CyTOF® for the Masses

All the single cells: if you like it then you should put some virus on it

Across a rich 70-year history, single-cell virology has revealed the impact of host and pathogen heterogeneity during virus infections. Recent technological innovations have enabled higher-resolution analyses of cellular and viral heterogeneity. Furthermore, single-cell analysis has revealed extreme phenotypes and provided additional insights into host-pathogen dynamics. Using a single-cell approach to explore fundamental virology questions, contemporary researchers have contributed to a revival of interest in single-cell virology with increased insights and enthusiasm.

CAR-T lymphocyte-based cell therapies; mechanistic substantiation, applications and biosafety enhancement with suicide genes: new opportunities to melt side effects

Immunotherapy has made significant strides in cancer treatment with strategies like checkpoint blockade antibodies and adoptive T cell transfer. Chimeric antigen receptor T cells (CAR-T) have emerged as a promising approach to combine these strategies and overcome their limitations. This review explores CAR-T cells as a living drug for cancer treatment. CAR-T cells are genetically engineered immune cells designed to target and eliminate tumor cells by recognizing specific antigens. The study involves a comprehensive literature review on CAR-T cell technology, covering structure optimization, generations, manufacturing processes, and gene therapy strategies. It examines CAR-T therapy in haematologic cancers and solid tumors, highlighting challenges and proposing a suicide gene-based mechanism to enhance safety. The results show significant advancements in CAR-T technology, particularly in structure optimization and generation. The manufacturing process has improved for broader clinical application. However, a series of inherent challenges and side effects still need to be addressed. In conclusion, CAR-T cells hold great promise for cancer treatment, but ongoing research is crucial to improve efficacy and safety for oncology patients. The proposed suicide gene-based mechanism offers a potential solution to mitigate side effects including cytokine release syndrome (the most common toxic side effect of CAR-T therapy) and the associated neurotoxicity.

Single-cell mass cytometry in immunological skin diseases

Immune-related skin diseases represent a collective of dermatological disorders intricately linked to dysfunctional immune system processes. These conditions are primarily characterized by an immoderate activation of the immune system or deviant immune responses, involving diverse immune components including immune cells, antibodies, and inflammatory mediators. However, the precise molecular dysregulation underlying numerous individual cases of these diseases and unique subsets respond under disease conditions remains elusive. Comprehending the mechanisms and determinants governing the homeostasis and functionality of diseases could offer potential therapeutic opportunities for intervention. Mass cytometry enables precise and high-throughput quantitative measurement of proteins within individual cells by utilizing antibodies labeled with rare heavy metal isotopes. Imaging mass cytometry employs mass spectrometry to obtain spatial information on cell-to-cell interactions within tissue sections, simultaneously utilizing more than 40 markers. The application of single-cell mass cytometry presents a unique opportunity to conduct highly multiplexed analysis at the single-cell level, thereby revolutionizing our understanding of cell population heterogeneity and hierarchy, cellular states, multiplexed signaling pathways, proteolysis products, and mRNA transcripts specifically in the context of many autoimmune diseases. This information holds the potential to offer novel approaches for the diagnosis, prognostic assessment, and monitoring responses to treatment, thereby enriching our strategies in managing the respective conditions. This review summarizes the present-day utilization of single-cell mass cytometry in studying immune-related skin diseases, highlighting its advantages and limitations. This technique will become increasingly prevalent in conducting extensive investigations into these disorders, ultimately yielding significant contributions to their accurate diagnosis and efficacious therapeutic interventions.

The immune landscape of uterine fibroids as determined by mass cytometry

OBJECTIVE

To study the differences in immune cell profiles in uterine fibroids (Fibs) and matched myometrium (Myo).

DESIGN

Observational study.

SETTING

Laboratory study.

PATIENT(S)

The study included tissue that was collected from 10 pairs of Fib and matched Myo from women, not on hormonal medications, undergoing hysterectomy and myomectomy.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Differences in immune cell and cytokine composition between Fib and matched Myo.

RESULT(S)

The mass cytometry analysis indicated that Fibs had a significantly higher number of natural killer (NK) cells, total macrophages, M2 macrophages, and conventional dendritic cells when compared with matched Myo from the same patient. In contrast, Fibs had significantly fewer CD3 and CD4 T cells when compared with Myo. The mass cytometry analysis results did not show any significant difference in the number of resting mast cells. Immunoflurorescent and immunohistochemical imaging confirmed the cytometry by time of flight results, showing a significantly higher number of NK cells, tryptase-positive mast cells indicative of mast cell activation, total macrophages, and M2 cells in Fibs and a significantly lower number of CD3 and CD4 T cells. The cytokine assay revealed significantly increased levels of human interferon α2, interleukin (IL)-1α, and platelet-derived growth factor AA and significantly lower levels of macrophage colony-stimulating factor and IL-1 receptor antagonist in Fib.

CONCLUSION(S)

Our results show significant differences in immune cell populations and cytokine levels between Fib and Myo. These differences could account for the increased inflammation in fib and a potential mechanism by which these tumors evade the immune system. These findings provide a foundation for further studies exploring the role of immune cells in Fib development.

Development of a Spectral Flow Cytometry Analysis Pipeline for High-Dimensional Immune Cell Characterization

Flow cytometry is a widely used technique for immune cell analysis, offering insights into cell composition and function. Spectral flow cytometry allows for high-dimensional analysis of immune cells, overcoming limitations of conventional flow cytometry. However, analyzing data from large antibody panels can be challenging using traditional bi-axial gating strategies. Here, we present a novel analysis pipeline designed to improve analysis of spectral flow cytometry. We employ this method to identify rare T cell populations in aging. We isolated splenocytes from young (2-3 months) and aged (18-19 months) female mice then stained these with a panel of 20 fluorescently labeled antibodies. Spectral flow cytometry was performed, followed by data processing and analysis using Python within a Jupyter Notebook environment to perform batch correction, unsupervised clustering, dimensionality reduction, and differential expression analysis. Our analysis of 3,776,804 T cells from 11 spleens revealed 34 distinct T cell clusters identified by surface marker expression. We observed significant differences between young and aged mice, with certain clusters enriched in one age group over the other. Naïve, effector memory, and central memory CD8+ and CD4+ T cell subsets exhibited age-associated changes in abundance and marker expression. Additionally, γδ T cell clusters showed differential abundance between age groups. By leveraging high-dimensional analysis methods borrowed from single-cell RNA sequencing analysis, we identified age-related differences in T cell subsets, providing insights into the immune aging process. This approach offers a robust, free, and easily implemented analysis pipeline for spectral flow cytometry data that may facilitate the discovery of novel therapeutic targets for age-related immune dysfunction.

CyTOF analysis revealed platelet heterogeneity in breast cancer patients received T-DM1 treatment

T-DM1 (Trastuzumab Emtansine) belongs to class of Antibody-Drug Conjugates (ADC), where cytotoxic drugs are conjugated with the antibody Trastuzumab to specifically target HER2-positive cancer cells. Platelets, as vital components of the blood system, intricately influence the immune response to tumors through complex mechanisms. In our study, we examined platelet surface proteins in the plasma of patients before and after T-DM1 treatment, categorizing them based on treatment response. We identified a subgroup of platelets with elevated expression of CD63 and CD9 exclusively in patients with favorable treatment responses, while this subgroup was absent in patients with poor responses. Another noteworthy discovery was the elevated expression of CD36 in the platelet subgroups of patients exhibiting inadequate responses to treatment. These findings suggest that the expression of these platelet surface proteins may be correlated with the prognosis of T-DM1 treatment. These indicators offer valuable insights for predicting the therapeutic response to T-DM1 and may become important references in future clinical practice, contributing to a better understanding of the impact of ADC therapies and optimizing personalized cancer treatment strategies.

Natural killer cells associate with epithelial cells in the pancreatic ductal adenocarcinoma tumor microenvironment

Background

Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer. PDAC's poor prognosis and resistance to immunotherapy are attributed in part to its dense, fibrotic tumor microenvironment (TME), which is known to inhibit immune cell infiltration. We recently demonstrated that PDAC patients with higher natural killer (NK) cell content and activation have better survival rates. However, NK cell interactions in the PDAC TME have yet to be deeply studied. We show here that NK cells are present and active in the human PDAC TME.

Methods

We used imaging mass cytometry (IMC) to assess NK cell content, function, and spatial localization in human PDAC samples. Then, we used CellChat, a tool to infer ligand-receptor interactions, on a human PDAC scRNAseq dataset to further define NK cell interactions in PDAC.

Results

Spatial analyses showed for the first time that active NK cells are present in the PDAC TME, and both associate and interact with malignant epithelial cell ducts. We also found that fibroblast-rich, desmoplastic regions limit NK cell infiltration in the PDAC TME. CellChat analysis identified that the CD44 receptor on NK cells interacts with PDAC extracellular matrix (ECM) components such as collagen, fibronectin and laminin expressed by fibroblasts and malignant epithelial cells. This led us to hypothesize that these interactions play roles in regulating NK cell motility in desmoplastic PDAC TMEs. Using 2D and 3D in vitro assays, we found that CD44 neutralization significantly increased NK cell invasion through matrix.

Conclusions

Targeting ECM-immune cell interactions may increase NK cell invasion into the PDAC TME.

Applications of single‑cell omics and spatial transcriptomics technologies in gastric cancer (Review)

Gastric cancer (GC) is a prominent contributor to global cancer-related mortalities, and a deeper understanding of its molecular characteristics and tumor heterogeneity is required. Single-cell omics and spatial transcriptomics (ST) technologies have revolutionized cancer research by enabling the exploration of cellular heterogeneity and molecular landscapes at the single-cell level. In the present review, an overview of the advancements in single-cell omics and ST technologies and their applications in GC research is provided. Firstly, multiple single-cell omics and ST methods are discussed, highlighting their ability to offer unique insights into gene expression, genetic alterations, epigenomic modifications, protein expression patterns and cellular location in tissues. Furthermore, a summary is provided of key findings from previous research on single-cell omics and ST methods used in GC, which have provided valuable insights into genetic alterations, tumor diagnosis and prognosis, tumor microenvironment analysis, and treatment response. In summary, the application of single-cell omics and ST technologies has revealed the levels of cellular heterogeneity and the molecular characteristics of GC, and holds promise for improving diagnostics, personalized treatments and patient outcomes in GC.

Applications of Flow Cytometry in Drug Discovery and Translational Research

Flow cytometry is a mainstay technique in cell biology research, where it is used for phenotypic analysis of mixed cell populations. Quantitative approaches have unlocked a deeper value of flow cytometry in drug discovery research. As the number of drug modalities and druggable mechanisms increases, there is an increasing drive to identify meaningful biomarkers, evaluate the relationship between pharmacokinetics and pharmacodynamics (PK/PD), and translate these insights into the evaluation of patients enrolled in early clinical trials. In this review, we discuss emerging roles for flow cytometry in the translational setting that supports the transition and evaluation of novel compounds in the clinic.

Analysis of the multiparametric cell cycle data

This chapter was originally written in 2011. The idea was to give some history of cell cycle analysis before and after flow cytometry became widely accessible; provide references to educational material for single parameter DNA content analysis, introduce and discuss multiparameter cell cycle analysis in a methodological style, and in a casual style, discuss aspects of the work over the last 40years that we have given thought, performing some experiments, but didn't publish. It feels like there is a linear progression that moves from counting cells for growth curves, to counting labeled mitotic cells by autoradiography, to DNA content analysis, to cell cycle states defined by immunofluorescence plus DNA content analysis, to extraction of cell cycle expression profiles, and finally to probability state modeling, which should be the "right" way to analyze cytometric cell cycle data. This is the sense of this chapter. In 2023, we have updated it, but the exciting, expansive aspects brought about by spectral and mass cytometry are still young and developing, and thus have not been vetted, reviewed, and presented in mature form.

Advancements in technology for characterizing the tumor immune microenvironment

Immunotherapy plays a key role in cancer treatment, however, responses are limited to a small number of patients. The biological basis for the success of immunotherapy is the complex interaction between tumor cells and tumor immune microenvironment (TIME). Historically, research on tumor immune constitution was limited to the analysis of one or two markers, more novel technologies are needed to interpret the complex interactions between tumor cells and TIME. In recent years, major advances have already been made in depicting TIME at a considerably elevated degree of throughput, dimensionality and resolution, allowing dozens of markers to be labeled simultaneously, and analyzing the heterogeneity of tumour-immune infiltrates in detail at the single cell level, depicting the spatial landscape of the entire microenvironment, as well as applying artificial intelligence (AI) to interpret a large amount of complex data from TIME. In this review, we summarized emerging technologies that have made contributions to the field of TIME, and provided prospects for future research.

ERS International Congress 2023: highlights from the Basic and Translational Sciences Assembly

Early career members of Assembly 3 (Basic and Translational Sciences) of the European Respiratory Society (ERS) summarise the key messages discussed during six selected sessions that took place at the ERS International Congress 2023 in Milan, Italy. Aligned with the theme of the congress, the first session covered is "Micro- and macro-environments and respiratory health", which is followed by a summary of the "Scientific year in review" session. Next, recent advances in experimental methodologies and new technologies are discussed from the "Tissue modelling and remodelling" session and a summary provided of the translational science session, "What did you always want to know about omics analyses for clinical practice?", which was organised as part of the ERS Translational Science initiative's aims. The "Lost in translation: new insights into cell-to-cell crosstalk in lung disease" session highlighted how next-generation sequencing can be integrated with laboratory methods, and a final summary of studies is presented from the "From the transcriptome landscape to innovative preclinical models in lung diseases" session, which links the transcriptome landscape with innovative preclinical models. The wide range of topics covered in the selected sessions and the high quality of the research discussed demonstrate the strength of the basic and translational science being presented at the international respiratory conference organised by the ERS.

Modeling Molecular Pathogenesis of Idiopathic Pulmonary Fibrosis-Associated Lung Cancer in Mice

Idiopathic pulmonary fibrosis (IPF) is characterized by progressive, often fatal loss of lung function due to overactive collagen production and tissue scarring. Patients with IPF have a sevenfold-increased risk of developing lung cancer. The COVID-19 pandemic has increased the number of patients with lung diseases, and infection can worsen prognoses for those with chronic lung diseases and disease-associated cancer. Understanding the molecular pathogenesis of IPF-associated lung cancer is imperative for identifying diagnostic biomarkers and targeted therapies that will facilitate prevention of IPF and progression to lung cancer. To understand how IPF-associated fibroblast activation, matrix remodeling, epithelial-to-mesenchymal transition (EMT), and immune modulation influences lung cancer predisposition, we developed a mouse model to recapitulate the molecular pathogenesis of pulmonary fibrosis-associated lung cancer using the bleomycin and Lewis lung carcinoma models. We demonstrate that development of pulmonary fibrosis-associated lung cancer is likely linked to increased abundance of tumor-associated macrophages and a unique gene signature that supports an immune-suppressive microenvironment through secreted factors. Not surprisingly, preexisting fibrosis provides a pre-metastatic niche and results in augmented tumor growth, and tumors associated with bleomycin-induced fibrosis are characterized by a dramatic loss of cytokeratin expression, indicative of EMT.

IMPLICATIONS

This characterization of tumors associated with lung diseases provides new therapeutic targets that may aid in the development of treatment paradigms for lung cancer patients with preexisting pulmonary diseases.

Systemic and local immunosuppression in glioblastoma and its prognostic significance

The effectiveness of tumor therapy, especially immunotherapy and oncolytic virotherapy, critically depends on the activity of the host immune cells. However, various local and systemic mechanisms of immunosuppression operate in cancer patients. Tumor-associated immunosuppression involves deregulation of many components of immunity, including a decrease in the number of T lymphocytes (lymphopenia), an increase in the levels or ratios of circulating and tumor-infiltrating immunosuppressive subsets [e.g., macrophages, microglia, myeloid-derived suppressor cells (MDSCs), and regulatory T cells (Tregs)], as well as defective functions of subsets of antigen-presenting, helper and effector immune cell due to altered expression of various soluble and membrane proteins (receptors, costimulatory molecules, and cytokines). In this review, we specifically focus on data from patients with glioblastoma/glioma before standard chemoradiotherapy. We discuss glioblastoma-related immunosuppression at baseline and the prognostic significance of different subsets of circulating and tumor-infiltrating immune cells (lymphocytes, CD4+ and CD8+ T cells, Tregs, natural killer (NK) cells, neutrophils, macrophages, MDSCs, and dendritic cells), including neutrophil-to-lymphocyte ratio (NLR), focus on the immune landscape and prognostic significance of isocitrate dehydrogenase (IDH)-mutant gliomas, proneural, classical and mesenchymal molecular subtypes, and highlight the features of immune surveillance in the brain. All attempts to identify a reliable prognostic immune marker in glioblastoma tissue have led to contradictory results, which can be explained, among other things, by the unprecedented level of spatial heterogeneity of the immune infiltrate and the significant phenotypic diversity and (dys)functional states of immune subpopulations. High NLR is one of the most repeatedly confirmed independent prognostic factors for shorter overall survival in patients with glioblastoma and carcinoma, and its combination with other markers of the immune response or systemic inflammation significantly improves the accuracy of prediction; however, more prospective studies are needed to confirm the prognostic/predictive power of NLR. We call for the inclusion of dynamic assessment of NLR and other blood inflammatory markers (e.g., absolute/total lymphocyte count, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, systemic immune-inflammation index, and systemic immune response index) in all neuro-oncology studies for rigorous evaluation and comparison of their individual and combinatorial prognostic/predictive significance and relative superiority.

Lessons learned from phase 3 trials of immunotherapy for glioblastoma: Time for longitudinal sampling?

Glioblastoma (GBM)'s median overall survival is almost 21 months. Six phase 3 immunotherapy clinical trials have recently been published, yet 5/6 did not meet approval by regulatory bodies. For the sixth, approval is uncertain. Trial failures result from multiple factors, ranging from intrinsic tumor biology to clinical trial design. Understanding the clinical and basic science of these 6 trials is compelled by other immunotherapies reaching the point of advanced phase 3 clinical trial testing. We need to understand more of the science in human GBMs in early trials: the "window of opportunity" design may not be best to understand complex changes brought about by immunotherapeutic perturbations of the GBM microenvironment. The convergence of increased safety of image-guided biopsies with "multi-omics" of small cell numbers now permits longitudinal sampling of tumor and biofluids to dissect the complex temporal changes in the GBM microenvironment as a function of the immunotherapy.

Antigen loss following CAR-T cell therapy: Mechanisms, implications, and potential solutions

Chimeric Antigen Receptor T-cell (CAR-T cell) therapy has emerged as a groundbreaking immunotherapeutic approach for treating various hematological malignancies. CAR-T cells are engineered to express synthetic receptors that target specific antigens on cancer cells, leading to their eradication. While the therapy has shown remarkable efficacy, a significant challenge that has been observed in 30%-70% of patients showing recurrent disease is antigen loss or downregulation. We searched PubMed/MEDLINE, EMBASE, and Google scholar for articles on antigen loss/escape following Chimeric antigen receptor T-cell therapy in malignancies. Antigen loss refers to the loss or reduction in the expression of the target antigen on cancer cells, rendering CAR-T cells ineffective. This phenomenon poses a significant clinical concern, as it can lead to disease relapse and limited treatment options. This review explores the mechanisms underlying antigen loss following CAR-T cell therapy, its implications on treatment outcomes, and potential strategies to overcome the problem.

Review of flow cytometry as a tool for cell and gene therapy

Quality control testing and analytics are critical for the development and manufacture of cell and gene therapies, and flow cytometry is a key quality control and analytical assay that is used extensively. However, the technical scope of characterization assays and safety assays must keep apace as the breadth of cell therapy products continues to expand beyond hematopoietic stem cell products into producing novel adoptive immune therapies and gene therapy products.  Flow cytometry services are uniquely positioned to support the evolving needs of cell therapy facilities, as access to flow cytometers, new antibody clones and improved fluorochrome reagents becomes more egalitarian. This report will outline the features, logistics, limitations and the current state of flow cytometry within the context of cellular therapy.

Mapping the single cell spatial immune landscapes of the melanoma microenvironment

Melanoma is a highly immunogenic malignancy with an elevated mutational burden, diffuse lymphocytic infiltration, and one of the highest response rates to immune checkpoint inhibitors (ICIs). However, over half of all late-stage patients treated with ICIs will either not respond or develop progressive disease. Spatial imaging technologies are being increasingly used to study the melanoma tumor microenvironment (TME). The goal of such studies is to understand the complex interplay between the stroma, melanoma cells, and immune cell-types as well as their association with treatment response. Investigators seeking a better understanding of the role of cell location within the TME and the importance of spatial expression of biomarkers are increasingly turning to highly multiplexed imaging approaches to more accurately measure immune infiltration as well as to quantify receptor-ligand interactions (such as PD-1 and PD-L1) and cell-cell contacts. CyTOF-IMC (Cytometry by Time of Flight - Imaging Mass Cytometry) has enabled high-dimensional profiling of melanomas, allowing researchers to identify complex cellular subpopulations and immune cell interactions with unprecedented resolution. Other spatial imaging technologies, such as multiplexed immunofluorescence and spatial transcriptomics, have revealed distinct patterns of immune cell infiltration, highlighting the importance of spatial relationships, and their impact in modulating immunotherapy responses. Overall, spatial imaging technologies are just beginning to transform our understanding of melanoma biology, providing new avenues for biomarker discovery and therapeutic development. These technologies hold great promise for advancing personalized medicine to improve patient outcomes in melanoma and other solid malignancies.

Approaching Mass Cytometry Translational Studies by Experimental and Data Curation Settings

Clinical studies are conducted to better understand the pathological mechanism of diseases and to find biomarkers associated with disease activity, drug response, or outcome prediction. Mass cytometry (MC) is a high-throughput single-cell technology that measures hundreds of cells per second with more than 40 markers per cell. Thus, it is a suitable tool for immune monitoring and biomarker discovery studies. Working in translational and clinical settings requires a careful experimental design to minimize, monitor, and correct the variations introduced during sample collection, preparation, acquisition, and analysis. In this review, we will focus on these important aspects of MC-related experiments and data curation in the context of translational clinical research projects.

Mass Cytometry in Food Allergy Research

Mechanisms underlying food allergy are not well understood. Mass cytometry is a technique that allows the multiple analysis of cell surface markers and intracellular proteins by using the spectrum of rare metal isotopes of different atomic masses without channel overlap. Bioinformatic approaches are implemented to combine and reduce the information of more than 60 parameters to define immune cell subpopulations. To date, mass cytometry has revealed a great heterogeneity in human response to food antigens and that subpopulations of basophils and mononuclear cells might be mechanistically implicated in food allergy. This chapter reviews some fundamentals of mass cytometry and the contributions of this technique in elucidating the immune basis of food allergy, oral tolerance, food desensitization, phenotypes, and the cellular events occurring upon allergen-specific immunotherapy.

Application of mass cytometry to characterize hematopoietic stem cells in apheresis products of patients with hematological malignancies

INTRODUCTION

Hematopoietic stem cell transplantation (HSCT) is a widely used therapy, but its success largely depends on the number and quality of stem cells collected. Current evidence shows the complexity of the hematopoietic system, which implies that, in the quality assurance of the apheresis product, the hematopoietic stem cells are adequately characterized and quantified, in which mass cytometry (MC) can provide its advantages in high-dimensional analysis.

OBJECTIVE

This research aimed to characterize and enumerate CD45dim/CD34+ stem cells using the MC in apheresis product yields from patients with chronic lymphoid malignant diseases undergoing autologous transplantation at the Abu Dhabi Stem Cells Center.

METHODS

An analytical and cross-sectional study was performed on 31 apheresis products from 15 patients diagnosed with multiple myeloma (n = 9) and non-Hodgkin lymphomas (n = 6) eligible for HSCT. The MC was employed using the MaxPar Kit for stem cell immunophenotyping. The analysis was performed manually in the Kaluza and unsupervised by machine learning in Cytobank Premium.

RESULTS

An excellent agreement was found between mass and flow cytometry for the relative and absolute counts of CD45dim/CD34+ cells (Bland-Altman bias: -0.029 and -64, respectively), seven subpopulations were phenotyped and no lineage bias was detected for any of the methods used in the pool of collected cells. A CD34+/CD38+/CD138+ population was seen in the analyses performed on four patients with multiple myeloma.

CONCLUSIONS

The MC helps to characterize subpopulations of stem cells in apheresis products. It also allows cell quantification by double platform. Unsupervised analysis allows results completion and validation of the manual strategy. The proposed methodology can be extended to apheresis products for purposes other than HSCT.

Functional phenotyping of hepatic lymphocytes in murine MASH by mass cytometry

Hepatic inflammation, driven by immune cells such as B and T lymphocytes, is a hallmark feature of metabolic dysfunction-associated steatohepatitis (MASH). Here, we detail a robust cytometry by time-of-flight (CyTOF) procedure to phenotype hepatic lymphocytes from mice with MASH. We employ custom metal conjugation of antibodies, isolation of hepatic lymphocytes, cell surface and intracellular staining, and data acquisition. This protocol overcomes the limitations of traditional flow cytometry by accommodating up to 40 markers for comprehensive immune phenotyping. For complete details on the use and execution of this protocol, please refer to Barrow et al.1.

Spatial -omics technologies: the new enterprise in 3D breast cancer models

The fields of tissue bioengineering, -omics, and spatial biology are advancing rapidly, each offering the opportunity for a paradigm shift in breast cancer research. However, to date, collaboration between these fields has not reached its full potential. In this review, we describe the most recently generated 3D breast cancer models regarding the biomaterials and technological platforms employed. Additionally, their biological evaluation is reported, highlighting their advantages and limitations. Specifically, we focus on the most up-to-date -omics and spatial biology techniques, which can generate a deeper understanding of the biological relevance of bioengineered 3D breast cancer in vitro models, thus paving the way towards truly clinically relevant microphysiological systems, improved drug development success rates, and personalised medicine approaches.

Mass cytometry as a tool in target validation and drug discovery

Mass cytometry provides highly multiparametric data at a single cell level, coupling the specificity and sensitivity of time-of-flight mass spectrometry with the single-cell throughput of flow cytometry. It offers great value in interrogating the potentially heterogenous impact that a drug may have on a biological system, allowing an investigator to capture not just changes in cell behavior, but how these changes may differ between cell subtypes. In this chapter, we review the technical details of the platform as well as its limitations, before describing our approach to planning and running a mass cytometry experiment. A series of method modules, spanning the staining process through to data cleaning, are described that are then combined to create three separate experiments. The first experiment illustrates a core process in mass cytometry: the validation and titration of a metal-conjugated antibody reporter. The second experiment explores the impact of a kinase inhibitor on cell cycle and apoptosis pathways of a human myeloma cell line. And the third experiment exploits the multiparametric capability of mass cytometry, by exploring the differential expression changes in a transcription factor upon drug treatment across the cellular compartments of a peripheral blood mononuclear cell sample.

Location, location, location: mapping the lymphoma tumor microenvironment using spatial transcriptomics

Lymphomas are a heterogenous group of lymphoid neoplasms with a wide variety of clinical presentations. Response to treatment and prognosis differs both between and within lymphoma subtypes. Improved molecular and genetic profiling has increased our understanding of the factors which drive these clinical dynamics. Immune and non-immune cells within the lymphoma tumor microenvironment (TME) can both play a key role in antitumor immune responses and conversely also support lymphoma growth and survival. A deeper understanding of the lymphoma TME would identify key lymphoma and immune cell interactions which could be disrupted for therapeutic benefit. Single cell RNA sequencing studies have provided a more comprehensive description of the TME, however these studies are limited in that they lack spatial context. Spatial transcriptomics provides a comprehensive analysis of gene expression within tissue and is an attractive technique in lymphoma to both disentangle the complex interactions between lymphoma and TME cells and improve understanding of how lymphoma cells evade the host immune response. This article summarizes current spatial transcriptomic technologies and their use in lymphoma research to date. The resulting data has already enriched our knowledge of the mechanisms and clinical impact of an immunosuppressive TME in lymphoma and the accrual of further studies will provide a fundamental step in the march towards personalized medicine.

Exploring New Dimensions of Tumor Heterogeneity: The Application of Single Cell Analysis to Organoid-Based 3D In Vitro Models

Modeling the heterogeneity of the tumor microenvironment (TME) in vitro is essential to investigating fundamental cancer biology and developing novel treatment strategies that holistically address the factors affecting tumor progression and therapeutic response. Thus, the development of new tools for both in vitro modeling, such as patient-derived organoids (PDOs) and complex 3D in vitro models, and single cell omics analysis, such as single-cell RNA-sequencing, represents a new frontier for investigating tumor heterogeneity. Specifically, the integration of PDO-based 3D in vitro models and single cell analysis offers a unique opportunity to explore the intersecting effects of interpatient, microenvironmental, and tumor cell heterogeneity on cell phenotypes in the TME. In this review, the current use of PDOs in complex 3D in vitro models of the TME is discussed and the emerging directions in the development of these models are highlighted. Next, work that has successfully applied single cell analysis to PDO-based models is examined and important experimental considerations are identified for this approach. Finally, open questions are highlighted that may be amenable to exploration using the integration of PDO-based models and single cell analysis. Ultimately, such investigations may facilitate the identification of novel therapeutic targets for cancer that address the significant influence of tumor-TME interactions.

How single-cell techniques help us look into lung cancer heterogeneity and immunotherapy

Lung cancer patients tend to have strong intratumoral and intertumoral heterogeneity and complex tumor microenvironment, which are major contributors to the efficacy of and drug resistance to immunotherapy. From a new perspective, single-cell techniques offer an innovative way to look at the intricate cellular interactions between tumors and the immune system and help us gain insights into lung cancer and its response to immunotherapy. This article reviews the application of single-cell techniques in lung cancer, with focuses directed on the heterogeneity of lung cancer and the efficacy of immunotherapy. This review provides both theoretical and experimental information for the future development of immunotherapy and personalized treatment for the management of lung cancer.

Dynamic evaluation of blood immune cells predictive of response to immune checkpoint inhibitors in NSCLC by multicolor spectrum flow cytometry

Introduction

Immune checkpoint inhibitors (ICIs) only benefit a subset of cancer patients, underlining the need for predictive biomarkers for patient selection. Given the limitations of tumor tissue availability, flow cytometry of peripheral blood mononuclear cells (PBMCs) is considered a noninvasive method for immune monitoring. This study explores the use of spectrum flow cytometry, which allows a more comprehensive analysis of a greater number of markers using fewer immune cells, to identify potential blood immune biomarkers and monitor ICI treatment in non-small-cell lung cancer (NSCLC) patients.

Methods

PBMCs were collected from 14 non-small-cell lung cancer (NSCLC) patients before and after ICI treatment and 4 healthy human donors. Using spectrum flow cytometry, 24 immune cell markers were simultaneously monitored using only 1 million PBMCs. The results were also compared with those from clinical flow cytometry and bulk RNA sequencing analysis.

Results

Our findings showed that the measurement of CD4+ and CD8+ T cells by spectrum flow cytometry matched well with those by clinical flow cytometry (Pearson R ranging from 0.75 to 0.95) and bulk RNA sequencing analysis (R=0.80, P=1.3 x 10-4). A lower frequency of CD4+ central memory cells before treatment was associated with a longer median progression-free survival (PFS) [Not reached (NR) vs. 5 months; hazard ratio (HR)=8.1, 95% confidence interval (CI) 1.5-42, P=0.01]. A higher frequency of CD4-CD8- double-negative (DN) T cells was associated with a longer PFS (NR vs. 4.45 months; HR=11.1, 95% CI 2.2-55.0, P=0.003). ICIs significantly changed the frequency of cytotoxic CD8+PD1+ T cells, DN T cells, CD16+CD56dim and CD16+CD56- natural killer (NK) cells, and CD14+HLDRhigh and CD11c+HLADR + monocytes. Of these immune cell subtypes, an increase in the frequency of CD16+CD56dim NK cells and CD14+HLADRhigh monocytes after treatment compared to before treatment were associated with a longer PFS (NR vs. 5 months, HR=5.4, 95% CI 1.1-25.7, P=0.03; 7.8 vs. 3.8 months, HR=5.7, 95% CI 169 1.0-31.7, P=0.04), respectively.

Conclusion

Our preliminary findings suggest that the use of multicolor spectrum flow cytometry helps identify potential blood immune biomarkers for ICI treatment, which warrants further validation.

Cytokine and chemokine map of peripheral specific immune cell subsets in Parkinson's disease

Peripheral immune cells play a vital role in the development of Parkinson's disease (PD). However, their cytokine and chemokine secretion functions remain unclear. Therefore, we aimed to explore the cytokine and chemokine secretion functions of specific immune cell subtypes in drug-naïve patients with PD at different ages of onset. We included 10 early-onset and 10 late-onset patients with PD and age-matched healthy controls (HCs). We used mass cytometry to select specific immune cell subsets and evaluate intracellular cytokine and chemokine expression. Statistical tests included t-tests, analysis of variance, bivariate correlation analysis, and linear regression analysis. Compared with HCs, patients with PD exhibited significantly decreased intracellular pro-inflammatory cytokines and chemokines in selected clusters (e.g., tumor necrosis factor (TNF)-α, interleukin (IL)-8, IL-1β, and CC-chemokine ligand (CCL)17). Specific cytokines and cell clusters were associated with clinical symptoms. TNF-α played an important role in cognitive impairment. Intracellular TNF-α levels in the naïve CD8⁺ T-cell cluster C16 (CD57^- naïve CD8⁺ T) and natural killer (NK) cell cluster C32 (CD57^- CD28^- NK) were negatively correlated with Montreal Cognitive Assessment scores. The C16 cluster affected cognitive function and motor symptoms. Increased TNF-α and decreased interferon-γ expression in C16 correlated with increased Unified Parkinson's Disease Rating Scale III scores in patients with PD. In summary, we developed a more detailed cytokine and chemokine map of peripheral specific CD8⁺ T cell and NK cell subsets, which revealed disrupted secretory function in patients with PD and provided unique clues for further mechanistic exploration.

A universal mass tag based on polystyrene nanoparticles for single-cell multiplexing with mass cytometry

Mass cytometry (MC) is an emerging bioanalytical technique for high-dimensional biomarkers interrogation simultaneously on individual cells. However, the sensitivity and multiplexed analysis ability of MC was highly restricted by the current metal chelating polymer (MCP) mass tags. Herein, a new design strategy for MC mass tags by using a commercial available and low cost classical material, polystyrene nanoparticle (PS-NP) to carry metals was reported. Unlike inorganic materials, sub-micron-grade metal-loaded polystyrene can be easily detected by MC, thus it is not essential to pursue extremely small particle size in this mass tag design strategy. An altered cell staining buffer can significantly lower the nonspecific binding (NSB) of non-functionalized PS-NPs, revealing another method to lower NSB beside surface modification. The metal doped PS-NP_Abs mass tags showed high compatibility with MCP mass tags and 5-fold higher sensitivity. By using Hf doped PS-NP_Abs as mass tags, four new MC detection channels (¹⁷⁷Hf, ¹⁷⁸Hf, ¹⁷⁹Hf and ¹⁸⁰Hf) were developed. In general, this work provides a new strategy in designing MC mass tags and lowering NSB, opening up possibility of introducing more potential MC mass tag candidates.

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.

Current Methods for Identifying Plasma Membrane Proteins as Cancer Biomarkers

Plasma membrane proteins are a special class of biomolecules present on the cellular membrane. They provide the transport of ions, small molecules, and water in response to internal and external signals, define a cell's immunological identity, and facilitate intra- and intercellular communication. Since they are vital to almost all cellular functions, their mutants, or aberrant expression is linked to many diseases, including cancer, where they are a part of cancer cell-specific molecular signatures and phenotypes. In addition, their surface-exposed domains make them exciting biomarkers for targeting by imaging agents and drugs. This review looks at the challenges in identifying cancer-related cell membrane proteins and the current methodologies that solve most of the challenges. We classified the methodologies as biased, i.e., search cells for the presence of already known membrane proteins. Second, we discuss the unbiased methods that can identify proteins without prior knowledge of what they are. Finally, we discuss the potential impact of membrane proteins on the early detection and treatment of cancer.

To metabolomics and beyond: a technological portfolio to investigate cancer metabolism

Tumour cells have exquisite flexibility in reprogramming their metabolism in order to support tumour initiation, progression, metastasis and resistance to therapies. These reprogrammed activities include a complete rewiring of the bioenergetic, biosynthetic and redox status to sustain the increased energetic demand of the cells. Over the last decades, the cancer metabolism field has seen an explosion of new biochemical technologies giving more tools than ever before to navigate this complexity. Within a cell or a tissue, the metabolites constitute the direct signature of the molecular phenotype and thus their profiling has concrete clinical applications in oncology. Metabolomics and fluxomics, are key technological approaches that mainly revolutionized the field enabling researchers to have both a qualitative and mechanistic model of the biochemical activities in cancer. Furthermore, the upgrade from bulk to single-cell analysis technologies provided unprecedented opportunity to investigate cancer biology at cellular resolution allowing an in depth quantitative analysis of complex and heterogenous diseases. More recently, the advent of functional genomic screening allowed the identification of molecular pathways, cellular processes, biomarkers and novel therapeutic targets that in concert with other technologies allow patient stratification and identification of new treatment regimens. This review is intended to be a guide for researchers to cancer metabolism, highlighting current and emerging technologies, emphasizing advantages, disadvantages and applications with the potential of leading the development of innovative anti-cancer therapies.

Interrogating the sepsis host immune response using cytomics

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2023. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2023 . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from https://link.springer.com/bookseries/8901 .

Dormant cancer cells: programmed quiescence, senescence, or both?

Metastasis is the overwhelming driver of cancer mortality, accounting for the majority of cancer deaths. Many patients present with metastatic relapse years after eradication of the primary lesion. Disseminated cancer cells can undergo a durable proliferative arrest and lie dormant in secondary tissues before reentering the cell cycle to seed these lethal relapses. This process of cancer cell dormancy remains poorly understood, largely due to difficulties in studying these dormant cells. In the face of these challenges, the application of knowledge from the cellular senescence and quiescence fields may help to guide future thinking on the study of dormant cancer cells. Both senescence and quiescence are common programs of proliferative arrest that are integral to tissue development and homeostasis. Despite phenotypic differences, these two states also share common characteristics, and both likely play a role in cancer dormancy and delayed metastatic relapse. Understanding the cell biology behind these states, their overlaps and unique characteristics is critical to our future understanding of dormant cancer cells, as these cells likely employ some of the same molecular programs to promote survival and dissemination. In this review, we highlight the biology underlying these non-proliferative states, relate this knowledge to what we currently know about dormant cancer cells, and discuss implications for future work toward targeting these elusive metastatic seeds.

To be or not to be: The double-edged sword roles of liver progenitor cells

Given the liver's remarkable and unique regenerative capacity, researchers have long focused on liver progenitor cells (LPCs) and liver cancer stem cells (LCSCs). LPCs can differentiate into both hepatocytes and cholangiocytes. However, the mechanism underlying cell conversion and its distinct contribution to liver homeostasis and tumorigenesis remain unclear. In this review, we discuss the complicated conversions involving LPCs and LCSCs. As the critical intermediate state in malignant transformation, LPCs play double-edged sword roles. LPCs are not only involved in hepatic wound-healing responses by supplementing liver cells and bile duct cells in the damaged liver but may transform into LCSCs under dysregulation of key signaling pathways, resulting in refractory malignant liver tumors. Because LPC lineages are temporally and spatially dynamic, we discuss crucial LPC subgroups and summarize regulatory factors correlating with the trajectories of LPCs and LCSCs in the liver tumor microenvironment. This review elaborates on the double-edged sword roles of LPCs to help understand the liver's regenerative potential and tumor heterogeneity. Understanding the sources and transformations of LPCs is essential in determining how to exploit their regenerative capacity in the future.

Technology meets TILs: Deciphering T cell function in the -omics era

T cells are at the center of cancer immunology because of their ability to recognize mutations in tumor cells and directly mediate cancer cell killing. Immunotherapies to rejuvenate exhausted T cell responses have transformed the clinical management of several malignancies. In parallel, the development of novel multidimensional analysis platforms, such as single-cell RNA sequencing and high-dimensional flow cytometry, has yielded unprecedented insights into immune cell biology. This convergence has revealed substantial heterogeneity of tumor-infiltrating immune cells in single tumors, across tumor types, and among individuals with cancer. Here we discuss the opportunities and challenges of studying the complex tumor microenvironment with -omics technologies that generate vast amounts of data, highlighting the opportunities and limitations of these technologies with a particular focus on interpreting high-dimensional studies of CD8+ T cells in the tumor microenvironment.

Engineering cytokine therapeutics

Cytokines have pivotal roles in immunity, making them attractive as therapeutics for a variety of immune-related disorders. However, the widespread clinical use of cytokines has been limited by their short blood half-lives and severe side effects caused by low specificity and unfavourable biodistribution. Innovations in bioengineering have aided in advancing our knowledge of cytokine biology and yielded new technologies for cytokine engineering. In this Review, we discuss how the development of bioanalytical methods, such as sequencing and high-resolution imaging combined with genetic techniques, have facilitated a better understanding of cytokine biology. We then present an overview of therapeutics arising from cytokine re-engineering, targeting and delivery, mRNA therapeutics and cell therapy. We also highlight the application of these strategies to adjust the immunological imbalance in different immune-mediated disorders, including cancer, infection and autoimmune diseases. Finally, we look ahead to the hurdles that must be overcome before cytokine therapeutics can live up to their full potential.

Development of Spectral Imaging Cytometry

Spectral flow cytometry is a new technology that enables measurements of fluorescent spectra and light scattering properties in diverse cellular populations with high precision. Modern instruments allow simultaneous determination of up to 40+ fluorescent dyes with heavily overlapping emission spectra, discrimination of autofluorescent signals in the stained specimens, and detailed analysis of diverse autofluorescence of different cells-from mammalian to chlorophyll-containing cells like cyanobacteria. In this paper, we review the history, compare modern conventional and spectral flow cytometers, and discuss several applications of spectral flow cytometry.

Using mass cytometry for the analysis of samples of the human airways

Mass cytometry (MC) is a powerful method for mapping complex cellular systems at single-cell levels, based on the detection of cellular proteins. Numerous studies have been performed using human blood, but there is a lack of protocols describing the processing and labeling of bronchoalveolar lavage fluid (BALF) and nasal polyps (NP) for acquisition by MC. These specimens are essential in the investigation of immune cell characteristics in airway diseases such as asthma and chronic rhinosinusitis with NP (CRSwNP). Here we optimized a workflow for processing, labeling, and acquisition of BALF and NP cells by MC. Among three methods tested for NP digestion, combined enzymatic/mechanical processing yielded maximum cell recovery, viability and labeling patterns compared to the other methods. Treatment with DNAse improved sample acquisition by MC. In a final step, we performed a comparison of blood, BALF and NP cell composition using a 31-marker MC antibody panel, revealing expected differences between the different tissue but also heterogeneity among the BALF and NP samples. We here introduce an optimized workflow for the MC analysis of human NP and BALF, which enables comparative analysis of different samples in larger cohorts. A deeper understanding of immune cell characteristics in these samples may guide future researchers and clinicians to a better disease management.

Emerging insights and challenges for understanding T cell function through the proteome

T cells rapidly transition from a quiescent state into active proliferation and effector function upon exposure to cognate antigen. These processes are tightly controlled by signal transduction pathways that influence changes in chromatin remodeling, gene transcription, and metabolism, all of which collectively drive specific T cell memory or effector cell development. Dysregulation of any of these events can mediate disease and the past several years has shown unprecedented novel approaches to understand these events, down to the single-cell level. The massive explosion of sequencing approaches to assess the genome and transcriptome at the single cell level has transformed our understanding of T cell activation, developmental potential, and effector function under normal and various disease states. Despite these advances, there remains a significant dearth of information regarding how these events are translated to the protein level. For example, resolution of protein isoforms and/or specific post-translational modifications mediating T cell function remains obscure. The application of proteomics can change that, enabling significant insights into molecular mechanisms that regulate T cell function. However, unlike genomic approaches that have enabled exquisite visualization of T cell dynamics at the mRNA and chromatin level, proteomic approaches, including those at the single-cell level, has significantly lagged. In this review, we describe recent studies that have enabled a better understanding of how protein synthesis and degradation change during T cell activation and acquisition of effector function. We also highlight technical advances and how these could be applied to T cell biology. Finally, we discuss future needs to expand upon our current knowledge of T cell proteomes and disease.

Mass Spectrometric-Based Proteomics for Biomarker Discovery in Osteosarcoma: Current Status and Future Direction

Due to a lack of novel therapies and biomarkers, the clinical outcomes of osteosarcoma patients have not significantly improved for decades. The advancement of mass spectrometry (MS), peptide quantification, and downstream pathway analysis enables the investigation of protein profiles across a wide range of input materials, from cell culture to long-term archived clinical specimens. This can provide insight into osteosarcoma biology and identify candidate biomarkers for diagnosis, prognosis, and stratification of chemotherapy response. In this review, we provide an overview of proteomics studies of osteosarcoma, indicate potential biomarkers that might be promising therapeutic targets, and discuss the challenges and opportunities of mass spectrometric-based proteomics in future osteosarcoma research.