CyTOF Measurement of Immunocompetence Across Major Immune Cell Types

Identification of immune subsets with distinct lectin binding signatures using multi-parameter flow cytometry: correlations with disease activity in systemic lupus erythematosus

Objectives

Cell surface glycosylation can influence protein-protein interactions with particular relevance to changes in core fucosylation and terminal sialylation. Glycans are ligands for immune regulatory lectin families like galectins (Gals) or sialic acid immunoglobulin-like lectins (Siglecs). This study delves into the glycan alterations within immune subsets of systemic lupus erythematosus (SLE).

Methods

Evaluation of binding affinities of Galectin-1, Galectin-3, Siglec-1, Aleuria aurantia lectin (AAL, recognizing core fucosylation), and Sambucus nigra agglutinin (SNA, specific for α-2,6-sialylation) was conducted on various immune subsets in peripheral blood mononuclear cells (PBMCs) from control and SLE subjects. Lectin binding was measured by multi-parameter flow cytometry in 18 manually gated subsets of T-cells, NK-cells, NKT-cells, B-cells, and monocytes in unstimulated resting state and also after 3-day activation. Stimulated pre-gated populations were subsequently clustered by FlowSOM algorithm based on lectin binding and activation markers, CD25 or HLA-DR.

Results

Elevated AAL, SNA and CD25+/CD25- SNA binding ratio in certain stimulated SLE T-cell subsets correlated with SLE Disease Activity Index 2000 (SLEDAI-2K) scores. The significantly increased frequencies of activated AALlow Siglec-1low NK metaclusters in SLE also correlated with SLEDAI-2K indices. In SLE, activated double negative NKTs displayed significantly lower core fucosylation and CD25+/CD25- Siglec-1 binding ratio, negatively correlating with disease activity. The significantly enhanced AAL binding in resting SLE plasmablasts positively correlated with SLEDAI-2K scores.

Conclusion

Alterations in the glycosylation of immune cells in SLE correlate with disease severity, which might represent potential implications in the pathogenesis of SLE.

Characterization of adipose depot-specific stromal cell populations by single-cell mass cytometry

The increased prevalence of obesity and metabolic diseases has heightened interest in adipose tissue biology and its potential as a therapeutic target. To better understand cellular heterogeneity and complexity of white adipose tissue (WAT), we employed cytometry by time-of-flight (CyTOF) to characterize immune and stromal cells in visceral and subcutaneous WAT depots under normal and high-fat diet feeding, by quantifying the expression levels of 32 surface marker proteins. We observed comparable proportions of immune cells in two WAT depots under steady state, but depot-distinct subtypes of adipose precursor cells (APC), suggesting differences in their adipogenic and fibrogenic potential. Furthermore, in addition to pro-inflammatory immune cell shifts, significant pro-fibrotic changes were observed in APCs under high-fat diet, suggesting that APCs are early responders to dietary challenges. We propose CyTOF as a complementary and alternative tool to current high-throughput single-cell transcriptomic analyses to better understand the function and plasticity of adipose tissue.

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Application of CyTOF for cellular characterization in two adipose depots

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Adipose depot-distinct APC subpopulations

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APCs are early responders under obesogenic conditions to regulate WAT fibrosis

Cutting-Edge Platforms for Analysis of Immune Cells in the Hepatic Microenvironment-Focus on Tumor-Associated Macrophages in Hepatocellular Carcinoma

The role of tumor-associated macrophages (TAMs) in the pathogenesis of hepatocellular carcinoma (HCC) is poorly understood. Most studies rely on platforms that remove intrahepatic macrophages from the microenvironment prior to evaluation. Cell isolation causes activation and phenotypic changes that may not represent their actual biology and function in situ. State-of-the-art methods provides new strategies to study TAMs without losing the context of tissue architecture and spatial relationship with neighboring cells. These technologies, such as multispectral imaging (e.g., Vectra Polaris), mass cytometry by time-of-flight (e.g., Fluidigm CyTOF), cycling of fluorochromes (e.g., Akoya Biosciences CODEX/PhenoCycler-Fusion, Bruker Canopy, Lunaphore Comet, and CyCIF) and digital spatial profiling or transcriptomics (e.g., GeoMx or Visium, Vizgen Merscope) are being utilized to accurately assess the complex cellular network within the tissue microenvironment. In cancer research, these platforms enable characterization of immune cell phenotypes and expression of potential therapeutic targets, such as PDL-1 and CTLA-4. Newer spatial profiling platforms allow for detection of numerous protein targets, in combination with whole transcriptome analysis, in a single liver biopsy tissue section. Macrophages can also be specifically targeted and analyzed, enabling quantification of both protein and gene expression within specific cell phenotypes, including TAMs. This review describes the workflow of each platform, summarizes recent research using these approaches, and explains the advantages and limitations of each.

Systems-based approaches to study immunometabolism

Technical advances at the interface of biology and computation, such as single-cell RNA-sequencing (scRNA-seq), reveal new layers of complexity in cellular systems. An emerging area of investigation using the systems biology approach is the study of the metabolism of immune cells. The diverse spectra of immune cell phenotypes, sparsity of immune cell numbers in vivo, limitations in the number of metabolites identified, dynamic nature of cellular metabolism and metabolic fluxes, tissue specificity, and high dependence on the local milieu make investigations in immunometabolism challenging, especially at the single-cell level. In this review, we define the systemic nature of immunometabolism, summarize cell- and system-based approaches, and introduce mathematical modeling approaches for systems interrogation of metabolic changes in immune cells. We close the review by discussing the applications and shortcomings of metabolic modeling techniques. With systems-oriented studies of metabolism expected to become a mainstay of immunological research, an understanding of current approaches toward systems immunometabolism will help investigators make the best use of current resources and push the boundaries of the discipline.

Biomimetic Scaffolds Modulate the Posttraumatic Inflammatory Response in Articular Cartilage Contributing to Enhanced Neoformation of Cartilaginous Tissue In Vivo

Focal chondral lesions of the knee are the most frequent type of trauma in younger patients and are associated with a high risk of developing early posttraumatic osteoarthritis. The only current clinical solutions include microfracture, osteochondral grafting, and autologous chondrocyte implantation. Cartilage tissue engineering based on biomimetic scaffolds has become an appealing strategy to repair cartilage defects. Here, a chondrogenic collagen-chondroitin sulfate scaffold is tested in an orthotopic Lapine in vivo model to understand the beneficial effects of the immunomodulatory biomaterial on the full chondral defect. Using a combination of noninvasive imaging techniques, histological and whole transcriptome analysis, the scaffolds are shown to enhance the formation of cartilaginous tissue and suppression of host cartilage degeneration, while also supporting tissue integration and increased tissue regeneration over a 12 weeks recovery period. The results presented suggest that biomimetic materials could be a clinical solution for cartilage tissue repair, due to their ability to modulate the immune environment in favor of regenerative processes and suppression of cartilage degeneration.

Immune profiling of COVID-19: preliminary findings and implications for the pandemic

SARS-CoV-2 infection can have widely diverse clinical outcomes, from asymptomatic infection to death, with many possible clinical symptoms and syndromes. It is thus essential to understand how the virus interacts with the host immune system to bring about these varied outcomes and to inform vaccine development. We now know that both antibody and T cell responses are induced in the majority of infected individuals, and that cross-reactive responses from other coronaviruses also exist in the uninfected population. Innate immune responses are a key focus of research and may influence the course of disease and the character of subsequent adaptive responses. Finally, baseline immune profiles and changes during early acute infection may be key to predicting the course of disease. Understanding all these aspects can help to create better immune monitoring tools for COVID-19, including tools for predicting disease severity or specific sequelae, perhaps even prior to infection.

The Multiple Potential Biomarkers for Predicting Immunotherapy Response-Finding the Needle in the Haystack

Immune checkpoint inhibitors (ICIs) are being increasingly utilised in a variety of advanced malignancies. Despite promising outcomes in certain patients, the majority will not derive benefit and are at risk of potentially serious immune-related adverse events (irAEs). The development of predictive biomarkers is therefore critical to personalise treatments and improve outcomes. A number of biomarkers have shown promising results, including from tumour (programmed cell death ligand 1 (PD-L1), tumour mutational burden (TMB), stimulator of interferon genes (STING) and apoptosis-associated speck-like protein containing a CARD (ASC)), from blood (peripheral blood mononuclear cells (PBMCs), circulating tumour DNA (ctDNA), exosomes, cytokines and metal chelators) and finally the microbiome.

Mass Cytometry Defines Virus-Specific CD4+ T Cells in Influenza Vaccination

The antiviral response to influenza virus is complex and multifaceted, involving many immune cell subsets. There is an urgent need to understand the role of CD4⁺ T cells, which orchestrate an effective antiviral response, to improve vaccine design strategies. In this study, we analyzed PBMCs from human participants immunized with influenza vaccine, using high-dimensional single-cell proteomic immune profiling by mass cytometry. Data were analyzed using a novel clustering algorithm, denoised ragged pruning, to define possible influenza virus–specific clusters of CD4⁺ T cells. Denoised ragged pruning identified six clusters of cells. Among these, one cluster (Cluster 3) was found to increase in abundance following stimulation with influenza virus peptide ex vivo. A separate cluster (Cluster 4) was found to expand in abundance between days 0 and 7 postvaccination, indicating that it is vaccine responsive. We examined the expression profiles of all six clusters to characterize their lineage, functionality, and possible role in the response to influenza vaccine. Clusters 3 and 4 consisted of effector memory cells, with high CD154 expression. Cluster 3 expressed cytokines like IL-2, IFN-γ, and TNF-α, whereas Cluster 4 expressed IL-17. Interestingly, some participants had low abundance of Clusters 3 and 4, whereas others had higher abundance of one of these clusters compared with the other. Taken together, we present an approach for identifying novel influenza virus–reactive CD4⁺ T cell subsets, a method that could help advance understanding of the immune response to influenza, predict responsiveness to vaccines, and aid in better vaccine design.

Pembrolizumab in Relapsed and Refractory Mycosis Fungoides and Sézary Syndrome: A Multicenter Phase II Study

PURPOSE

To assess the efficacy of pembrolizumab in patients with advanced relapsed or refractory mycosis fungoides (MF) or Sézary syndrome (SS).

PATIENTS AND METHODS

CITN-10 is a single-arm, multicenter phase II trial of 24 patients with advanced MF or SS. Patients were treated with pembrolizumab 2 mg/kg every 3 weeks for up to 24 months. The primary end point was overall response rate by consensus global response criteria.

RESULTS

Patients had advanced-stage disease (23 of 24 with stage IIB to IV MF/SS) and were heavily pretreated with a median of four prior systemic therapies. The overall response rate was 38% with two complete responses and seven partial responses. Of the nine responding patients, six had 90% or more improvement in skin disease by modified Severity Weighted Assessment Tool, and eight had ongoing responses at last follow-up. The median duration of response was not reached, with a median response follow-up time of 58 weeks. Immune-related adverse events led to treatment discontinuation in four patients. A transient worsening of erythroderma and pruritus occurred in 53% of patients with SS. This cutaneous flare reaction did not result in treatment discontinuation for any patient. The flare reaction correlated with high PD-1 expression on Sézary cells but did not associate with subsequent clinical responses or lack of response. Treatment responses did not correlate with expression of PD-L1, total mutation burden, or an interferon-γ gene expression signature.

CONCLUSION

Pembrolizumab demonstrated significant antitumor activity with durable responses and a favorable safety profile in patients with advanced MF/SS.

HLA Expression in Uveal Melanoma: An Indicator of Malignancy and a Modifiable Immunological Target

Uveal melanoma (UM) is the most common primary intraocular malignancy in adults, and gives rise to metastases in 50% of cases. The presence of an inflammatory phenotype is a well-known risk factor for the development of metastases. This inflammatory phenotype is characterized by the presence of high numbers of lymphocytes and macrophages, and a high expression of the HLA Class I and II antigens. An abnormal expression of HLA Class I may influence cytotoxic T lymphocyte (CTL) as well as Natural Killer (NK) cell responses. We provide a comprehensive review regarding the inflammatory phenotype in UM and the expression of locus- and allele-specific HLA Class I and of Class II antigens in primary UM and its metastases. Furthermore, we describe the known regulators and the role of genetics (especially chromosome 3 and BRCA-Associated Protein 1 (BAP1 status)), and, last but not least, the effect of putative therapeutic treatments on HLA expression.

The biology of the cell - insights from mass cytometry

In single-cell biology there is an ongoing push toward more and more comprehensive measurements made in individual cells. By combining measurements of proteins, mRNA, genetic, and epigenetic traits, in contexts of cell stimulation or drug treatment, novel single-cell analyses will help understand the determinants of cellular identity, differentiation decisions, and regulatory mechanisms governing cellular function in health and disease. Mass cytometry is a flexible methodology not only developed toward this aim, allowing analyses of cells in suspension such as blood but also extended for the analyses of tissue sections. Here, I will discuss the different measurements possible by mass cytometry and not only discuss its potential but also its limitations now and in the years to come.

Distinct predictive biomarker candidates for response to anti-CTLA-4 and anti-PD-1 immunotherapy in melanoma patients

BACKGROUND

While immune checkpoint blockade has greatly improved clinical outcomes in diseases such as melanoma, there remains a need for predictive biomarkers to determine who will likely benefit most from which therapy. To date, most biomarkers of response have been identified in the tumors themselves. Biomarkers that could be assessed from peripheral blood would be even more desirable, because of ease of access and reproducibility of sampling.

METHODS

We used mass cytometry (CyTOF) to comprehensively profile peripheral blood of melanoma patients, in order to find predictive biomarkers of response to anti-CTLA-4 or anti-PD-1 therapy. Using a panel of ~ 40 surface and intracellular markers, we performed in-depth phenotypic and functional immune profiling to identify potential predictive biomarker candidates.

RESULTS

Immune profiling of baseline peripheral blood samples using CyTOF revealed that anti-CTLA-4 and anti-PD-1 therapies have distinct sets of candidate biomarkers. The distribution of CD4+ and CD8+ memory/non-memory cells and other memory subsets was different between responders and non-responders to anti-CTLA-4 therapy. In anti-PD-1 (but not anti-CTLA-4) treated patients, we discovered differences in CD69 and MIP-1β expressing NK cells between responders and non-responders. Finally, multivariate analysis was used to develop a model for the prediction of response.

CONCLUSIONS

Our results indicate that anti-CTLA-4 and anti-PD-1 have distinct predictive biomarker candidates. CD4+ and CD8+ memory T cell subsets play an important role in response to anti-CTLA-4, and are potential biomarker candidates. For anti-PD-1 therapy, NK cell subsets (but not memory T cell subsets) correlated with clinical response to therapy. These functionally active NK cell subsets likely play a critical role in the anti-tumor response triggered by anti-PD-1.