Immunophenotyping by Mass Cytometry

Best practices for user consultation in flow cytometry shared resource laboratories

This "Best Practices in User Consultation" article is the result of a 2022 International Society for the Advancement of Cytometry (ISAC) membership survey that collected valuable insights from the shared research laboratory (SRL) community and of a group discussion at the CYTO 2022 workshop of the same name. One key takeaway is the importance of initiating a consultation at the outset of a flow cytometry project, particularly for trainees. This approach enables the improvement and standardization of every step, from planning experiments to interpreting data. This proactive approach effectively mitigates experimental bias and avoids superfluous trial and error, thereby conserving valuable time and resources. In addition to guidelines, the optimal approaches for user consultation specify communication channels, methods, and critical information, thereby establishing a structure for productive correspondence between SRL and users. This framework functions as an exemplar for establishing robust and autonomous collaborative relationships. User consultation adds value by providing researchers with the necessary information to conduct reproducible flow cytometry experiments that adhere to scientific rigor. By following the steps, instructions, and strategies outlined in these best practices, an SRL can readily tailor them to its own setting, establishing a personalized workflow and formalizing user consultation services. This article provides a pragmatic guide for improving the caliber and efficacy of flow cytometry research and aggregates the flow cytometry SRL community's collective knowledge regarding user consultation.

Validation of Artificial Intelligence (AI)-Assisted Flow Cytometry Analysis for Immunological Disorders

Flow cytometry is a vital diagnostic tool for hematologic and immunologic disorders, but manual analysis is prone to variation and time-consuming. Over the last decade, artificial intelligence (AI) has advanced significantly. In this study, we developed and validated an AI-assisted flow cytometry workflow using 379 clinical cases from 2021, employing a 3-tube, 10-color flow panel with 21 antibodies for primary immunodeficiency diseases and related immunological disorders. The AI software (DeepFlow™, version 2.1.1) is fully automated, reducing analysis time to under 5 min per case. It interacts with hematopatholoists for manual gating adjustments when necessary. Using proprietary multidimensional density-phenotype coupling algorithm, the AI model accurately classifies and enumerates T, B, and NK cells, along with important immune cell subsets, including CD4+ helper T cells, CD8+ cytotoxic T cells, CD3+/CD4-/CD8- double-negative T cells, and class-switched or non-switched B cells. Compared to manual analysis with hematopathologist-determined lymphocyte subset percentages as the gold standard, the AI model exhibited a strong correlation (r > 0.9) across lymphocyte subsets. This study highlights the accuracy and efficiency of AI-assisted flow cytometry in diagnosing immunological disorders in a clinical setting, providing a transformative approach within a concise timeframe.

A biology-driven deep generative model for cell-type annotation in cytometry

Cytometry enables precise single-cell phenotyping within heterogeneous populations. These cell types are traditionally annotated via manual gating, but this method lacks reproducibility and sensitivity to batch effect. Also, the most recent cytometers-spectral flow or mass cytometers-create rich and high-dimensional data whose analysis via manual gating becomes challenging and time-consuming. To tackle these limitations, we introduce Scyan https://github.com/MICS-Lab/scyan, a Single-cell Cytometry Annotation Network that automatically annotates cell types using only prior expert knowledge about the cytometry panel. For this, it uses a normalizing flow-a type of deep generative model-that maps protein expressions into a biologically relevant latent space. We demonstrate that Scyan significantly outperforms the related state-of-the-art models on multiple public datasets while being faster and interpretable. In addition, Scyan overcomes several complementary tasks, such as batch-effect correction, debarcoding and population discovery. Overall, this model accelerates and eases cell population characterization, quantification and discovery in cytometry.

Mass Cytometry as a Tool for Investigating Senescence in Multiple Model Systems

Cellular senescence is a durable cell cycle arrest as a result of the finite proliferative capacity of cells. Senescence responds to both intrinsic and extrinsic cellular stresses, such as aging, mitochondrial dysfunction, irradiation, and chemotherapy. Here, we report on the use of mass cytometry (MC) to analyze multiple model systems and demonstrate MC as a platform for senescence analysis at the single-cell level. We demonstrate changes to p16 expression, cell cycling fraction, and histone tail modifications in several established senescent model systems and using isolated human T cells. In bone marrow mesenchymal stromal cells (BMSCs), we show increased p16 expression with subsequent passage as well as a reduction in cycling cells and open chromatin marks. In WI-38 cells, we demonstrate increased p16 expression with both culture-induced senescence and oxidative stress-induced senescence (OSIS). We also use Wanderlust, a trajectory analysis tool, to demonstrate how p16 expression changes with histone tail modifications and cell cycle proteins. Finally, we demonstrate that repetitive stimulation of human T cells with CD3/CD28 beads induces an exhausted phenotype with increased p16 expression. This p16-expressing population exhibited higher expression of exhaustion markers such as EOMES and TOX. This work demonstrates that MC is a useful platform for studying senescence at a single-cell protein level, and is capable of measuring multiple markers of senescence at once with high confidence, thereby improving our understanding of senescent pathways.

Moving beyond DNA: towards functional analysis of the vaginal microbiome by non-sequencing-based methods

Over the last two decades, sequencing-based methods have revolutionised our understanding of niche-specific microbial complexity. In the lower female reproductive tract, these approaches have enabled identification of bacterial compositional structures associated with health and disease. Application of metagenomics and metatranscriptomics strategies have provided insight into the putative function of these communities but it is increasingly clear that direct measures of microbial and host cell function are required to understand the contribution of microbe-host interactions to pathophysiology. Here we explore and discuss current methods and approaches, many of which rely upon mass-spectrometry, being used to capture functional insight into the vaginal mucosal interface. In addition to improving mechanistic understanding, these methods offer innovative solutions for the development of diagnostic and therapeutic strategies designed to improve women's health.

Performance of spectral flow cytometry and mass cytometry for the study of innate myeloid cell populations

Introduction

Monitoring of innate myeloid cells (IMC) is broadly applied in basic and translational research, as well as in diagnostic patient care. Due to their immunophenotypic heterogeneity and biological plasticity, analysis of IMC populations typically requires large panels of markers. Currently, two cytometry-based techniques allow for the simultaneous detection of ≥40 markers: spectral flow cytometry (SFC) and mass cytometry (MC). However, little is known about the comparability of SFC and MC in studying IMC populations.

Methods

We evaluated the performance of two SFC and MC panels, which contained 21 common markers, for the identification and subsetting of blood IMC populations. Based on unsupervised clustering analysis, we systematically identified 24 leukocyte populations, including 21 IMC subsets, regardless of the cytometry technique.

Results

Overall, comparable results were observed between the two technologies regarding the relative distribution of these cell populations and the staining resolution of individual markers (Pearson's ρ=0.99 and 0.55, respectively). However, minor differences were observed between the two techniques regarding intra-measurement variability (median coefficient of variation of 42.5% vs. 68.0% in SFC and MC, respectively; p<0.0001) and reproducibility, which were most likely due to the significantly longer acquisition times (median 16 min vs. 159 min) and lower recovery rates (median 53.1% vs. 26.8%) associated with SFC vs. MC.

Discussion

Altogether, our results show a good correlation between SFC and MC for the identification, enumeration and characterization of IMC in blood, based on large panels (>20) of antibody reagents.

Single-Cell Analysis in Immuno-Oncology

The complexity of the cellular and non-cellular milieu surrounding human tumors plays a decisive role in the course and outcome of disease. The high variability in the distribution of the immune and non-immune compartments within the tumor microenvironments (TME) among different patients governs the mode of their response or resistance to current immunotherapeutic approaches. Through deciphering this diversity, one can tailor patients' management to meet an individual's needs. Single-cell (sc) omics technologies have given a great boost towards this direction. This review gathers recent data about how multi-omics profiling, including the utilization of single-cell RNA sequencing (scRNA-seq), assay for transposase-accessible chromatin with sequencing (scATAC-seq), T-cell receptor sequencing (scTCR-seq), mass, tissue-based, or microfluidics cytometry, and related bioinformatics tools, contributes to the high-throughput assessment of a large number of analytes at single-cell resolution. Unravelling the exact TCR clonotype of the infiltrating T cells or pinpointing the classical or novel immune checkpoints across various cell subsets of the TME provide a boost to our comprehension of adaptive immune responses, their antigen specificity and dynamics, and grant suggestions for possible therapeutic targets. Future steps are expected to merge high-dimensional data with tissue localization data, which can serve the investigation of novel multi-modal biomarkers for the selection and/or monitoring of the optimal treatment from the current anti-cancer immunotherapeutic armamentarium.

Fiber-Type Shifting in Sarcopenia of Old Age: Proteomic Profiling of the Contractile Apparatus of Skeletal Muscles

The progressive loss of skeletal muscle mass and concomitant reduction in contractile strength plays a central role in frailty syndrome. Age-related neuronal impairments are closely associated with sarcopenia in the elderly, which is characterized by severe muscular atrophy that can considerably lessen the overall quality of life at old age. Mass-spectrometry-based proteomic surveys of senescent human skeletal muscles, as well as animal models of sarcopenia, have decisively improved our understanding of the molecular and cellular consequences of muscular atrophy and associated fiber-type shifting during aging. This review outlines the mass spectrometric identification of proteome-wide changes in atrophying skeletal muscles, with a focus on contractile proteins as potential markers of changes in fiber-type distribution patterns. The observed trend of fast-to-slow transitions in individual human skeletal muscles during the aging process is most likely linked to a preferential susceptibility of fast-twitching muscle fibers to muscular atrophy. Studies with senescent animal models, including mostly aged rodent skeletal muscles, have confirmed fiber-type shifting. The proteomic analysis of fast versus slow isoforms of key contractile proteins, such as myosin heavy chains, myosin light chains, actins, troponins and tropomyosins, suggests them as suitable bioanalytical tools of fiber-type transitions during aging.

Aberrant signaling of immune cells in Sjögren’s syndrome patient subgroups upon interferon stimulation

Background

Primary Sjögren’s syndrome (pSS) is a systemic autoimmune disease, characterized by mononuclear cell infiltrates in the salivary and lacrimal glands, leading to glandular atrophy and dryness. Patient heterogeneity and lack of knowledge regarding its pathogenesis makes pSS a difficult disease to manage.

Methods

An exploratory analysis using mass cytometry was conducted of MAPK/ERK and JAK/STAT signaling pathways in peripheral blood mononuclear cells (PBMC) from 16 female medication free pSS patients (8 anti-Sjögren’s syndrome-related antigen A negative/SSA- and 8 SSA+) and 8 female age-matched healthy donors after stimulation with interferons (IFNs).

Results

We found significant differences in the frequencies of memory B cells, CD8+ T central and effector memory cells and terminally differentiated CD4+ T cells among the healthy donors and patient subgroups. In addition, we observed an upregulation of HLA-DR and CD38 in many cell subsets in the patients. Upon IFNα2b stimulation, slightly increased signaling through pSTAT1 Y701 was observed in most cell types in pSS patients compared to controls, while phosphorylation of STAT3 Y705 and STAT5 Y694 were slightly reduced. IFNγ stimulation resulted in significantly increased pSTAT1 Y701 induction in conventional dendritic cells (cDCs) and classical and non-classical monocytes in the patients. Most of the observed differences were more prominent in the SSA+ subgroup, indicating greater disease severity in them.

Conclusions

Augmented activation status of certain cell types along with potentiated pSTAT1 Y701 signaling and reduced pSTAT3 Y705 and pSTAT5 Y694 induction may predispose pSS patients, especially the SSA+ subgroup, to upregulated expression of IFN-induced genes and production of autoantibodies. These patients may benefit from therapies targeting these pathways.

PP2A is a therapeutically targetable driver of cell fate decisions via a c-Myc/p21 axis in human and murine acute myeloid leukemia

Dysregulated cellular differentiation is a hallmark of acute leukemogenesis. Phosphatases are widely suppressed in cancers but have not been traditionally associated with differentiation. In this study, we found that the silencing of protein phosphatase 2A (PP2A) directly blocks differentiation in acute myeloid leukemia (AML). Gene expression and mass cytometric profiling revealed that PP2A activation modulates cell cycle and transcriptional regulators that program terminal myeloid differentiation. Using a novel pharmacological agent, OSU-2S, in parallel with genetic approaches, we discovered that PP2A enforced c-Myc and p21 dependent terminal differentiation, proliferation arrest, and apoptosis in AML. Finally, we demonstrated that PP2A activation decreased leukemia-initiating stem cells, increased leukemic blast maturation, and improved overall survival in murine Tet2-/-Flt3ITD/WT and human cell-line derived xenograft AML models in vivo. Our findings identify the PP2A/c-Myc/p21 axis as a critical regulator of the differentiation/proliferation switch in AML that can be therapeutically targeted in malignancies with dysregulated maturation fate.

Pre-operative exercise therapy triggers anti-inflammatory trained immunity of Kupffer cells through metabolic reprogramming

Pre-operative exercise therapy improves outcomes for many patients who undergo surgery. Despite the well-known effects on tolerance to systemic perturbation, the mechanisms by which pre-operative exercise protects the organ that is operated on from inflammatory injury are unclear. Here, we show that four-week aerobic pre-operative exercise significantly attenuates liver injury and inflammation from ischaemia and reperfusion in mice. Remarkably, these beneficial effects last for seven more days after completing pre-operative exercising. We find that exercise specifically drives Kupffer cells toward an anti-inflammatory phenotype with trained immunity via metabolic reprogramming. Mechanistically, exercise-induced HMGB1 release enhances itaconate metabolism in the tricarboxylic acid cycle that impacts Kupffer cells in an NRF2-dependent manner. Therefore, these metabolites and cellular/molecular targets can be investigated as potential exercise-mimicking pharmaceutical candidates to protect against liver injury during surgery.

Mass Cytometry, Imaging Mass Cytometry, and Multiplexed Ion Beam Imaging Use in a Clinical Setting

Mass cytometry (MC), imaging mass cytometry (IMC), and multiplexed ion beam imaging (MIBI) represent a new generation of tools to understand increasingly complex systems. Although these technologies differ in their intended applications, with MC being most similar to flow cytometry, and IMC/MIBI being similar to immunohistochemistry, they all share a time of flight mass spectrometry (TOF MS) platform. These TOF MS platforms use metal conjugated antibodies as opposed to fluorophores, increasing the measurable parameters up to approximately 50 with a theoretic limit approximately 100 parameters. These tools are being adapted to understand highly complex systems in basic and clinical research.

Alternative methods of viability determination in single cell mass cytometry

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.

Gene Expression and Resistance to Glucocorticoid-Induced Apoptosis in Acute Lymphoblastic Leukemia: A Brief Review and Update

BACKGROUND

Resistance to glucocorticoid (GC)-induced apoptosis in Acute Lymphoblastic Leukemia (ALL), is considered one of the major prognostic factors for the disease. Prednisolone is a corticosteroid and one of the most important agents in the treatment of acute lymphoblastic leukemia. The mechanics of GC resistance are largely unknown and intense ongoing research focuses on this topic.

AIM

The aim of the present study is to review some aspects of GC resistance in ALL, and in particular of Prednisolone, with emphasis on previous and present knowledge on gene expression and signaling pathways playing a role in the phenomenon.

METHODS

An electronic literature search was conducted by the authors from 1994 to June 2019. Original articles and systematic reviews selected, and the titles and abstracts of papers screened to determine whether they met the eligibility criteria, and full texts of the selected articles were retrieved.

RESULTS

Identification of gene targets responsible for glucocorticoid resistance may allow discovery of drugs, which in combination with glucocorticoids may increase the effectiveness of anti-leukemia therapies. The inherent plasticity of clinically evolving cancer justifies approaches to characterize and prevent undesirable activation of early oncogenic pathways.

CONCLUSION

Study of the pattern of intracellular signal pathway activation by anticancer drugs can lead to development of efficient treatment strategies by reducing detrimental secondary effects.

Towards a Systems Immunology Approach to Unravel Responses to Cancer Immunotherapy

Immunotherapy, particularly immune checkpoint blockade and chimeric antigen receptor (CAR)-T cells, holds a great promise against cancer. These treatments have markedly improved survival in solid as well as in hematologic tumors previously considered incurable. However, durable responses occur in a fraction of patients, and existing biomarkers (e.g. PD-L1) have shown limited prediction power. This scenario highlights the need to dissect the complex interplay between immune and tumor cells to identify reliable biomarkers of response to be used for patients’ selection. In this context, systems immunology represents indeed the new frontier to address important clinical challenges in biomarker discovery. Through the integration of multiple layers of data obtained with several high-throughput approaches, systems immunology may give insights on the vast range of inter-individual differences and on the influences of genes and factors that cooperatively shape the individual immune response to a given treatment. In this Mini Review, we give an overview of the current high-throughput methodologies, including genomics, epigenomics, transcriptomics, metabolomics, proteomics, and multi-parametric phenotyping suitable for systems immunology as well as on the key steps of data integration and biological interpretation. Additionally, we review recent studies in which multi-omics technologies have been used to characterize mechanisms of response and to identify powerful biomarkers of response to checkpoint inhibitors, CAR-T cell therapy, dendritic cell-based and peptide-based cancer vaccines. We also highlight the need of favoring the collaboration of researchers with complementary expertise and of integrating multi-omics data into biological networks with the final goal of developing accurate markers of therapeutic response.

Method for the Analysis of the Tumor Microenvironment by Mass Cytometry: Application to Chronic Lymphocytic Leukemia

In the past 20 years, the interest for the tumor microenvironment (TME) has exponentially increased. Indeed, it is now commonly admitted that the TME plays a crucial role in cancer development, maintenance, immune escape and resistance to therapy. This stands true for hematological malignancies as well. A considerable amount of newly developed therapies are directed against the cancer-supporting TME instead of targeting tumor cells themselves. However, the TME is often not clearly defined. In addition, the unique phenotype of each tumor and the variability among patients limit the success of such therapies. Recently, our group took advantage of the mass cytometry technology to unveil the specific TME in the context of chronic lymphocytic leukemia (CLL) in mice. We found the enrichment of LAG3 and PD1, two immune checkpoints. We tested an antibody-based immunotherapy, targeting these two molecules. This combination of antibodies was successful in the treatment of murine CLL. In this methods article, we provide a detailed protocol for the staining of CLL TME cells aiming at their characterization using mass cytometry. We include panel design and validation, sample preparation and acquisition, machine set-up, quality control, and analysis. Additionally, we discuss different advantages and pitfalls of this technique.

Current Challenges in Vaccinology

The development of vaccines, which prime the immune system to respond to future infections, has led to global declines in morbidity and mortality from dreadful infectious communicable diseases. However, many pathogens of public health importance are highly complex and/or rapidly evolving, posing unique challenges to vaccine development. Several of these challenges include an incomplete understanding of how immunity develops, host and pathogen genetic variability, and an increased societal skepticism regarding vaccine safety. In particular, new high-dimensional omics technologies, aided by bioinformatics, are driving new vaccine development (vaccinomics). Informed by recent insights into pathogen biology, host genetic diversity, and immunology, the increasing use of genomic approaches is leading to new models and understanding of host immune system responses that may provide solutions in the rapid development of novel vaccine candidates.

Phenotyping of tumor infiltrating immune cells using mass-cytometry (CyTOF)

The anti-tumor immune response plays a crucial role in cancer patient outcome as well as in response to the growing family of immunotherapeutic treatments. Improving patient prognostic and therapeutic management requires a better knowledge of the tumor microenvironment, for which a deep characterization of tumor-infiltrating immune populations is instrumental. Mass cytometry represents an excellent tool in tumor Immunology, as it allows the simultaneous analysis of >40 markers on single cells. In this chapter, we review challenging technical aspects of the mass cytometry phenotyping of tumor infiltrating immune cells, focusing on fresh human solid tumor samples. We first explain how to design mass cytometry experiments, then provide detailed protocols to isolate mononuclear immune cells from solid tissues and to stain them for an acquisition on a mass cytometer. We also discuss how to optimize the preparation of single immune cell samples, and how to ensure the reproducibility of data generated from distinct fresh human samples. Finally, we provide troubleshooting suggestions for difficult sample acquisitions on a mass cytometer.