Unbiased method for spectral analysis of cells with great diversity of autofluorescence spectra.

Autofluorescence is an intrinsic feature of cells, caused by the natural emission of light by photo-excitatory molecular content, which can complicate analysis of flow cytometry data. Different cell types have different autofluorescence spectra and, even within one cell type, heterogeneity of autofluorescence spectra can be present, for example, as a consequence of activation status or metabolic changes. By using full spectrum flow cytometry, the emission spectrum of a fluorochrome is captured by a set of photo detectors across a range of wavelengths, creating an unique signature for that fluorochrome. This signature is then used to identify, or unmix, that fluorochrome's unique spectrum from a multicolor sample containing different fluorescent molecules. Importantly, this means that this technology can also be used to identify intrinsic autofluorescence signal of an unstained sample, which can be used for unmixing purposes and to separate the autofluorescence signal from the fluorophore signals. However, this only works if the sample has a singular, relatively homogeneous and bright autofluorescence spectrum. To analyze samples with heterogeneous autofluorescence spectral profiles, we setup an unbiased workflow to more quickly identify differing autofluorescence spectra present in a sample to include as "autofluorescence signatures" during the unmixing of the full stained samples. First, clusters of cells with similar autofluorescence spectra are identified by unbiased dimensional reduction and clustering of unstained cells. Then, unique autofluorescence clusters are determined and are used to improve the unmixing accuracy of the full stained sample. Independent of the intensity of the autofluorescence and immunophenotyping of cell subsets, this unbiased method allows for the identification of most of the distinct autofluorescence spectra present in a sample, leading to less confounding autofluorescence spillover and spread into extrinsic phenotyping markers. Furthermore, this method is equally useful for spectral analysis of different biological samples, including tissue cell suspensions, peripheral blood mononuclear cells, and in vitro cultures of (primary) cells.

CPHEN-017: Comprehensive phenotyping of neutrophil extracellular traps (NETs) on peripheral human neutrophils.

With the recent discovery of their ability to produce neutrophil extracellular traps (NETs), neutrophils are increasingly appreciated as active participants in infection and inflammation. NETs are characterized as large, web-like networks of DNA and proteins extruded from neutrophils, and there is considerable interest in how these structures drive disease in humans. Advancing research in this field is contingent on developing novel tools for quantifying NETosis. To this end, we have developed a 7-marker flow cytometry panel for analyzing NETosis on human peripheral neutrophils following in vitro stimulation, and in fresh circulating neutrophils under inflammatory conditions. This panel was optimized on neutrophils isolated from whole blood and analyzed fresh or in vitro stimulated with phorbol 12-myristate 13-acetate (PMA) or ionomycin, two known NET-inducing agonists. Neutrophils were identified as SSChighFSChighCD15+CD66b+. Neutrophils positive for amine residues and 7-Aminoactinomycin D (7-AAD), our DNA dye of choice, were deemed necrotic (Zombie-NIR+7-AAD+) and were removed from downstream analysis. Exclusion of Zombie-NIR and positivity for 7-AAD (Zombie-NIRdim7-AAD+) was used here as a marker of neutrophil-appendant DNA, a key feature of NETs. The presence of two NET-associated proteins - myeloperoxidase (MPO) and neutrophil elastase (NE) - were utilized to identify neutrophil-appendant NET events (SSChighFSChighCD15+CD66b+Zombie NIRdim7-AAD+MPO+NE+). We also demonstrate that NETotic neutrophils express citrullinated histone H3 (H3cit), are concentration-dependently induced by in vitro PMA and ionomycin stimulation but are disassembled with DNase treatment, and are present in both chronic and acute inflammation. This 7-color flow cytometry panel provides a novel tool for examining NETosis in humans.

Circulating immune profile in granulomatosis with polyangiitis reveals distinct patterns related to disease activity.

Granulomatosis with polyangiitis (GPA) is an autoimmune disorder characterized by recurrent relapses that can cause severe tissue damage and life-threatening organ dysfunction. Multiple immune cells and cytokines/chemokines are involved in the different stages of the disease. Immune profiling of patients may be useful for tracking disease activity, however, reliable immune signatures for GPA activity are lacking. In this study, we examined circulating immune profiles in GPA patients during active and remission disease states to identify potential immune patterns associated with disease activity. The distribution and phenotypic characteristics of major circulating immune cells, and the profiles of circulating cytokines/chemokines, were studied on cryopreserved peripheral blood mononuclear cells from GPA patients (active, n = 20; remission, n = 20) and healthy controls (n = 20) leveraging a 40-color optimized multicolor immunofluorescence panel (OMIP-69) and in serum using a 46-plex Luminex multiplex assay, respectively. Deep phenotyping uncovered a distinct composition of major circulating immune cells in active GPA and GPA in remission, with the most significant findings emerging within the monocyte compartment. Our detailed analysis revealed circulating monocyte diversity beyond the conventional monocyte subsets. We identified eight classical monocyte populations, two intermediate monocyte populations, and one non-classical monocyte population. Notably, active GPA had a higher frequency of CD45RA+CCR5+CCR6-CCR7+/lowCD127-HLA-DR+CD2- classical monocytes and a lower frequency of CD45RA-CCR5-/lowCCR6-CCR7-CD127-HLA-DR+CD2+/- classical monocytes, which both strongly correlated with disease activity. Furthermore, serum levels of CXCL1, CXCL2, and CCL20, all linked to monocyte biology, were elevated in active GPA and correlated strongly with disease activity. These findings shed light on the circulating immune profile of GPA and may lead to immune signature profiles for assessing disease activity. Monocytes in particular may be studied further as potential markers for monitoring GPA.

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

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

OMIP-104: A 30-color spectral flow cytometry panel for comprehensive analysis of immune cell composition and macrophage subsets in mouse metabolic organs.

Obesity-induced chronic low-grade inflammation, also known as metaflammation, results from alterations of the immune response in metabolic organs and contributes to the development of fatty liver diseases and type 2 diabetes. The diversity of tissue-resident leukocytes involved in these metabolic dysfunctions warrants an in-depth immunophenotyping in order to elucidate disease etiology. Here, we present a 30-color, full spectrum flow cytometry panel, designed to (i) identify the major innate and adaptive immune cell subsets in murine liver and white adipose tissues and (ii) discriminate various tissue-specific myeloid subsets known to contribute to the development of metabolic dysfunctions. This panel notably allows for distinguishing embryonically-derived liver-resident Kupffer cells from newly recruited monocyte-derived macrophages and KCs. Furthermore, several adipose tissue macrophage (ATM) subsets, including perivascular macrophages, lipid-associated macrophages, and pro-inflammatory CD11c+ ATMs, can also be identified. Finally, the panel includes cell-surface markers that have been associated with metabolic activation of different macrophage and dendritic cell subsets. Altogether, our spectral flow cytometry panel allows for an extensive immunophenotyping of murine metabolic tissues, with a particular focus on metabolically-relevant myeloid cell subsets, and can easily be adjusted to include various new markers if needed.

Development of a customizable mouse backbone spectral flow cytometry panel to delineate immune cell populations in normal and tumor tissues.

Introduction: In vivo studies of cancer biology and assessment of therapeutic efficacy are critical to advancing cancer research and ultimately improving patient outcomes. Murine cancer models have proven to be an invaluable tool in pre-clinical studies. In this context, multi-parameter flow cytometry is a powerful method for elucidating the profile of immune cells within the tumor microenvironment and/or play a role in hematological diseases. However, designing an appropriate multi-parameter panel to comprehensively profile the increasing diversity of immune cells across different murine tissues can be extremely challenging. Methods: To address this issue, we designed a panel with 13 fixed markers that define the major immune populations -referred to as the backbone panel- that can be profiled in different tissues but with the option to incorporate up to seven additional fluorochromes, including any marker specific to the study in question. Results: This backbone panel maintains its resolution across different spectral flow cytometers and organs, both hematopoietic and non-hematopoietic, as well as tumors with complex immune microenvironments. Discussion: Having a robust backbone that can be easily customized with pre-validated drop-in fluorochromes saves time and resources and brings consistency and standardization, making it a versatile solution for immuno-oncology researchers. In addition, the approach presented here can serve as a guide to develop similar types of customizable backbone panels for different research questions requiring high-parameter flow cytometry panels.

An autologous ex vivo model for exploring patient-specific responses to viro-immunotherapy in glioblastoma.

Oncolytic virus (OV) clinical trials have demonstrated remarkable efficacy in subsets of patients with glioblastoma (GBM). However, the lack of tools to predict this response hinders the advancement of a more personalized application of OV therapy. In this study, we characterize an ex vivo co-culture system designed to examine the immune response to OV infection of patient-derived GBM neurospheres in the presence of autologous peripheral blood mononuclear cells (PBMCs). Co-culture conditions were optimized to retain viability and functionality of both tumor cells and PBMCs, effectively recapitulating the well-recognized immunosuppressive effects of GBM. Following OV infection, we observed elevated secretion of pro-inflammatory cytokines and chemokines, including interferon γ, tumor necrosis factor α, CXCL9, and CXCL10, and marked changes in immune cell activation markers. Importantly, OV treatment induced unique patient-specific immune responses. In summary, our co-culture platform presents an avenue for personalized screening of viro-immunotherapies in GBM, offering promise as a potential tool for future patient stratification in OV therapy.

Comprehensive analysis of lung macrophages and dendritic cells in two murine models of allergic airway inflammation reveals model- and subset-specific accumulation and phenotypic alterations.

Introduction: Allergic asthma has been mainly attributed to T helper type 2 (Th2) and proinflammatory responses but many cellular processes remain elusive. There is increasing evidence for distinct roles for macrophage and dendritic cell (DC) subsets in allergic airway inflammation (AAI). At the same time, there are various mouse models for allergic asthma that have been of utmost importance in identifying key inflammatory pathways in AAI but that differ in the allergen and/or route of sensitization. It is unclear whether and how the accumulation and activation of specialized macrophage and DC subsets depend on the experimental model chosen for analyses. Methods: In our study, we employed high-parameter spectral flow cytometry to comprehensively assess the accumulation and phenotypic alterations of different macrophage- and DC-subsets in the lung in an OVA- and an HDM-mediated mouse model of AAI. Results: We observed subset-specific as well as model-specific characteristics with respect to cell numbers and functional marker expression. Generally, alveolar as opposed to interstitial macrophages showed increased MHCII surface expression in AAI. Between the models, we observed significantly increased numbers of alveolar macrophages, CD103+ DC and CD11b+ DC in HDM-mediated AAI, concurrent with significantly increased airway interleukin-4 but decreased total serum IgE levels. Further, increased expression of CD80 and CD86 on DC was exclusively detected in HDM-mediated AAI. Discussion: Our study demonstrates a model-specific involvement of macrophage and DC subsets in AAI. It further highlights spectral flow cytometry as a valuable tool for their comprehensive analysis under inflammatory conditions in the lung.

Practical 10-Color T-Cell Panel for Phenotyping Diverse Populations Using Spectral Flow Cytometry: A Beginner's Guide.

Flow cytometry stands as the most employed high-throughput single-cell analysis technique, facilitating the profiling of remarkably diverse samples, such as blood, bone marrow and body fluids. In addition, it allows for the discrimination of diverse immune cell subsets, including infrequently encountered types like T regulatory cells and exhausted CD28Null T cells. However, analyzing rare immune cell subsets with conventional flow cytometry poses challenges stemming from factors like fluorophore overlap, compensation issues, and limited flexibility in fluorophore selection. Therefore, spectral flow cytometry offers advantages over traditional flow cytometry. It measures the full emission spectrum and then separates it to identify different fluorochromes. This enables the use of fluorochromes with significant overlap in a single test, allowing for the analysis of more protein markers. Following this, spectral technology employs precise calculations to separate individual fluorochromes, thereby enabling the detection and elimination of autofluorescent signals originating from cells within the entire emission spectrum. This capability is pivotal in achieving deep phenotyping of immune cells with the requisite sensitivity and resolution essential for monitoring the immune systems of patients with compromised immunity, such as cancer and autoimmune disorders. Additionally, it allows for the exploration of interactions between distinct immune subsets. In this context, we introduce an optimized protocol utilizing spectral flow cytometry for precise T-cell characterization and differentiation, encompassing the assessment of their activation states. Furthermore, this protocol extends its applicability to the identification of less common circulating T-cell populations, notably T-regulatory and CD28Null T cells, following autofluorescence correction within the spectrum. This protocol provides a set of steps and reagents for the surface and intracellular staining of human T cells using whole peripheral blood. The spectral-based design of this panel allows for its applicability to other spectral machines, providing a versatile and efficient tool for T-cell analysis. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Achieving optimal staining through effective antibody titration Basic Protocol 2: Single-cell staining Basic Protocol 3: Comprehensive panel staining post-titration and spectral library integration.

Modified cell trace violet proliferation assay preserves lymphocyte viability and allows spectral flow cytometry analysis.

In this study we describe three different methods for labeling T lymphocytes with cell trace violet (CTV), in order to track cell division in mouse and human cells, in both the in vitro and in vivo setting. We identified a modified method of CTV labeling that can be applied directly to either conventional or spectral flow cytometry, that maintained lymphocyte viability and function, yet minimized dye spill-over into other fluorochrome channels. Our optimized method for CTV labeling allowed us to identify up to eight cell divisions and the replication index for in vitro-stimulated mouse and human lymphocytes, and the co-expression of T-cell subset markers. Furthermore, the homeostatic trafficking, expansion and division of CTV-labeled congenic donor T cells could be detected using spectral cytometry, in an adoptive T-cell transfer mouse model. Our optimized CTV method can be applied to both in vitro and in vivo settings to examine the behavior and phenotype of activated T cells.

Brief research report: in-depth immunophenotyping reveals stability of CD19 CAR T-cells over time.

Variability or stability might have an impact on treatment success and toxicity of CD19 CAR T-cells. We conducted a prospective observational study of 12 patients treated with Tisagenlecleucel for CD19+ B-cell malignancies. Using a 31-color spectral flow cytometry panel, we analyzed differentiation stages and exhaustion markers of CAR T-cell subsets prior to CAR T-cell infusion and longitudinally during 6 months of follow-up. The majority of activation markers on CAR T-cells showed stable expression patterns over time and were not associated with response to therapy or toxicity. Unsupervised cluster analysis revealed an immune signature of CAR T-cell products associated with the development of immune cell-associated neurotoxicity syndrome. Warranting validation in an independent patient cohort, in-depth phenotyping of CAR T-cell products as well as longitudinal monitoring post cell transfer might become a valuable tool to increase efficacy and safety of CAR T-cell therapy.

Comparative assessment of cytometry by time-of-flight and full spectral flow cytometry based on a 33-color antibody panel.

Mass cytometry and full spectrum flow cytometry have recently emerged as new promising single cell proteomic analysis tools that can be exploited to decipher the extensive diversity of immune cell repertoires and their implication in human diseases. In this study, we evaluated the performance of mass cytometry against full spectrum flow cytometry using an identical 33-color antibody panel on four healthy individuals. Our data revealed an overall high concordance in the quantification of major immune cell populations between the two platforms using a semi-automated clustering approach. We further showed a strong correlation of cluster assignment when comparing manual and automated clustering. Both comparisons revealed minor disagreements in the quantification and assignment of rare cell subpopulations. Our study showed that both single cell proteomic technologies generate highly overlapping results and substantiate that the choice of technology is not a primary factor for successful biological assessment of cell profiles but must be considered in a broader design framework of clinical studies.

Detection of radiation-induced senescence by the Debacq-Chainiaux protocol: Improvements and upgrade in the detection of positive events.

Senescent cells are blocked in the cell cycle but remain metabolically active. These cells, once engaged in the senescence process, fail to initiate DNA replication. Due to the shortening of telomeres, replicative senescence can be triggered by a DNA damage response. Moreover, cells can also be induced to senesce by DNA damage in response to elevated reactive oxygen species (ROS), activation of oncogenes, cell-cell fusion or after ionizing radiation. There are multiple experimental ways to detect senescent cells directly or indirectly. Senescence-associated cellular traits (SA ß-Gal activity, increase in cell volume and lysosome content, appearance of γ-H2AX foci, increase of ROS and oxidative damage adducts, etc.) can be identified by numerous methods of detection (flow cytometry, confocal imaging, in situ staining, etc.). Here, we improved an existing flow cytometry protocol and further developed a new one specifically tailored to ionizing radiation-induced endothelial senescence. Thus, we have upgraded the Debacq-Chainiaux protocol and added improvements in this protocol (i) to better detect positive events (ii) to offer a compatibility to simultaneously analyze various intracellular molecules including phosphorylated signaling proteins and cytokines, whether related or not to senescence processes.

OMIP-099: 31-color spectral flow cytometry panel to investigate the steady-state phenotype of human T cells.

We have developed a 31-color panel to define the steady-state phenotype of T cells in human peripheral blood (Table 1). The panel presented here was optimized using cryopreserved peripheral blood mononuclear cells (PBMC). The markers included in this panel were chosen in order to characterize the steady-state phenotype of T cells and includes markers (CD45RA, CD45RO, CCR7, CD95) to distinguish the main subsets (e.g., naïve, TEM , TCM , TEMRA , TSCM etc.) of CD4, CD8, and γδ T cells. This panel also includes markers for the identification of differentiation status (CD27, CD28), activation/antigen experience status (CD11a, CD49d, CD38, HLA-DR, CD56, and CD39), co-inhibitory marker expression (PD-1, TIM-3), and CD4 T helper subsets (CXCR3, CXCR5, CCR4, CCR6, Foxp3, CD25, and CD127). This optimized panel provides a broad assessment of the steady-state phenotype of human T cells.

Spectral Flow Cytometry Analysis of Resident Tissue Macrophages.

Spectral flow cytometry improves flow cytometry panels by resolving the full emission spectra of individual fluorophores, allowing greater flexibility to incorporate more fluorochromes when designing multicolor panels. Additionally, the spectral approach captures the autofluorescence of a sample or cell population (e.g., macrophages, which are highly autofluorescent) that can be considered during unmixing for improved downstream analyses. As the increased complexity of macrophage heterogeneity unravels in the scientific community, it is crucial to obtain high-dimensional data at the single-cell level to resolve these populations.

Impact of rising seawater temperature on a phagocytic cell population during V. parahaemolyticus infection in the sea anemone E. pallida.

Climate change is increasing ocean temperatures and consequently impacts marine life (e.g., bacterial communities). In this context, studying host-pathogen interactions in marine organisms is becoming increasingly important, not only for ecological conservation, but also to reduce economic loss due to mass mortalities in cultured species. In this study, we used Exaiptasia pallida (E. pallida), an anemone, as an emerging marine model to better understand the effect of rising temperatures on the infection induced by the pathogenic marine bacterium Vibrio parahaemolyticus. The effect of temperature on E. pallida was examined at 6, 24, or 30 h after bath inoculation with 108 CFU of V. parahaemolyticus expressing GFP (Vp-GFP) at 27°C (husbandry temperature) or 31°C (heat stress). Morphological observations of E. pallida and their Hsps expression demonstrated heat stress induced increasing damage to anemones. The kinetics of the infections revealed that Vp-GFP were localized on the surface of the ectoderm and in the mucus during the first hours of infection and in the mesenterial filaments thereafter. To better identify the E. pallida cells targeted by Vp-GFP infection, we used spectral flow cytometry. E. pallida cell types were identified based on their autofluorescent properties. corresponding to different cell types (algae and cnidocytes). We identified an AF10 population whose autofluorescent spectrum was identical to that of human monocytes/macrophage, suggesting that this spectral print could be the hallmark of phagocytic cells called "amebocytes''. AF10 autofluorescent cells had a high capacity to phagocytize Vp-GFP, suggesting their possible role in fighting infection. This was confirmed by microscopy using sorted AF10 and GFP-positive cells (AF10+/GFP+). The number of AF10+/GFP+ cells were reduced at 31°C, demonstrating that increased temperature not only damages tissue but also affects the immune response of E. pallida. In conclusion, our study provides a springboard for more comprehensive studies of immune defense in marine organisms and paves the way for future studies of the dynamics, activation patterns, and functional responses of immune cells when encountering pathogens.

High-dimensional phenotyping of the peripheral immune response in community-acquired pneumonia.

Background: Community-acquired pneumonia (CAP) represents a major health burden worldwide. Dysregulation of the immune response plays an important role in adverse outcomes in patients with CAP. Methods: We analyzed peripheral blood mononuclear cells by 36-color spectral flow cytometry in adult patients hospitalized for CAP (n=40), matched control subjects (n=31), and patients hospitalized for COVID-19 (n=35). Results: We identified 86 immune cell metaclusters, 19 of which (22.1%) were differentially abundant in patients with CAP versus matched controls. The most notable differences involved classical monocyte metaclusters, which were more abundant in CAP and displayed phenotypic alterations reminiscent of immunosuppression, increased susceptibility to apoptosis, and enhanced expression of chemokine receptors. Expression profiles on classical monocytes, driven by CCR7 and CXCR5, divided patients with CAP into two clusters with a distinct inflammatory response and disease course. The peripheral immune response in patients with CAP was highly similar to that in patients with COVID-19, but increased CCR7 expression on classical monocytes was only present in CAP. Conclusion: CAP is associated with profound cellular changes in blood that mainly relate to classical monocytes and largely overlap with the immune response detected in COVID-19.

Hematopoietic stem cells and extramedullary hematopoiesis in the lungs.

Hematopoietic stem cells are key players in hematopoiesis as the body maintains a physiologic steady state, and the signaling pathways and control mechanisms of these dynamic cells are implicated in processes from inflammation to cancer. Although the bone marrow is commonly regarded as the site of hematopoiesis and hematopoietic stem cell residence, these cells also circulate in the blood and reside in extramedullary tissues, including the lungs. Flow cytometry is an invaluable tool in evaluating hematopoietic stem cells, revealing their phenotypes and relative abundances in both healthy and diseased states. This review outlines current protocols and cell markers used in flow cytometric analysis of hematopoietic stem and progenitor cell populations. Specific niches within the bone marrow are discussed, as are metabolic processes that contribute to stem cell self-renewal and differentiation, as well as the role of hematopoietic stem cells outside of the bone marrow at physiologic steady state. Finally, pulmonary extramedullary hematopoiesis and its associated disease states are outlined. Hematopoiesis in the lungs is a new and emerging concept, and discovering ways in which the study of lung-resident hematopoietic stem cells can be translated from murine models to patients will impact clinical treatment.

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.

Design, optimisation and standardisation of a high-dimensional spectral flow cytometry workflow assessing T-cell immunophenotype in patients with melanoma.

Objectives: Despite the success of immune checkpoint blockade, most metastatic melanoma patients fail to respond to therapy or experience severe toxicity. Assessment of biomarkers and immunophenotypes before or early into treatment will help to understand favourable responses and improve therapeutic outcomes. Methods: We present a high-dimensional approach for blood T-cell profiling using three multi-parameter cytometry panels: (1) a TruCount panel for absolute cell counts, (2) a 27-colour spectral panel assessing T-cell markers and (3) a 20-colour spectral panel evaluating intracellular cytokine expression. Pre-treatment blood mononuclear cells from patients and healthy controls were cryopreserved before staining across 11 batches. Batch effects were tracked using a single-donor control and the suitability of normalisation was assessed. The data were analysed using manual gating and high-dimensional strategies. Results: Batch-to-batch variation was minimal, as demonstrated by the dimensionality reduction of batch-control samples, and normalisation did not improve manual or high-dimensional analysis. Application of the workflow demonstrated the capacity of the panels and showed that patients had fewer lymphocytes than controls (P = 0.0027), due to lower naive CD4+ (P = 0.015) and CD8+ (P = 0.011) T cells and follicular helper T cells (P = 0.00076). Patients showed trends for higher proportions of Ki67 and IL-2-expressing cells within CD4+ and CD8+ memory subsets, and increased CD57 and EOMES expression within TCRγδ+ T cells. Conclusion: Our optimised high-parameter spectral cytometry approach provided in-depth profiling of blood T cells and found differences in patient immunophenotype at baseline. The robustness of our workflow, as demonstrated by minimal batch effects, makes this approach highly suitable for the longitudinal evaluation of immunotherapy effects.