutic target for interventions aimed at modulating senescence-associated processes in ACO.

A 19-color single-tube full spectrum flow cytometry assay for the detection of measurable residual disease in acute myeloid leukemia

Multiparameter flow cytometry (MFC) has emerged as a standard method for quantifying measurable residual disease (MRD) in acute myeloid leukemia. However, the limited number of available channels on conventional flow cytometers requires the division of a diagnostic sample into several tubes, restricting the number of cells and the complexity of immunophenotypes that can be analyzed. Full spectrum flow cytometers overcome this limitation by enabling the simultaneous use of up to 40 fluorescent markers. Here, we used this approach to develop a good laboratory practice-conform single-tube 19-color MRD detection assay that complies with recommendations of the European LeukemiaNet Flow-MRD Working Party. We based our assay on clinically-validated antibody clones and evaluated its performance on an IVD-certified full spectrum flow cytometer. We measured MRD and normal bone marrow samples and compared the MRD data to a widely used reference MRD-MFC panel generating highly concordant results. Using our newly developed single-tube panel, we established reference values in healthy bone marrow for 28 consensus leukemia-associated immunophenotypes and introduced a semi-automated dimensionality-reduction, clustering and cell type identification approach that aids the unbiased detection of aberrant cells. In summary, we provide a comprehensive full spectrum MRD-MFC workflow with the potential for rapid implementation for routine diagnostics due to reduced cell requirements and ease of data analysis with increased reproducibility in comparison to conventional FlowMRD routines.

A versatile CRISPR-Cas13d platform for multiplexed transcriptomic regulation and metabolic engineering in primary human T cells

CRISPR technologies have begun to revolutionize T cell therapies; however, conventional CRISPR-Cas9 genome-editing tools are limited in their safety, efficacy, and scope. To address these challenges, we developed multiplexed effector guide arrays (MEGA), a platform for programmable and scalable regulation of the T cell transcriptome using the RNA-guided, RNA-targeting activity of CRISPR-Cas13d. MEGA enables quantitative, reversible, and massively multiplexed gene knockdown in primary human T cells without targeting or cutting genomic DNA. Applying MEGA to a model of CAR T cell exhaustion, we robustly suppressed inhibitory receptor upregulation and uncovered paired regulators of T cell function through combinatorial CRISPR screening. We additionally implemented druggable regulation of MEGA to control CAR activation in a receptor-independent manner. Lastly, MEGA enabled multiplexed disruption of immunoregulatory metabolic pathways to enhance CAR T cell fitness and anti-tumor activity in vitro and in vivo. MEGA offers a versatile synthetic toolkit for applications in cancer immunotherapy and beyond.

CytoPipeline and CytoPipelineGUI: a Bioconductor R package suite for building and visualizing automated pre-processing pipelines for flow cytometry data

BACKGROUND

With the increase of the dimensionality in flow cytometry data over the past years, there is a growing need to replace or complement traditional manual analysis (i.e. iterative 2D gating) with automated data analysis pipelines. A crucial part of these pipelines consists of pre-processing and applying quality control filtering to the raw data, in order to use high quality events in the downstream analyses. This part can in turn be split into a number of elementary steps: signal compensation or unmixing, scale transformation, debris, doublets and dead cells removal, batch effect correction, etc. However, assembling and assessing the pre-processing part can be challenging for a number of reasons. First, each of the involved elementary steps can be implemented using various methods and R packages. Second, the order of the steps can have an impact on the downstream analysis results. Finally, each method typically comes with its specific, non standardized diagnostic and visualizations, making objective comparison difficult for the end user.

RESULTS

Here, we present CytoPipeline and CytoPipelineGUI, two R packages to build, compare and assess pre-processing pipelines for flow cytometry data. To exemplify these new tools, we present the steps involved in designing a pre-processing pipeline on a real life dataset and demonstrate different visual assessment use cases. We also set up a benchmarking comparing two pre-processing pipelines differing by their quality control methods, and show how the package visualization utilities can provide crucial user insight into the obtained benchmark metrics.

CONCLUSION

CytoPipeline and CytoPipelineGUI are two Bioconductor R packages that help building, visualizing and assessing pre-processing pipelines for flow cytometry data. They increase productivity during pipeline development and testing, and complement benchmarking tools, by providing user intuitive insight into benchmarking results.

IL-23 induces CLEC5A+ IL-17A+ neutrophils and elicit skin inflammation associated with psoriatic arthritis

IL-23-activation of IL-17 producing T cells is involved in many rheumatic diseases. Herein, we investigate the role of IL-23 in the activation of myeloid cell subsets that contribute to skin inflammation in mice and man. IL-23 gene transfer in WT, IL-23RGFP reporter mice and subsequent analysis with spectral cytometry show that IL-23 regulates early innate immune events by inducing the expansion of a myeloid MDL1+CD11b+Ly6G+ population that dictates epidermal hyperplasia, acanthosis, and parakeratosis; hallmark pathologic features of psoriasis. Genetic ablation of MDL-1, a major PU.1 transcriptional target during myeloid differentiation exclusively expressed in myeloid cells, completely prevents IL-23-pathology. Moreover, we show that IL-23-induced myeloid subsets are also capable of producing IL-17A and IL-23R+MDL1+ cells are present in the involved skin of psoriasis patients and gene expression correlations between IL-23 and MDL-1 have been validated in multiple patient cohorts. Collectively, our data demonstrate a novel role of IL-23 in MDL-1-myelopoiesis that is responsible for skin inflammation and related pathologies. Our data open a new avenue of investigations regarding the role of IL-23 in the activation of myeloid immunoreceptors and their role in autoimmunity.

Standardized high-dimensional spectral cytometry protocol and panels for whole blood immune phenotyping in clinical and translational studies

Flow cytometry is the method of choice for immunophenotyping in the context of clinical, translational, and systems immunology studies. Among the latter, the Milieu Intérieur (MI) project aims at defining the boundaries of a healthy immune response to identify determinants of immune response variation. MI used immunophenotyping of a 1000 healthy donor cohort by flow cytometry as a principal outcome for immune variance at steady state. New generation spectral cytometers now enable high-dimensional immune cell characterization from small sample volumes. Therefore, for the MI 10-year follow up study, we have developed two high-dimensional spectral flow cytometry panels for deep characterization of innate and adaptive whole blood immune cells (35 and 34 fluorescent markers, respectively). We have standardized the protocol for sample handling, staining, acquisition, and data analysis. This approach enables the reproducible quantification of over 182 immune cell phenotypes at a single site. We have applied the protocol to discern minor differences between healthy and patient samples and validated its value for application in immunomonitoring studies. Our protocol is currently used for characterization of the impact of age and environmental factors on peripheral blood immune phenotypes of >400 donors from the initial MI cohort.

Enhanced detection of antigen-specific T cells by a multiplexed AIM assay

Broadly applicable methods to identify and characterize antigen-specific CD4+ and CD8+ T cells are key to immunology research, including studies of vaccine responses and immunity to infectious diseases. We developed a multiplexed activation-induced marker (AIM) assay that presents several advantages compared to single pairs of AIMs. The simultaneous measurement of four AIMs (CD69, 4-1BB, OX40, and CD40L) creates six AIM pairs that define CD4+ T cell populations with partial and variable overlap. When combined in an AND/OR Boolean gating strategy for analysis, this approach enhances CD4+ T cell detection compared to any single AIM pair, while CD8+ T cells are dominated by CD69/4-1BB co-expression. Supervised and unsupervised clustering analyses show differential expression of the AIMs in defined T helper lineages and that multiplexing mitigates phenotypic biases. Paired and unpaired comparisons of responses to infections (HIV and cytomegalovirus [CMV]) and vaccination (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) validate the robustness and versatility of the method.

Lower frequencies of circulating suppressive regulatory T cells and higher frequencies of CD4+ naïve T cells at baseline are associated with severe immune-related adverse events in immune checkpoint inhibitor-treated melanoma

BACKGROUND

Immune-related adverse events (irAEs) are major barriers of clinical management and further development of immune checkpoint inhibitors (ICIs) for cancer therapy. Therefore, biomarkers associated with the onset of severe irAEs are needed. In this study, we aimed to identify immune features detectable in peripheral blood and associated with the development of severe irAEs that required clinical intervention.

METHODS

We used a 43-marker mass cytometry panel to characterize peripheral blood mononuclear cells from 28 unique patients with melanoma across 29 lines of ICI therapy before treatment (baseline), before the onset of irAEs (pre-irAE) and at the peak of irAEs (irAE-max). In the 29 lines of ICI therapy, 18 resulted in severe irAEs and 11 did not.

RESULTS

Unsupervised and gated population analysis showed that patients with severe irAEs had a higher frequency of CD4+ naïve T cells and lower frequency of CD16+ natural killer (NK) cells at all time points. Gated population analysis additionally showed that patients with severe irAEs had fewer T cell immunoreceptor with Ig and ITIM domain (TIGIT+) regulatory T cells at baseline and more activated CD38+ CD4+ central memory T cells (TCM) and CD39+ and Human Leukocyte Antigen-DR Isotype (HLA-DR)+ CD8+ TCM at peak of irAEs. The differentiating immune features at baseline were predominantly seen in patients with gastrointestinal and cutaneous irAEs and type 1 diabetes. Higher frequencies of CD4+ naïve T cells and lower frequencies of CD16+ NK cells were also associated with clinical benefit to ICI therapy.

CONCLUSIONS

This study demonstrates that high-dimensional immune profiling can reveal novel blood-based immune signatures associated with risk and mechanism of severe irAEs. Development of severe irAEs in melanoma could be the result of reduced immune inhibitory capacity pre-ICI treatment, resulting in more activated TCM cells after treatment.

SPDB: a comprehensive resource and knowledgebase for proteomic data at the single-cell resolution

The single-cell proteomics enables the direct quantification of protein abundance at the single-cell resolution, providing valuable insights into cellular phenotypes beyond what can be inferred from transcriptome analysis alone. However, insufficient large-scale integrated databases hinder researchers from accessing and exploring single-cell proteomics, impeding the advancement of this field. To fill this deficiency, we present a comprehensive database, namely Single-cell Proteomic DataBase (SPDB, https://scproteomicsdb.com/), for general single-cell proteomic data, including antibody-based or mass spectrometry-based single-cell proteomics. Equipped with standardized data process and a user-friendly web interface, SPDB provides unified data formats for convenient interaction with downstream analysis, and offers not only dataset-level but also protein-level data search and exploration capabilities. To enable detailed exhibition of single-cell proteomic data, SPDB also provides a module for visualizing data from the perspectives of cell metadata or protein features. The current version of SPDB encompasses 133 antibody-based single-cell proteomic datasets involving more than 300 million cells and over 800 marker/surface proteins, and 10 mass spectrometry-based single-cell proteomic datasets involving more than 4000 cells and over 7000 proteins. Overall, SPDB is envisioned to be explored as a useful resource that will facilitate the wider research communities by providing detailed insights into proteomics from the single-cell perspective.

Loss of function of XBP1 splicing activity of IRE1α favors B cell tolerance breakdown

Anti-nuclear antibodies are the hallmark of autoimmune diseases such as systemic lupus erythematosus (SLE) and scleroderma. However, the molecular mechanisms of B cell tolerance breakdown in these pathological contexts are poorly known. The study of rare familial forms of autoimmune diseases could therefore help to better describe common biological mechanisms leading to B cell tolerance breakdown. By Whole-Exome Sequencing, we identified a new heterozygous mutation (p.R594C) in ERN1 gene, encoding IRE1α (Inositol-Requiring Enzyme 1α), in a multiplex family with several members presenting autoantibody-mediated autoimmunity. Using human cell lines and a knock-in (KI) transgenic mouse model, we showed that this mutation led to a profound defect of IRE1α ribonuclease activity on X-Box Binding Protein 1 (XBP1) splicing. The KI mice developed a broad panel of autoantibodies, however in a subclinical manner. These results suggest that a decrease of spliced form of XBP1 (XBP1s) production could contribute to B cell tolerance breakdown and give new insights into the function of IRE1α which are important to consider for the development of IRE1α targeting strategies.

NET formation is a default epigenetic program controlled by PAD4 in apoptotic neutrophils

Neutrophil extracellular traps (NETs) not only counteract bacterial and fungal pathogens but can also promote thrombosis, autoimmunity, and sterile inflammation. The presence of citrullinated histones, generated by the peptidylarginine deiminase 4 (PAD4), is synonymous with NETosis and is considered independent of apoptosis. Mitochondrial- and death receptor-mediated apoptosis promote gasdermin E (GSDME)-dependent calcium mobilization and membrane permeabilization leading to histone H3 citrullination (H3Cit), nuclear DNA extrusion, and cytoplast formation. H3Cit is concentrated at the promoter in bone marrow neutrophils and redistributes in a coordinated process from promoter to intergenic and intronic regions during apoptosis. Loss of GSDME prevents nuclear and plasma membrane disruption of apoptotic neutrophils but prolongs early apoptosis-induced cellular changes to the chromatin and cytoplasmic granules. Apoptotic signaling engages PAD4 in neutrophils, establishing a cellular state that is primed for NETosis, but that occurs only upon membrane disruption by GSDME, thereby redefining the end of life for neutrophils.

Tumor endothelial cell autophagy is a key vascular-immune checkpoint in melanoma

Tumor endothelial cells (TECs) actively repress inflammatory responses and maintain an immune-excluded tumor phenotype. However, the molecular mechanisms that sustain TEC-mediated immunosuppression remain largely elusive. Here, we show that autophagy ablation in TECs boosts antitumor immunity by supporting infiltration and effector function of T-cells, thereby restricting melanoma growth. In melanoma-bearing mice, loss of TEC autophagy leads to the transcriptional expression of an immunostimulatory/inflammatory TEC phenotype driven by heightened NF-kB and STING signaling. In line, single-cell transcriptomic datasets from melanoma patients disclose an enriched InflammatoryHigh /AutophagyLow TEC phenotype in correlation with clinical responses to immunotherapy, and responders exhibit an increased presence of inflamed vessels interfacing with infiltrating CD8+ T-cells. Mechanistically, STING-dependent immunity in TECs is not critical for the immunomodulatory effects of autophagy ablation, since NF-kB-driven inflammation remains functional in STING/ATG5 double knockout TECs. Hence, our study identifies autophagy as a principal tumor vascular anti-inflammatory mechanism dampening melanoma antitumor immunity.

Exploring the Role of Spatial Confinement in Immune Cell Recruitment and Regeneration of Skin Wounds

Microporous annealed particle (MAP) scaffolds are injectable granular materials comprised of micron sized hydrogel particles (microgels). The diameter of these microgels directly determines the size of the interconnected void space between particles where infiltrating or encapsulated cells reside. This tunable porosity allows the authors to use MAP scaffolds to study the impact of spatial confinement (SC) on both cellular behaviors and the host response to biomaterials. Despite previous studies showing that pore size and SC influence cellular phenotypes, including mitigating macrophage inflammatory response, there is still a gap in knowledge regarding how SC within a biomaterial modulates immune cell recruitment in vivo in wounds and implants. Thus, the immune cell profile within confined and unconfined biomaterials is studied using small (40 µm), medium (70 µm), and large (130 µm) diameter spherical microgels, respectively. This work uncovered that MAP scaffolds impart regenerative wound healing with an IgG1-biased Th2 response. MAP scaffolds made with large microgels promote a balanced pro-regenerative macrophage response, resulting in enhanced wound healing with mature collagen regeneration and reduced inflammation levels.

The extrafollicular B cell response is a hallmark of childhood idiopathic nephrotic syndrome

The efficacy of the B cell-targeting drug rituximab (RTX) in childhood idiopathic nephrotic syndrome (INS) suggests that B cells may be implicated in disease pathogenesis. However, B cell characterization in children with INS remains limited. Here, using single-cell RNA sequencing, we demonstrate that a B cell transcriptional program poised for effector functions represents the major immune perturbation in blood samples from children with active INS. This transcriptional profile was associated with an extrafollicular B cell response marked by the expansion of atypical B cells (atBCs), marginal zone-like B cells, and antibody-secreting cells (ASCs). Flow cytometry of blood from 13 children with active INS and 24 healthy donors confirmed the presence of an extrafollicular B cell response denoted by the expansion of proliferating RTX-sensitive extrafollicular (CXCR5-) CD21low T-bet+ CD11c+ atBCs and short-lived T-bet+ ASCs in INS. Together, our study provides evidence for an extrafollicular origin for humoral immunity in active INS.

From data to diagnosis: how machine learning is revolutionizing biomarker discovery in idiopathic inflammatory myopathies

Idiopathic inflammatory myopathies (IIMs) are a heterogeneous group of muscle disorders including adult and juvenile dermatomyositis, polymyositis, immune-mediated necrotising myopathy and sporadic inclusion body myositis, all of which present with variable symptoms and disease progression. The identification of effective biomarkers for IIMs has been challenging due to the heterogeneity between IIMs and within IIM subgroups, but recent advances in machine learning (ML) techniques have shown promises in identifying novel biomarkers. This paper reviews recent studies on potential biomarkers for IIM and evaluates their clinical utility. We also explore how data analytic tools and ML algorithms have been used to identify biomarkers, highlighting their potential to advance our understanding and diagnosis of IIM and improve patient outcomes. Overall, ML techniques have great potential to revolutionize biomarker discovery in IIMs and lead to more effective diagnosis and treatment.

An end-to-end workflow for multiplexed image processing and analysis

Multiplexed imaging enables the simultaneous spatial profiling of dozens of biological molecules in tissues at single-cell resolution. Extracting biologically relevant information, such as the spatial distribution of cell phenotypes from multiplexed tissue imaging data, involves a number of computational tasks, including image segmentation, feature extraction and spatially resolved single-cell analysis. Here, we present an end-to-end workflow for multiplexed tissue image processing and analysis that integrates previously developed computational tools to enable these tasks in a user-friendly and customizable fashion. For data quality assessment, we highlight the utility of napari-imc for interactively inspecting raw imaging data and the cytomapper R/Bioconductor package for image visualization in R. Raw data preprocessing, image segmentation and feature extraction are performed using the steinbock toolkit. We showcase two alternative approaches for segmenting cells on the basis of supervised pixel classification and pretrained deep learning models. The extracted single-cell data are then read, processed and analyzed in R. The protocol describes the use of community-established data containers, facilitating the application of R/Bioconductor packages for dimensionality reduction, single-cell visualization and phenotyping. We provide instructions for performing spatially resolved single-cell analysis, including community analysis, cellular neighborhood detection and cell-cell interaction testing using the imcRtools R/Bioconductor package. The workflow has been previously applied to imaging mass cytometry data, but can be easily adapted to other highly multiplexed imaging technologies. This protocol can be implemented by researchers with basic bioinformatics training, and the analysis of the provided dataset can be completed within 5-6 h. An extended version is available at https://bodenmillergroup.github.io/IMCDataAnalysis/ .

Immune profile of patients with peritoneal carcinomatosis selected for CRS-HIPEC therapy

Cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) is a treatment option for peritoneal carcinomatosis (PC) from colorectal cancer (CRC), which is otherwise a terminal stage of disease. Nevertheless, survival outcomes are only marginally superior to other treatments. This fact highlights the need for better strategies to control intra-abdominal disease recurrence after CRS-HIPEC, including the complementary use of immunotherapies. The aim of this study was therefore to investigate the immune phenotype of T cells in patients with PC. Fifty three patients with CRC (34 patients with PC and 19 patients without PC) were enrolled in a prospective study (clinicaltrials.gov: NCT04108936). Peripheral blood and omental fat were collected to isolate peripheral blood mononuclear cells (PBMCs) and adipose tissue mononuclear cells (ATMCs). These cells were analysed by flow cytometry using a panel focused upon T cell memory differentiation and exhaustion markers. We found a more naïve profile for CD8+ T cells in peripheral blood and intra-abdominal fat of PC patients compared to comparator group (CG) patients. Furthermore, there was an over-representation of CD4+ T cells expressing inhibitory receptors in adipose tissue of PC patients, but not in blood. Our description of intraperitoneal T cell subsets gives us a better understanding of how peritoneal carcinomatosis shapes local immune responses.

Active tuberculosis patients have high systemic IgG levels and B-cell fingerprinting, characterized by a reduced capacity to produce IFN-γ or IL-10 as a response to M.tb antigens

Introduction

Tuberculosis (TB) is a bacterial infection caused by Mycobacterium tuberculosis (M.tb). B cells are the central mediator of the humoral response; they are responsible for producing antibodies in addition to mediating other functions. The role of the cellular response during the TB spectrum by B cells is still controversial.

Methods

In this study, we evaluated the distribution of the circulating B cell subsets in patients with active and latent TB (ATB and LTB, respectively) and how they respond to stimuli of protein or lipid from M.tb.

Results

Here, we show that ATB patients show an immune fingerprinting. However, patients with drug-sensitive- (DS-TB) or drug-resistant- (DR-TB) TB have altered frequencies of circulating B cells. DS-TB and DR-TB display a unique profile characterized by high systemic levels of IFN-γ, IL-10, IgG, IgG/IgM ratio, and total B cells. Moreover, B cells from DR-TB are less efficient in producing IL-10, and both DS-TB and DR-TB produce less IFN-γ in response to M.tb antigens.

Conclusion

These results provide new insights into the population dynamics of the cellular immune response by B cells against M.tb and suggest a fingerprinting to characterize the B-cell response on DR-TB.

A robust pipeline for high-content, high-throughput immunophenotyping reveals age- and genetics-dependent changes in blood leukocytes

High-dimensional flow cytometry is the gold standard to study the human immune system in large cohorts. However, large sample sizes increase inter-experimental variation because of technical and experimental inaccuracies introduced by batch variability. Our high-throughput sample processing pipeline in combination with 28-color flow cytometry focuses on increased throughput (192 samples/experiment) and high reproducibility. We implemented quality control checkpoints to reduce technical and experimental variation. Finally, we integrated FlowSOM clustering to facilitate automated data analysis and demonstrate the reproducibility of our pipeline in a study with 3,357 samples. We reveal age-associated immune dynamics in 2,300 individuals, signified by decreasing T and B cell subsets with age. In addition, by combining genetic analyses, our approach revealed unique immune signatures associated with a single nucleotide polymorphism (SNP) that abrogates CD45 isoform splicing. In summary, we provide a versatile and reliable high-throughput, flow cytometry-based pipeline for immune discovery and exploration in large cohorts.

Bifidobacterium infantis supplementation versus placebo in early life to improve immunity in infants exposed to HIV: a protocol for a randomized trial

INTRODUCTION

Infants who are born from mothers with HIV (infants who are HIV exposed but uninfected; iHEU) are at higher risk of morbidity and display multiple immune alterations compared to infants who are HIV-unexposed (iHU). Easily implementable strategies to improve immunity of iHEU, and possibly subsequent clinical health outcomes, are needed. iHEU have altered gut microbiome composition and bifidobacterial depletion, and relative abundance of Bifidobacterium infantis has been associated with immune ontogeny, including humoral and cellular vaccine responses. Therefore, we will assess microbiological and immunological phenotypes and clinical outcomes in a randomized, double-blinded trial of B. infantis Rosell®-33 versus placebo given during the first month of life in South African iHEU.

METHODS

This is a parallel, randomised, controlled trial. Two-hundred breastfed iHEU will be enrolled from the Khayelitsha Site B Midwife Obstetric Unit in Cape Town, South Africa and 1:1 randomised to receive 8 × 109 CFU B. infantis Rosell®-33 daily or placebo for the first 4 weeks of life, starting on day 1-3 of life. Infants will be followed over 36 weeks with extensive collection of meta-data and samples. Primary outcomes include gut microbiome composition and diversity, intestinal inflammation and microbial translocation and cellular vaccine responses. Additional outcomes include biological (e.g. gut metabolome and T cell phenotypes) and clinical (e.g. growth and morbidity) outcome measures.

DISCUSSION

The results of this trial will provide evidence whether B. infantis supplementation during early life could improve health outcomes for iHEU.

ETHICS AND DISSEMINATION

Approval for this study has been obtained from the ethics committees at the University of Cape Town (HREC Ref 697/2022) and Seattle Children's Research Institute (STUDY00003679).

TRIAL REGISTRATION

Pan African Clinical Trials Registry Identifier: PACTR202301748714019.

CLINICAL

TRIALS

gov: NCT05923333.

PROTOCOL VERSION

Version 1.8, dated 18 July 2023.

CRB1-Associated Retinal Dystrophy Patients Have Expanded Lewis Glycoantigen-Positive T Cells

Purpose

Eye inflammation may occur in patients with inherited retinal dystrophies (IRDs) and is seen frequently in IRDs associated with mutations in the CRB1 gene. The purpose of this study was to determine the types of inflammatory cells involved in IRDs, by deep profiling the composition of peripheral blood mononuclear cells of patients with a CRB1-associated IRD.

Methods

This study included 33 patients with an IRD with confirmed CRB1 mutations and 32 healthy controls. A 43-parameter flow cytometry analysis was performed on peripheral blood mononuclear cells isolated from venous blood. FlowSOM and manual Boolean combination gating were used to identify and quantify immune cell subsets.

Results

Comparing patients with controls revealed a significant increase in patients in the abundance of circulating CD4+ T cells and CD8+ T cells that express sialyl Lewis X antigen. Furthermore, we detected a decrease in plasmacytoid dendritic cells and an IgA+CD24+CD38+ transitional B-cell subset in patients with an IRD.

Conclusions

Patients with a CRB1-associated IRD show marked changes in blood leukocyte composition, affecting lymphocyte and dendritic cell populations. These results implicate inflammatory pathways in the disease manifestations of IRDs.

Spontaneous HIV expression during suppressive ART is associated with the magnitude and function of HIV-specific CD4+ and CD8+ T cells

Spontaneous transcription and translation of HIV can persist during suppressive antiretroviral therapy (ART). The quantity, phenotype, and biological relevance of this spontaneously "active" reservoir remain unclear. Using multiplexed single-cell RNAflow-fluorescence in situ hybridization (FISH), we detect active HIV transcription in 14/18 people with HIV on suppressive ART, with a median of 28/million CD4+ T cells. While these cells predominantly exhibit abortive transcription, p24-expressing cells are evident in 39% of participants. Phenotypically diverse, active reservoirs are enriched in central memory T cells and CCR6- and activation-marker-expressing cells. The magnitude of the active reservoir positively correlates with total HIV-specific CD4+ and CD8+ T cell responses and with multiple HIV-specific T cell clusters identified by unsupervised analysis. These associations are particularly strong with p24-expressing active reservoir cells. Single-cell vDNA sequencing shows that active reservoirs are largely dominated by defective proviruses. Our data suggest that these reservoirs maintain HIV-specific CD4+ and CD8+ T responses during suppressive ART.

Mapping human natural killer cell development in pediatric tonsil by imaging mass cytometry and high-resolution microscopy

Natural killer (NK) cells develop from CD34+ progenitors in a stage-specific manner defined by changes in cell surface receptor expression and function. Secondary lymphoid tissues, including tonsil, are sites of human NK cell development. Here we present new insights into human NK cell development in pediatric tonsil using cyclic immunofluorescence and imaging mass cytometry. We show that NK cell subset localization and interactions are dependent on NK cell developmental stage and tissue residency. NK cell progenitors are found in the interfollicular domain in proximity to cytokine-expressing stromal cells that promote proliferation and maturation. Mature NK cells are primarily found in the T-cell rich parafollicular domain engaging in cell-cell interactions that differ depending on their stage and tissue residency. The presence of local inflammation results in changes in NK cell interactions, abundance, and localization. This study provides the first comprehensive atlas of human NK cell development in secondary lymphoid tissue.

Cyclone: an accessible pipeline to analyze, evaluate, and optimize multiparametric cytometry data

In the past decade, high-dimensional single-cell technologies have revolutionized basic and translational immunology research and are now a key element of the toolbox used by scientists to study the immune system. However, analysis of the data generated by these approaches often requires clustering algorithms and dimensionality reduction representation, which are computationally intense and difficult to evaluate and optimize. Here, we present Cytometry Clustering Optimization and Evaluation (Cyclone), an analysis pipeline integrating dimensionality reduction, clustering, evaluation, and optimization of clustering resolution, and downstream visualization tools facilitating the analysis of a wide range of cytometry data. We benchmarked and validated Cyclone on mass cytometry (CyTOF), full-spectrum fluorescence-based cytometry, and multiplexed immunofluorescence (IF) in a variety of biological contexts, including infectious diseases and cancer. In each instance, Cyclone not only recapitulates gold standard immune cell identification but also enables the unsupervised identification of lymphocytes and mononuclear phagocyte subsets that are associated with distinct biological features. Altogether, the Cyclone pipeline is a versatile and accessible pipeline for performing, optimizing, and evaluating clustering on a variety of cytometry datasets, which will further power immunology research and provide a scaffold for biological discovery.

Computational Methods for Single-Cell Proteomics

Advances in single-cell proteomics technologies have resulted in high-dimensional datasets comprising millions of cells that are capable of answering key questions about biology and disease. The advent of these technologies has prompted the development of computational tools to process and visualize the complex data. In this review, we outline the steps of single-cell and spatial proteomics analysis pipelines. In addition to describing available methods, we highlight benchmarking studies that have identified advantages and pitfalls of the currently available computational toolkits. As these technologies continue to advance, robust analysis tools should be developed in tandem to take full advantage of the potential biological insights provided by these data.

Adjuvant dendritic cell-based immunotherapy after cytoreductive surgery and hyperthermic intraperitoneal chemotherapy in patients with malignant peritoneal mesothelioma: a phase II clinical trial

BACKGROUND

Malignant peritoneal mesothelioma (MPM) is an aggressive malignancy with a poor prognosis. Cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) improves survival outcomes, but recurrence rates remain high. Dendritic cell-based immunotherapy (DCBI) showed promising results in patients with pleural mesothelioma. The primary aim of this trial was to determine feasibility of adjuvant DCBI after CRS-HIPEC.

METHODS

This open-label, single-center, phase II clinical trial, performed in the Erasmus MC Cancer Institute Rotterdam, the Netherlands, included patients with epithelioid MPM. 4-6 weeks before CRS-HIPEC leukapheresis was performed. 8-10 weeks after surgery, DCBI was administered three times biweekly. Feasibility was defined as administration of at least three adjuvant vaccinations in 75% of patients. Comprehensive immune cell profiling was performed on peripheral blood samples prior to and during treatment.

RESULTS

All patients who received CRS-HIPEC (n=16) were successfully treated with adjuvant DCBI. No severe toxicity related to DCBI was observed. Median progression-free survival (PFS) was 12 months (IQR 5-23) and median overall survival was not reached. DCBI was associated with increased proliferation of circulating natural killer cells and CD4+ T-helper (Th) cells. Co-stimulatory molecules, including ICOS, HLA-DR, and CD28 were upregulated predominantly on memory or proliferating Th-cells and minimally on CD8+ cytotoxic T-lymphocytes (CTLs) after treatment. However, an increase in CD8+ terminally differentiated effector memory (Temra) cells positively correlated with PFS, whereas co-expression of ICOS and Ki67 on CTLs trended towards a positive correlation.

CONCLUSIONS

Adjuvant DCBI after CRS-HIPEC in patients with MPM was feasible and safe, and showed promising survival outcomes. DCBI had an immune modulatory effect on lymphoid cells and induced memory T-cell activation. Moreover, an increase of CD8+ Temra cells was more pronounced in patients with longer PFS. These data provide rationale for future combination treatment strategies.

TRIAL REGISTRATION NUMBER

NTR7060; Dutch Trial Register (NTR).

Interleukin-23 Regulates Inflammatory Osteoclastogenesis via Activation of CLEC5A(+) Osteoclast Precursors

OBJECTIVE

To investigate the role of interleukin-23 (IL-23) in pathologic bone remodeling in inflammatory arthritis.

METHODS

In this study we investigated the role of IL-23 in osteoclast differentiation and activation using in vivo gene transfer techniques in wild-type and myeloid DNAX-activation protein 12-associating lectin-1 (MDL-1)-deficient mice, and by performing in vitro and in vivo osteoclastogenesis assays using spectral flow cytometry, micro-computed tomography analysis, Western blotting, and immunoprecipitation.

RESULTS

Herein, we show that IL-23 induces the expansion of a myeloid osteoclast precursor population and supports osteoclastogenesis and bone resorption in inflammatory arthritis. Genetic ablation of C-type lectin domain family member 5A, also known as MDL-1, prevents the induction of osteoclast precursors by IL-23 that is associated with bone destruction, as commonly observed in inflammatory arthritis. Moreover, osteoclasts derived from the bone marrow of MDL-1-deficient mice showed impaired osteoclastogenesis, and MDL-1-/- mice had increased bone mineral density.

CONCLUSION

Our data show that IL-23 signaling regulates the availability of osteoclast precursors in inflammatory arthritis that could be effectively targeted for the treatment of inflammatory bone loss in inflammatory arthritis.

Regulation of the programmed cell death protein 1/programmed cell death ligand 1 axis in relapsing-remitting multiple sclerosis

The programmed cell death protein 1/programmed cell death ligand 1 axis plays an important role in the adaptive immune system and has influence on neoplastic and inflammatory diseases, while its role in multiple sclerosis is unclear. Here, we aimed to analyse expression patterns of programmed cell death protein 1 and programmed cell death ligand 1 on peripheral blood mononuclear cells and their soluble variants in multiple sclerosis patients and controls, to determine their correlation with clinical disability and disease activity. In a cross-sectional study, we performed in-depth flow cytometric immunophenotyping of peripheral blood mononuclear cells and analysed soluble programmed cell death protein 1 and programmed cell death ligand 1 serum levels in patients with relapsing-remitting multiple sclerosis and controls. In comparison to control subjects, relapsing-remitting multiple sclerosis patients displayed distinct cellular programmed cell death protein 1/programmed cell death ligand 1 expression patterns in immune cell subsets and increased soluble programmed cell death ligand 1 levels, which correlated with clinical measures of disability and MRI activity over time. This study extends our knowledge of how programmed cell death protein 1 and programmed cell death ligand 1 are expressed in the membranes of patients with relapsing-remitting multiple sclerosis and describes for the first time the elevation of soluble programmed cell death ligand 1 in the blood of multiple sclerosis patients. The distinct expression pattern of membrane-bound programmed cell death protein 1 and programmed cell death ligand 1 and the correlation between soluble programmed cell death ligand 1, membrane-bound programmed cell death ligand 1, disease and clinical factors may offer therapeutic potential in the setting of multiple sclerosis and might improve future diagnosis and clinical decision-making.

Flow Cytometry: The Next Revolution

Unmasking the subtleties of the immune system requires both a comprehensive knowledge base and the ability to interrogate that system with intimate sensitivity. That task, to a considerable extent, has been handled by an iterative expansion in flow cytometry methods, both in technological capability and also in accompanying advances in informatics. As the field of fluorescence-based cytomics matured, it reached a technological barrier at around 30 parameter analyses, which stalled the field until spectral flow cytometry created a fundamental transformation that will likely lead to the potential of 100 simultaneous parameter analyses within a few years. The simultaneous advance in informatics has now become a watershed moment for the field as it competes with mature systematic approaches such as genomics and proteomics, allowing cytomics to take a seat at the multi-omics table. In addition, recent technological advances try to combine the speed of flow systems with other detection methods, in addition to fluorescence alone, which will make flow-based instruments even more indispensable in any biological laboratory. This paper outlines current approaches in cell analysis and detection methods, discusses traditional and microfluidic sorting approaches as well as next-generation instruments, and provides an early look at future opportunities that are likely to arise.

Optimization of monocyte gating to quantify monocyte subsets for the diagnosis of chronic myelomonocytic leukemia

BACKGROUND

The presence of >94% classical monocytes (MO1, CD14++/CD16-) in peripheral blood (PB) has an excellent performance for the diagnosis of chronic myelomonocytic leukemia (CMML). However, the monocyte gating strategy is not well defined. The objective of the study was to compare monocyte gating strategies and propose an optimal one.

METHODS

This is a prospective, single center study assessing monocyte subsets in PB. First, we compared monocyte subsets using 13 monocyte gating strategies in 10 samples. Then we developed our own 10 color tube and tested it on 124 patients (normal white blood cell counts, reactive monocytosis, CMML and a spectrum of other myeloid malignancies). Both conventional and computational (FlowSOM) analyses were used.

RESULTS

Comparing different monocyte gating strategies, small but significant differences in %MO1 and percentually large differences in %MO3 (nonclassical monocytes) were found, suggesting that the monocyte gating strategy can impact monocyte subset quantification. Then, we designed a 10-color tube for this purpose (CD45/CD33/CD14/CD16/CD64/CD86/CD300/CD2/CD66c/CD56) and applied it to 124 patients. This tube allowed proper monocyte gating even in highly abnormal PB. Computational analysis found a higher %MO1 and lower %MO3 compared to conventional analysis. However, differences between conventional and computational analysis in both MO1 and MO3 were globally consistent and only minimal differences were observed when comparing the ranking of patients according to %MO1 or %MO3 obtained with the conventional versus the computational approach.

CONCLUSIONS

The choice of monocyte gating strategy appears relevant for the monocyte subset distribution test. Our 10-color proposal allowed satisfactory monocyte gating even in highly abnormal PB. Computational analysis seems promising to increase reproducibility in monocyte subset quantification.

Chronic antigen in solid tumors drives a distinct program of T cell residence

Analyses of healthy tissue reveal signatures that identify resident memory CD8+ T cells (TRM), which survey tissues without recirculating. The density of TRM phenotype cells within solid tumors correlates favorably with prognosis, suggesting that intratumoral residents control cancer. However, residence has not been directly tested, and intratumoral TRM phenotype cells could instead reflect aspects of the microenvironment that correlate with prognosis. Using a breast cancer model in mice, we found that conventional TRM markers do not inform the tumor residence of either bystander or tumor-specific cells, which exhibit further distinct phenotypes in the tumor microenvironment and healthy mammary tissue. Rather, tumor-specific, stem progenitor CD8+ T cells migrate to tumors and become resident while acquiring select markers of exhaustion. These data indicate that tonic antigen stimulation and the tumor environment drive distinct programs of residence compared with healthy tissues and that tumor immunity is sustained by continued migration of tumor-specific stem cells.

The Effect of Lung Resection for NSCLC on Circulating Immune Cells: A Pilot Study

This pilot study sought to evaluate the circulating levels of immune cells, particularly regulatory T-cell (Treg) subsets, before and after lung resection for non-small cell lung cancer. Twenty-five patients consented and had specimens collected. Initially, peripheral blood of 21 patients was collected for circulating immune cell studies. Two of these patients were excluded due to technical issues, leaving 19 patients for the analyses of circulating immune cells. Standard gating and high-dimensional unsupervised clustering flow cytometry analyses were performed. The blood, tumors and lymph nodes were analyzed via single-cell RNA and TCR sequencing for Treg analyses in a total of five patients (including four additional patients from the initial 21 patients). Standard gating flow cytometry revealed a transient increase in neutrophils immediately following surgery, with a variable neutrophil-lymphocyte ratio and a stable CD4-CD8 ratio. Unexpectedly, the total Treg and Treg subsets did not change with surgery with standard gating in short- or long-term follow-up. Similarly, unsupervised clustering of Tregs revealed a dominant cluster that was stable perioperatively and long-term. Two small FoxP3hi clusters slightly increased following surgery. In the longer-term follow-up, these small FoxP3hi Treg clusters were not identified, indicating that they were likely a response to surgery. Single-cell sequencing demonstrated six CD4+FoxP3+ clusters among the blood, tumors and lymph nodes. These clusters had a variable expression of FoxP3, and several were mainly, or only, present in tumor and lymph node tissue. As such, serial monitoring of circulating Tregs may be informative, but not completely reflective of the Tregs present in the tumor microenvironment.

Exploring the Role of Spatial Confinement in Immune Cell Recruitment and Regeneration of Skin Wounds

Microporous annealed particle (MAP) scaffolds are injectable granular materials comprised of micron sized hydrogel particles (microgels). The diameter of these microgels directly determines the size of the interconnected void space between particles where infiltrating or encapsulated cells reside. This tunable porosity allows us to use MAP scaffolds to study the impact of spatial confinement (SC) on both cellular behaviors and the host response to biomaterials. Despite previous studies showing that pore size and SC influence cellular phenotypes, including mitigating the macrophage inflammatory response, there is still a gap in knowledge regarding how SC within a biomaterial modulates immune cell recruitment in vivo in wounds and implants. Thus, we studied the immune cell profile within confined and unconfined biomaterials using small (40 μm), medium (70 μm), and large (130 μm) diameter spherical microgels, respectively. We discovered that MAP scaffolds imparted regenerative wound healing with an IgG1-biased Th2 response. MAP scaffolds generated from 130 μm diameter microgels have a median pore size that can accommodate ∼40 µm diameter spheres induced a more balanced pro-regenerative macrophage response and better wound healing outcomes with more mature collagen regeneration and reduced levels of inflammation.

Clustering ensemble in scRNA-seq data analysis: Methods, applications and challenges

With the rapid development of single-cell RNA-sequencing techniques, various computational methods and tools were proposed to analyze these high-throughput data, which led to an accelerated reveal of potential biological information. As one of the core steps of single-cell transcriptome data analysis, clustering plays a crucial role in identifying cell types and interpreting cellular heterogeneity. However, the results generated by different clustering methods showed distinguishing, and those unstable partitions can affect the accuracy of the analysis to a certain extent. To overcome this challenge and obtain more accurate results, currently clustering ensemble is frequently applied to cluster analysis of single-cell transcriptome datasets, and the results generated by all clustering ensembles are nearly more reliable than those from most of the single clustering partitions. In this review, we summarize applications and challenges of the clustering ensemble method in single-cell transcriptome data analysis, and provide constructive thoughts and references for researchers in this field.

A third SARS-CoV-2 mRNA vaccine dose in people receiving hemodialysis overcomes B cell defects but elicits a skewed CD4+ T cell profile

Cellular immune defects associated with suboptimal responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA vaccination in people receiving hemodialysis (HD) are poorly understood. We longitudinally analyze antibody, B cell, CD4⁺, and CD8⁺ T cell vaccine responses in 27 HD patients and 26 low-risk control individuals (CIs). The first two doses elicit weaker B cell and CD8⁺ T cell responses in HD than in CI, while CD4⁺ T cell responses are quantitatively similar. In HD, a third dose robustly boosts B cell responses, leads to convergent CD8⁺ T cell responses, and enhances comparatively more T helper (T_H) immunity. Unsupervised clustering of single-cell features reveals phenotypic and functional shifts over time and between cohorts. The third dose attenuates some features of T_H cells in HD (tumor necrosis factor alpha [TNFα]/interleukin [IL]-2 skewing), while others (CCR6, CXCR6, programmed cell death protein 1 [PD-1], and HLA-DR overexpression) persist. Therefore, a third vaccine dose is critical to achieving robust multifaceted immunity in hemodialysis patients, although some distinct T_H characteristics endure.

Cyclone: an accessible pipeline to analyze, evaluate and optimize multiparametric cytometry data

In the past decade, high-dimensional single cell technologies have revolutionized basic and translational immunology research and are now a key element of the toolbox used by scientists to study the immune system. However, analysis of the data generated by these approaches often requires clustering algorithms and dimensionality reduction representation which are computationally intense and difficult to evaluate and optimize. Here we present Cyclone, an analysis pipeline integrating dimensionality reduction, clustering, evaluation and optimization of clustering resolution, and downstream visualization tools facilitating the analysis of a wide range of cytometry data. We benchmarked and validated Cyclone on mass cytometry (CyTOF), full spectrum fluorescence-based cytometry, and multiplexed immunofluorescence (IF) in a variety of biological contexts, including infectious diseases and cancer. In each instance, Cyclone not only recapitulates gold standard immune cell identification, but also enables the unsupervised identification of lymphocytes and mononuclear phagocytes subsets that are associated with distinct biological features. Altogether, the Cyclone pipeline is a versatile and accessible pipeline for performing, optimizing, and evaluating clustering on variety of cytometry datasets which will further power immunology research and provide a scaffold for biological discovery.

Artificial intelligence in clinical multiparameter flow cytometry and mass cytometry-key tools and progress

There are many research studies and emerging tools using artificial intelligence (AI) and machine learning to augment flow and mass cytometry workflows. Emerging AI tools can quickly identify common cell populations with continuous improvement of accuracy, uncover patterns in high-dimensional cytometric data that are undetectable by human analysis, facilitate the discovery of cell subpopulations, perform semi-automated immune cell profiling, and demonstrate potential to automate aspects of clinical multiparameter flow cytometric (MFC) diagnostic workflow. Utilizing AI in the analysis of cytometry samples can reduce subjective variability and assist in breakthroughs in understanding diseases. Here we review the diverse types of AI that are being applied to clinical cytometry data and how AI is driving advances in data analysis to improve diagnostic sensitivity and accuracy. We review supervised and unsupervised clustering algorithms for cell population identification, various dimensionality reduction techniques, and their utilities in visualization and machine learning pipelines, and supervised learning approaches for classifying entire cytometry samples.Understanding the AI landscape will enable pathologists to better utilize open source and commercially available tools, plan exploratory research projects to characterize diseases, and work with machine learning and data scientists to implement clinical data analysis pipelines.

Intestinal location- and age-specific variation of intraepithelial T lymphocytes and mucosal microbiota in pigs

Intraepithelial T lymphocytes (T-IELs) are T cells located within the epithelium that provide a critical line of immune defense in the intestinal tract. In pigs, T-IEL abundances and phenotypes are used to infer putative T-IEL functions and vary by intestinal location and age, though investigations regarding porcine T-IELs are relatively limited. In this study, we expand on analyses of porcine intestinal T-IELs to include additional phenotypic designations not previously recognized in pigs. We describe non-conventional CD8α⁺CD8β^- αβ T-IELs that were most prevalent in the distal intestinal tract and primarily CD16⁺CD27^-, a phenotype suggestive of innate-like activation and an activated cell state. Additional T-IEL populations included CD8α⁺CD8β⁺ αβ, CD2⁺CD8α⁺ γδ, and CD2⁺CD8α^- γδ T-IELs, with increasing proportions of CD16⁺CD27^- phenotype in the distal intestine. Thus, putative non-conventional, activated T-IELs were most abundant in the distal intestine within multiple γδ and αβ T-IEL populations. A comparison of T-IEL and respective mucosal microbial community structures across jejunum, ileum, and cecum of 5- and 7-week-old pigs revealed largest community differences were tissue-dependent for both T-IELs and the microbiota. Between 5 and 7 weeks of age, the largest shifts in microbial community compositions occurred in the large intestine, while the largest shifts in T-IEL communities were in the small intestine. Therefore, results indicate different rates of community maturation and stabilization for porcine T-IELs and the mucosal microbiota for proximal versus distal intestinal locations between 5 and 7 weeks of age. Collectively, data emphasize the intestinal tract as a site of location- and age-specific T-IEL and microbial communities that have important implications for understanding intestinal health in pigs.

Whole-Transcriptome Sequencing Combined with High-Dimensional Proteomic Technologies Reveals the Potential Value of miR-135b-5p as a Biomarker for Hepatocellular Carcinoma

Purpose

Hepatocellular carcinoma (HCC) is a disease with great heterogeneity and a high mortality rate. It is crucial to identify reliable biomarkers for diagnosis, prognosis, and treatment to improve clinical outcomes in patients with HCC. Alpha-fetoprotein (AFP) is not only a widely used biomarker in clinical practice but also plays a complicated role in HCC, and it has recently been considered to be related to immunotherapy. MicroRNAs (miRNAs) are regarded as key regulators and promising biomarkers of HCC. We investigated the role of an AFP-related miRNA, miR-135b-5p, in HCC progression.

Methods

Identification of miR-135b-5p was performed based on a cohort of 65 HCC cases and the liver hepatocellular carcinoma cohort of The Cancer Genome Atlas (Asian people only). A combination of whole-transcriptome sequencing and high-dimensional proteomic technologies was used to study the role of miR-135b-5p in HCC.

Results

Upregulation of miR-135b-5p was detected in patients with HCC with high serum AFP levels (AFP > 400 ng/ml). Elevated miR-135b-5p expression was associated with adverse prognosis. We also identified the relevance between high miR-135b-5p expression and tumor-related pathological characteristics, such as Edmondson grade and vascular invasion. We revealed tyrosine kinase nonreceptor 1 as a potential target of miR-135b-5p. Additionally, the transcriptional start site of miR-135b-5p had potential binding sites for SRY-box transcription factor 9, and the stemness properties of tumor cells were more remarkable in HCC with the upregulation of miR-135b-5p. The molecular characterization of the miR-135b-5p-high group was similar to that of the HCC subclasses containing moderately and poorly differentiated tumors. Finally, gene signatures associated with improved clinical outcomes in immune checkpoint inhibitor therapy were upregulated in the miR-135b-5p-high group.

Conclusion

miR-135b-5p could be a biomarker for predicting the prognosis and antiprogrammed cell death protein 1 monotherapy response in HCC.