Mass cytometry: a highly multiplexed single-cell technology for advancing drug development

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.

Platinum-Chimeric Carrier Cells for Ultratrace Cell Analysis in Mass Cytometry

Mass cytometry by time-of-flight (CyTOF), a high-dimensional single-cell analysis platform, detects up to 50 biomarkers at single-cell resolution. However, CyTOF analysis of biological samples with a minimal number of available cells or rare cell subsets remains a major technical challenge due to the extensive loss of cells during cell recovery, staining, and acquisition. Here, we introduce a platinum-chimeric carrier cell strategy for mass cytometry profiling of ultratrace cell samples. Cisplatin can rapidly enter broken plasma membranes of dead cells and form a chimeric interaction with cellular proteins, peptides, and amino acids. Thus, 198Pt-cisplatin is adopted to tag carrier cells in the pretreatment stage. We investigated 8 cell lines that are commonly accessible in laboratories for their potential as carrier cells to preserve rare target cells for CyTOF analysis. We designed a panel of 35 protein biomarkers to evaluate the comprehensive single-cell subtype classification capability with or without the carrier cell strategy. We further demonstrated the detection and analysis of as few as 1 × 104 immune cells using our method. The proposed method thus allows CyTOF analysis on precious clinical samples with less abundant cells.

High-Dimensional Mass Cytometry Analysis of Embryonic Antigens and Their Signaling Pathways in Myeloid Cells from Bone Marrow Aspirates in AML Patients at Diagnosis

BACKGROUND

Embryonic antigens (EA) regulate pluripotency, self-renewal, and differentiation in embryonic stem (ES) cells during their development. In adult somatic cells, EA expression is normally inhibited; however, EAs can be re-expressed by cancer cells and are involved in the deregulation of different signaling pathways (SPs). In the context of AML, data concerning the expression of EAs are scarce and contradictory.

METHODS

We used mass cytometry to explore the expression of EAs and three SPs in myeloid cells from AML patients and normal bone marrow (NBM). Imaging flow cytometry was used for morphological assessment of cells in association with their OCT3/4 expression status (positive vs. negative).

RESULTS

An overall reduction in or absence of EA expression was observed in immature myeloid cells from AML patients compared to their normal counterparts. Stage-specific embryonic antigen-3 (SSEA-3) was consistently expressed at low levels in immature myeloid cells, whereas SSEA-1 was overexpressed in hematopoietic stem cells (HSCs) and myeloblasts from AML with monocytic differentiation (AML M4/M5). Therefore, these markers are valuable for distinguishing between normal and abnormal myeloid cells. These preliminary results show that the exploration of myeloid cell intracellular SPs in the setting of AML is very informative. Deregulation of three important leukemogenic SPs was also observed in myeloid cells from AML.

CONCLUSIONS

Exploring EAs and SPs in myeloid cells from AML patients by mass cytometry may help identify characteristic phenotypes and facilitate AML follow-up.

Untangling the web of glioblastoma treatment resistance using a multi-omic and multidisciplinary approach

Glioblastoma (GBM), the most common human brain tumor, has been notoriously resistant to treatment. As a result, the dismal overall survival of GBM patients has not changed over the past three decades. GBM has been stubbornly resistant to checkpoint inhibitor immunotherapies, which have been remarkably effective in the treatment of other tumors. It is clear that GBM resistance to therapy is multifactorial. Although therapeutic transport into brain tumors is inhibited by the blood brain barrier, there is evolving evidence that overcoming this barrier is not the predominant factor. GBMs generally have a low mutation burden, exist in an immunosuppressed environment and they are inherently resistant to immune stimulation, all of which contribute to treatment resistance. In this review, we evaluate the contribution of multi-omic approaches (genomic and metabolomic) along with analyzing immune cell populations and tumor biophysical characteristics to better understand and overcome GBM multifactorial resistance to treatment.

Unravelling human hematopoietic progenitor cell diversity through association with intrinsic regulatory factors

Hematopoietic stem and progenitor cell (HSPC) transplantation is an essential therapy for hematological conditions, but finer definitions of human HSPC subsets with associated function could enable better tuning of grafts and more routine, lower-risk application. To deeply phenotype HSPCs, following a screen of 328 antigens, we quantified 41 surface proteins and functional regulators on millions of CD34+ and CD34- cells, spanning four primary human hematopoietic tissues: bone marrow, mobilized peripheral blood, cord blood, and fetal liver. We propose more granular definitions of HSPC subsets and provide new, detailed differentiation trajectories of erythroid and myeloid lineages. These aspects of our revised human hematopoietic model were validated with corresponding epigenetic analysis and in vitro clonal differentiation assays. Overall, we demonstrate the utility of using molecular regulators as surrogates for cellular identity and functional potential, providing a framework for description, prospective isolation, and cross-tissue comparison of HSPCs in humans.

Mass cytometry for the multiplexed quantification and characterization of target expression on circulating cells in whole blood

Characterization of target abundance on cells has broad translational applications. Among the approaches for assessing membrane target expression is quantification of the number of target-specific antibody (Ab) bound per cell (ABC). ABC determination on relevant cell subsets in complex and limited biological samples necessitates multidimensional immunophenotyping, for which the high-order multiparameter capabilities of mass cytometry provide considerable advantages. In the present study, we describe the implementation of CyTOF® for the concomitant quantification of membrane markers on diverse types of immune cells in human whole blood. Specifically, our protocol relies on establishing Bmax of Ab saturable binding on cells, then converted into ABC according to a metal's transmission efficiency and number of metal atoms per Ab. Using this method, we calculated ABC values for CD4 and CD8 within the expected range for circulating T cells and in concordance with the ABC obtained in the same samples by flow cytometry. Furthermore, we successfully conducted multiplex measurements of the ABC for CD28, CD16, CD32a, and CD64, on >15 immune cell subsets in human whole blood samples. We developed a high-dimensional data analysis workflow enabling semi-automated Bmax calculation in all examined cell subsets to facilitate ABC reporting across populations. In addition, we investigated impacts of the type of metal isotope and acquisition batch effect on the ABC evaluation with CyTOF®. In summary, our findings demonstrate mass cytometry is a valuable tool for concurrent quantitative analysis of multiple targets in specific and rare cell types, thus increasing the numbers of biomeasures obtained from a single sample.

Histochemistry in Advanced Cytometry: From Fluorochromes to Mass Probes

For over half a century, fluorescence has been the milestone of most of the quantitative approaches in various fields from chemistry and biochemistry to microscopy. This latter also evolved into cytometry, thanks to the development of fluorescence techniques. The dyes of classical cytochemistry were replaced by fluorochromes, and the pioneer microphotometry was replaced by microfluorometry. The latter has great advantages in terms of simplicity, sensitivity, and accuracy. The extensive research and availability of new fluorochromes as well as the technological evolution contributed to the success of microfluorometry. The development of flow cytometry in the 1960s gave a giant boost to cell analysis and in particular to the clinical diagnostics. The synergy between flow cytometry and the subsequent development of monoclonal antibodies allowed the setup of multiparametric analytical panels that are today popular and irreplaceable in many clinical and research laboratories. Multiparametric analysis has required the application of an increasing number of fluorochromes, but their simultaneous use creates problems of mutual contamination, hence the need to develop new fluorescent probes. Semiconductor and nanotechnology research enabled the development of new probes called nanocrystals or quantum dots, which offered great advantages to the multiparametric analysis: in fact, thanks to their spectrofluorometric peculiarities, dozens of quantum dots may be simultaneously used without appreciable crosstalk between them. New analytical horizons in cytometry seem to be associated with a new concept of analysis that replaces fluorescence toward new markers with (non-radiative) isotopes of heavy metals. Thus, the mass flow cytometry was born, which seems to guarantee the simultaneous compensation-free analysis of up to 100 markers on a single sample aliquot.

Full spectrum flow cytometry and mass cytometry: A 32-marker panel comparison

High-dimensional single-cell data has become an important tool in unraveling the complexity of the immune system and its involvement in homeostasis and a large array of pathologies. As technological tools are developed, researchers are adopting them to answer increasingly complex biological questions. Up until recently, mass cytometry (MC) has been the main technology employed in cytometric assays requiring more than 29 markers. Recently, however, with the introduction of full spectrum flow cytometry (FSFC), it has become possible to break the fluorescence barrier and go beyond 29 fluorescent parameters. In this study, in collaboration with the Stanford Human Immune Monitoring Center (HIMC), we compared five patient samples using an established immune panel developed by the HIMC using their MC platform. Using split samples and the same antibody panel, we were able to demonstrate highly comparable results between the two technologies using multiple data analysis approaches. We report here a direct comparison of two technology platforms (MC and FSFC) using a 32-marker flow cytometric immune monitoring panel that can identify all the previously described and anticipated immune subpopulations defined by this panel.

DGCyTOF: Deep learning with graphic cluster visualization to predict cell types of single cell mass cytometry data

Single-cell mass cytometry, also known as cytometry by time of flight (CyTOF) is a powerful high-throughput technology that allows analysis of up to 50 protein markers per cell for the quantification and classification of single cells. Traditional manual gating utilized to identify new cell populations has been inadequate, inefficient, unreliable, and difficult to use, and no algorithms to identify both calibration and new cell populations has been well established. A deep learning with graphic cluster (DGCyTOF) visualization is developed as a new integrated embedding visualization approach in identifying canonical and new cell types. The DGCyTOF combines deep-learning classification and hierarchical stable-clustering methods to sequentially build a tri-layer construct for known cell types and the identification of new cell types. First, deep classification learning is constructed to distinguish calibration cell populations from all cells by softmax classification assignment under a probability threshold, and graph embedding clustering is then used to identify new cell populations sequentially. In the middle of two-layer, cell labels are automatically adjusted between new and unknown cell populations via a feedback loop using an iteration calibration system to reduce the rate of error in the identification of cell types, and a 3-dimensional (3D) visualization platform is finally developed to display the cell clusters with all cell-population types annotated. Utilizing two benchmark CyTOF databases comprising up to 43 million cells, we compared accuracy and speed in the identification of cell types among DGCyTOF, DeepCyTOF, and other technologies including dimension reduction with clustering, including Principal Component Analysis (PCA), Factor Analysis (FA), Independent Component Analysis (ICA), Isometric Feature Mapping (Isomap), t-distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP) with k-means clustering and Gaussian mixture clustering. We observed the DGCyTOF represents a robust complete learning system with high accuracy, speed and visualization by eight measurement criteria. The DGCyTOF displayed F-scores of 0.9921 for CyTOF1 and 0.9992 for CyTOF2 datasets, whereas those scores were only 0.507 and 0.529 for the t-SNE+k-means; 0.565 and 0.59, for UMAP+ k-means. Comparison of DGCyTOF with t-SNE and UMAP visualization in accuracy demonstrated its approximately 35% superiority in predicting cell types. In addition, observation of cell-population distribution was more intuitive in the 3D visualization in DGCyTOF than t-SNE and UMAP visualization. The DGCyTOF model can automatically assign known labels to single cells with high accuracy using deep-learning classification assembling with traditional graph-clustering and dimension-reduction strategies. Guided by a calibration system, the model seeks optimal accuracy balance among calibration cell populations and unknown cell types, yielding a complete and robust learning system that is highly accurate in the identification of cell populations compared to results using other methods in the analysis of single-cell CyTOF data. Application of the DGCyTOF method to identify cell populations could be extended to the analysis of single-cell RNASeq data and other omics data.

Recent progress in cytometric technologies and their applications in ecotoxicology and environmental risk assessment

Environmental toxicology focuses on identifying and predicting impact of potentially toxic anthropogenic chemicals on biosphere at various levels of biological organization. Presently there is a significant drive to gain deeper understanding of cellular and sub-cellular mechanisms of ecotoxicity. Most notable is increased focus on elucidation of cellular-response networks, interactomes, and greater implementation of cell-based biotests using high-throughput procedures, while at the same time decreasing the reliance on standard animal models used in ecotoxicity testing. This is aimed at discovery and interpretation of molecular pathways of ecotoxicity at large scale. In this regard, the applications of cytometry are perhaps one of the most fundamental prospective analytical tools for the next generation and high-throughput ecotoxicology research. The diversity of this modern technology spans flow, laser-scanning, imaging, and more recently, Raman as well as mass cytometry. The cornerstone advantages of cytometry include the possibility of multi-parameter measurements, gating and rapid analysis. Cytometry overcomes, thus, limitations of traditional bulk techniques such as spectrophotometry or gel-based techniques that average the results from pooled cell populations or small model organisms. Novel technologies such as cell imaging in flow, laser scanning cytometry, as well as mass cytometry provide innovative and tremendously powerful capabilities to analyze cells, tissues as well as to perform in situ analysis of small model organisms. In this review, we outline cytometry as a tremendously diverse field that is still vastly underutilized and often largely unknown in environmental sciences. The main motivation of this work is to highlight the potential and wide-reaching applications of cytometry in ecotoxicology, guide environmental scientists in the technological aspects as well as popularize its broader adoption in environmental risk assessment.

A Silica Coating Approach to Enhance Bioconjugation on Metal-Encoded Polystyrene Microbeads for Bead-Based Assays in Mass Cytometry

Bead-based assays in flow cytometry are multiplexed analytical techniques that allow rapid and simultaneous detection and quantification of a large number of analytes from small volumes of samples. The development of corresponding bead-based assays in mass cytometry (MC) is highly desirable since it could increase the number of analytes detected in a single assay. The microbeads for these assays have to be labeled with metal isotopes for MC detection. One must also be able to functionalize the bead surface with affinity reagents to capture the analytes. Metal-encoded polystyrene microbeads prepared by multi-stage dispersion polymerization can produce effective isotopic signals in MC with relatively small bead-to-bead variations. However, functionalizing this microbead surface with bioaffinity agents remains challenging, possibly due to the interference of the steric-stabilizing PVP corona on the microbead surface. Here, we report a systematic investigation of a silica coating approach to coat Eu-encoded microbeads with thin silica shells, to functionalize the surface with amino groups, and to introduce bioaffinity agents. We examine the effect of silica shell roughness on the bioconjugation capacity and the effect of silica shell thickness on signal quality in MC measurements. To limit non-specific binding, we converted the amino groups on the microbead surface to carboxylic acid groups. Antibodies were effectively attached to microbead by first conjugating NeutrAvidin to the carboxyl-modified bead surface and then attaching biotinylated antibodies to the NeutrAvidin-modified bead surface. The antibody-modified microbeads can specifically capture antigens, which were marked with isotopic labels, and generate strong signals in MC. These are promising results for the development of bead-based assays in MC.

Evolution and Diversity of Immune Responses during Acute HIV Infection

Understanding the earliest immune responses following HIV infection is critical to inform future vaccines and therapeutics. Here, we review recent prospective human studies in at-risk populations that have provided insight into immune responses during acute infection, including additional relevant data from non-human primate (NHP) studies. We discuss the timing, nature, and function of the diverse immune responses induced, the onset of immune dysfunction, and the effects of early anti-retroviral therapy administration. Treatment at onset of viremia mitigates peripheral T and B cell dysfunction, limits seroconversion, and enhances cellular antiviral immunity despite persistence of infection in lymphoid tissues. We highlight pertinent areas for future investigation, and how application of high-throughput technologies, alongside targeted NHP studies, may elucidate immune response features to target in novel preventions and cures.

Immunologic goalposts for TB vaccine development

A limiting factor in identifying effective tuberculosis (TB) vaccines is our incomplete understanding of correlates of protection. In this issue of Cell Host & Microbe, Esaulova et al. reveal cell types associated with TB containment and disease progression in non-human primates, which may provide immunologic goalposts for vaccine design.

Characterizing Highly Cited Papers in Mass Cytometry through H-Classics

Mass cytometry (CyTOF) is a relatively novel technique for the multiparametric analysis of single-cell features with an increasing central role in cell biology, immunology, pharmacology, and biomedicine. This technique mixes the fundamentals of flow cytometry with mass spectrometry and is mainly used for in-depth studies of the immune system and diseases with a significant immune load, such as cancer, autoimmune diseases, and viral diseases like HIV or the recently emerged COVID-19, produced by the SARS-CoV-2 coronavirus. The objective of this study was to provide a useful insight into the evolution of the mass cytometry research field, revealing the knowledge structure (conceptual and social) and authors, countries, sources, documents, and organizations that have made the most significant contribution to its development. We retrieved 937 articles from the Web of Science (2010-2019), analysed 71 Highly Cited Papers (HCP) through the H-Classics methodology and computed the data by using Bibliometrix R package. HCP sources corresponded to high-impact journals, such as Nature Biotechnology and Cell, and its production was concentrated in the US, and specifically Stanford University, affiliation of the most relevant authors in the field. HCPs analysis confirmed great interest in the study of the immune system and complex data processing in the mass cytometry research field.

[Methods and applications of single-cell proteomics analysis based on mass spectrometry]

The cell is the smallest unit of living organisms. Although cells often assemble to serve a common function, intercellular heterogeneity often exists due to different genetic and environmental effects. Therefore, single-cell analysis has been regarded as an indispensable means to investigate cell heterogeneity, especially when researching cell differentiation, disease diagnosis, and therapy. As the chief factors influencing cell and biological activities, proteins have long been a major concern in biochemistry. However, due to their intrinsic lack of amplification characteristics, wide species variety, low abundance, and wide dynamic range, proteins are scarcely studied in single-cell research when compared with other biological macromolecules. Therefore, ultra-sensitive single-cell proteomics analysis methods are urgently required. Among all general measurement techniques, fluorescence methods possess high sensitivity and a capability of dynamic tracing, but low target numbers impose restrictions on their broad application in real "proteomic" studies. Similarly, electrochemical methods adapt to electrochemically active molecules, which miss the majority of proteins. Mass spectrometry (MS), as the core approach of proteomic studies, provides high-sensitivity and high-throughput analysis of proteins together with abundant structural information, which is unique in all the analytical instruments and has made great progress in single-cell proteomic research. Herein, the representative research methods for single-cell proteomics based on MS are reviewed. According to the different protein separation methods used prior to MS analysis, they are divided into three categories, including capillary electrophoresis (CE), liquid chromatography (LC), and direct infusion without the need for separation. First, CE has been widely used in the separation and analysis of complex biological samples owing to its low cost, high analysis speed, and high separation efficiency. Its unique feature is the extraction and transfer of contents from cellular or subcellular regions using capillaries smaller than a single cell size. This sampling method also offers less substrate interference and negligible oxidative damage to the cells. Nonetheless, single-cell analysis based on CE-MS mainly focuses on proteomic studies of large cells because of the considerable sample loss, interface instability, and reproducibility issues. Compared with CE, LC, especially nanoLC, is more widely used in single-cell proteomic research, which mainly depends on its good reproducibility, nanoliter injection volume, low flow rate, low sample loss, and good compatibility with mass spectrometry. In recent years, it has been increasingly applied in the study of large-volume embryos, germ cells, and even somatic cells. More than 1000 proteins have been identified in single HeLa cells using this state-of-the-art single-cell proteomics method. It is worth noting that the single-cell sampling volume based on LC gradually reduces to the nanoliter level, and that the sample loss can be reduced by integrating a series of proteomic sampling processes into small volumes, setting sealing conditions, and reducing washing steps. However, the adequacy of cell lysis, the completeness and efficiency of protein pretreatment, and the labeling of peptide segments are important factors affecting the number and types of protein identification. Compared with protein separation using CE or LC prior to MS analysis, the direct MS analysis, assisted by labelling and signal transformation, eliminates complicated sample pretreatment and simplifies the operation by reducing enzymatic hydrolysis and separation. It also renders higher resolution as well as multi-omics compatibility. So far, the number of proteins detected using this method is limited due to the complexity of the samples. In conclusion, the aspects of throughput, sensitivity, identified protein species, and applications are summarized for each method mentioned above, and the prospect of single-cell proteomic research based on MS in the future is also discussed.

Progress and applications of mass cytometry in sketching immune landscapes

Recently emerged mass cytometry (cytometry by time-of-flight [CyTOF]) technology permits the identification and quantification of inherently diverse cellular systems, and the simultaneous measurement of functional attributes at the single-cell resolution. By virtue of its multiplex ability with limited need for compensation, CyTOF has led a critical role in immunological research fields. Here, we present an overview of CyTOF, including the introduction of CyTOF principle and advantages that make it a standalone tool in deciphering immune mysteries. We then discuss the functional assays, introduce the bioinformatics to interpret the data yield via CyTOF, and depict the emerging clinical and research applications of CyTOF technology in sketching immune landscape in a wide variety of diseases.

Enabling Indium Channels for Mass Cytometry by Using Reinforced Cyclam-Based Chelating Polylysine

The synthesis of a polylysine polymer functionalized with the previously reported astonishingly inert [In(cb-te2pa)]⁺ chelate was performed. A biotin end group allowed the conjugation to biotinylated beads by the intermediary of a fluorescein isothiocyanate/neutravidin receptor. High quality imaging mass cytometry trials, based on ¹¹⁵In detection were performed to highlight the behavior of the material. Anti-CD20 antibody was labeled by the so-obtained In(III)-modified polylysine using the biotin/neutravidin interaction. Ramos (CD20[+]) and HL-60 (CD20[-]) cell lines were costained with the In(III)-modified bioconjugate by finding the best staining conditions. Both immunofluorescence microscopy (IF-M) and mass cytometry analyses confirmed the specific binding of anti-CD20 onto Ramos cells. CyTOF histograms constructed on the ¹¹⁵In detection allowed us to define and to separate, with a good signal-to-noise ratio, two populations (Ramos and HL-60). The inertness of In(III)-MCP-NAv over a three-month storage period was proved by performing new functionality tests involving Jurkat cells (CD20[-]) and multiparametric trials involving the ¹¹⁵In channel. The results ensure a promising future use of the previously announced [In(cb-te2pa)]⁺ complex-based polymers for mass cytometry.

Deep Profiling of Cellular Heterogeneity by Emerging Single-Cell Proteomic Technologies

The ability to comprehensively profile cellular heterogeneity in functional proteome is crucial in advancing the understanding of cell behavior, organism development, and disease mechanisms. Conventional bulk measurement by averaging the biological responses across a population often loses the information of cellular variations. Single-cell proteomic technologies are becoming increasingly important to understand and discern cellular heterogeneity. The well-established methods for single-cell protein analysis based on flow cytometry and fluorescence microscopy are limited by the low multiplexing ability owing to the spectra overlap of fluorophores for labeling antibodies. Recent advances in mass spectrometry (MS), microchip, and reiterative staining-based techniques for single-cell proteomics have enabled the evaluation of cellular heterogeneity with high throughput, increased multiplexity, and improved sensitivity. In this review, the principles, developments, advantages, and limitations of these advanced technologies in analysis of single-cell proteins, along with their biological applications to study cellular heterogeneity, are described. At last, the remaining challenges, possible strategies, and future opportunities that will facilitate the improvement and broad applications of single-cell proteomic technologies in cell biology and medical research are discussed.

In-Line Sample Processing System with an Immobilized Trypsin-Packed Fused-Silica Capillary Tube for the Proteomic Analysis of a Small Number of Mammalian Cells

Omics analysis at single-cell resolution has helped to demonstrate the shaping of cellular heterogeneity on the basis of the expression of various molecules. However, in-depth proteomic analysis of low-quantity samples has remained challenging because of difficulties associated with the measurement of large numbers of proteins by shotgun proteomics using nanoflow liquid chromatography tandem mass spectrometry (nano-LC/MS/MS). To meet such a demand, we developed a method called in-line sample preparation for efficient cellular proteomics (ISPEC) in which cells were captured, directly lysed, and digested with immobilized trypsin within fused-silica capillaries. ISPEC minimized sample loss during the sample preparation processes with a relatively small number of mammalian cells (<1000 cells) and improved the stability and efficiency of digestion by immobilized trypsin, compared to a conventional preparation method. Using our optimized ISPEC method with nano-LC/MS/MS analysis, we identified 1351, 351, and 60 proteins from 100 cells, 10 cells, and single cells, respectively. The linear response of the signal intensity of each peptide to the introduced cell number indicates the quantitative recovery of the proteome from a very small number of cells. Thus, our ISPEC strategy facilitates quantitative proteomic analysis of small cell populations.

A Carrier Strategy for Mass Cytometry Analysis of Small Numbers of Cells

The recent launch of mass cytometry or cytometry by time of flight (CyTOF) has revolutionized flow cytometry. Similar to fluorescence flow cytometry, a key challenge for CyTOF is to analyze samples of limited amount or very rare cell populations under various experimental settings. Here we describe a carrier strategy that significantly reduces the required sample amount without losing analytical resolution. We were able to detect as few as 5 × 10⁴ human peripheral blood mononuclear cells (PBMCs) using this method. This simple method thus enables the maximal usage of valuable clinical samples.

High-dimensional single-cell proteomics analysis reveals the landscape of immune cells and stem-like cells in renal tumors

Background

Renal tumors are highly heterogeneous, and identification of tumor heterogeneity is an urgent clinical need for effective treatment. Mass cytometry (MC) can be used to perform high‐dimensional single‐cell proteomics analysis of heterogeneous samples via cytometry by time‐of‐flight (CyTOF), in order to achieve more accurate observation and classification of phenotypes within a cell population. This study aimed to develop a high‐dimensional MC method for the detection and analysis of heterogeneity in renal tumors.

Materials and Methods

We collected tissue samples from 8 patients with different types of renal tumors. Single‐cell suspensions were prepared and stained using a panel of 28 immune cell‐centric antibodies and a panel of 21 stem‐like cell‐centric antibodies. The stained cells were detected using CyTOF.

Result

Renal tumors were divided into 25 immune cell subsets (4 CD4+ T cells, 7 CD8+ T cells, 1 B cells, 8 macrophages, 1 dendritic cells, 2 natural killer (NK) cells, 1 granulocyte, and 1 other subset) and 7 stem‐like cells subsets (based on positivity of vimentin, CD326, CD34, CD90, CD13, CD44, and CD47). Different types of renal tumors have different cell subsets with significantly different characteristics.

Conclusion

High‐dimensional single‐cell proteomics analysis using MC aids in the discovery and analysis of renal tumors heterogeneity. Additionally, it can be used to accurately classify the immune cell population and analyze the expression of stem cell‐related markers in renal tumors. Our findings provide a valuable resource for deciphering tumor heterogeneity and might improve the clinical management of patients with renal tumors.

Metal-Encoded Polystyrene Microbeads as a Mass Cytometry Calibration/Normalization Standard Covering Channels from Yttrium (89 amu) to Bismuth (209 amu)

Mass cytometry (MC) measures metal isotope signals from single cells and bead samples. Since large numbers of isotopes can be employed as labels, mass cytometry is a powerful analytical technique for multiparameter cytometric assays. The calibration protocol in MC is a critical algorithm, which employs metal-encoded microbeads as an internal standard to correct the data for instrumental signal drift. The current generation of commercially available beads carries four lanthanide elements (cerium, europium, holmium, and lutetium). However, this is not sufficient to calibrate the full span of detection channels, ranging from yttrium (89 amu) to bismuth (209 amu), which are now available. To address this issue we prepared polystyrene microbeads encoded with seven elements (yttrium, indium, and bismuth in addition to the four lanthanides) by multistage dispersion polymerization for MC calibration and normalization. The bead synthesis conditions were optimized to obtain microbeads that were uniform in size and generated strong MC signal intensities at similar levels for the eight encoded isotopes. Metal ion leaching from the beads under storage and application conditions was also examined. We demonstrated that the precision of normalized MC signals in the MC detection channels was improved by employing seven-element-encoded microbeads as a standard.

Profiling protein-protein interactions of single cancer cells with in situ lysis and co-immunoprecipitation

Heterogeneity in a tumor allows a small portion of cancer cells to survive and regrow upon targeted cancer therapy, eventually leading to cancer relapse. Such drug-resistant cells often exhibit dynamic adaptation of their signaling pathways at the level of protein-protein interactions (PPIs). To probe the rewiring of signaling pathways and the heterogeneity across individual cancer cells, we developed a single-cell version of the co-immunoprecipitation (co-IP) analysis that examines the amount and PPIs of target proteins immunoprecipitated from individual cells. The method captures cancer cells at predefined locations using a microfluidic chip, pulls down target proteins on the surface using antibodies, and lyses the captured cells in situ. Then, subsequent addition of eGFP-labeled downstream proteins enables the determination of the corresponding PPIs for the minimal amount of target proteins sampled from a single cell. We applied the technique to probe epidermal growth factor receptors (EGFRs) in PC9 lung adenocarcinoma cells. The results reveal that the strength of EGFR PPIs can be largely uncorrelated with the expression level of EGFRs in single cells. In addition, the individual PC9 cells showed markedly different patterns of PPIs, indicating a high heterogeneity in EGFR signaling within a genetically homogeneous population.

RNA-Seq Signatures Normalized by mRNA Abundance Allow Absolute Deconvolution of Human Immune Cell Types

The molecular characterization of immune subsets is important for designing effective strategies to understand and treat diseases. We characterized 29 immune cell types within the peripheral blood mononuclear cell (PBMC) fraction of healthy donors using RNA-seq (RNA sequencing) and flow cytometry. Our dataset was used, first, to identify sets of genes that are specific, are co-expressed, and have housekeeping roles across the 29 cell types. Then, we examined differences in mRNA heterogeneity and mRNA abundance revealing cell type specificity. Last, we performed absolute deconvolution on a suitable set of immune cell types using transcriptomics signatures normalized by mRNA abundance. Absolute deconvolution is ready to use for PBMC transcriptomic data using our Shiny app (https://github.com/giannimonaco/ABIS). We benchmarked different deconvolution and normalization methods and validated the resources in independent cohorts. Our work has research, clinical, and diagnostic value by making it possible to effectively associate observations in bulk transcriptomics data to specific immune subsets.

Strategies and Techniques for NK Cell Phenotyping

Therapies based on activating the immune system, that is, immunotherapy, are now widely implemented in clinical praxis in patients with advanced cancer. Although cancer immunotherapy can result in long-lasting clinical responses, the majority of patients do not respond or develop resistance. Furthermore, cancer immunotherapy is being increasingly combined with other forms of immunotherapy or conventional cancer therapies. It is therefore much needed to identify biomarkers that can precisely classify what patients will benefit from the treatment without any major adverse events and to further develop the efficacy of cancer immunotherapy. While much attention has been focused on monitoring T cell responses in cancer immunotherapy, recent reports have shown that NK cells also play a major role in the response to cancer immunotherapy. The gold standard for immunoprofiling of NK cells is flow cytometry, but other technologies have emerged and include mass cytometry, multiplex immunohistochemistry, and single-cell RNA-sequencing. In this chapter we provide a detailed protocol to profile NK cells using flow cytometry, and a brief introduction to other techniques.

Prognosis, Prevention and Research Prospects of Progression to Severe Hepatitis B (Liver Failure)

This chapter describes the factors involved in the disease prognosis, parameters of outcome evaluations, principles and techniques for progression prevention. In last section, the future perspectives in both basic and clinical investigations towards unmet medical needs in AECHB and HBV ACLF are discussed.

Factors affecting the prognosis of patients with severe hepatitis B include those related to the virus (including viral load, HBeAg expression, and gene mutation), patient age, co-morbidity, TBil, INR, serum Cr, and the host genetic background. Indicators associated with patient prognosis include TBil, total cholesterol, albumin and prealbumin, hepatic encephalopathy, kidney damage, alpha-fetoprotein and vitamin D binding protein, blood sodium level, virus HBeAg expression and genotype, and blood glucose.

In addition to TBil, INR, hepatic encephalopathy, Cr level and AFP as indicators for prognosis of severe hepatitis, some other parameters such as clinical signs, symptoms, serum levels of total cholesterol and albumin and natrium, and coagulation factors are all valuable in assessment. The roles of cell apoptosis, liver regeneration and immunological parameters in assessing patient prognosis are under study. Prognostic evaluating systems include MELD score, MELD-Na score, iMELD score, KCI and CTP score.

Prevention of severe hepatitis B should be started in asymptomatic patients. Close observation, sufficient rest, adequate nutrition, meticulous nursing and psychological care, preventing and removing exacerbating factors, treating concomitant diseases, reasonable antiviral and comprehensive therapies are helpful to prevent CHB patients from developing to severe hepatitis. For patients who already have severe hepatitis B, the prevention and management of complications is important for lowering mortality rate.

New research directions in acute-on-chronic liver failure include: (1) Additional well controlled studies using present or new liver systems are warranted. Other approaches include the use of granulocyte colony stimulating factor to treat infections as well as the potential of use of stem cells to restore immune integrity and enhance liver regeneration. (2) Using new cell lines and animal models to understand the molecular biology of HBV, the immune response and to develop novel therapies. (3) Development of new anti-HBV strategies, e.g. silencing or remove cccDNA, enhancing immunologic clearance of HBV infection, inhibiting virus entry or HBc expression and using CRISP to disrupt cccDNA.

Metal-isotope-tagged monoclonal antibodies for high-dimensional mass cytometry

Advances in single-cell mass cytometry have increasingly improved highly multidimensional characterization of immune cell heterogeneity. The immunoassay multiplexing capacity relies on monoclonal antibodies labeled with stable heavy-metal isotopes. To date, a variety of rare-earth elements and noble and post-transition metal isotopes have been used in mass cytometry; nevertheless, the methods used for antibody conjugation differ because of the individual metal coordination chemistries and distinct stabilities of various metal cations. Herein, we provide three optimized protocols for conjugating monoclonal IgG antibodies with 48 high-purity heavy-metal isotopes: (i) 38 isotopes of lanthanides, 2 isotopes of indium, and 1 isotope of yttrium; (ii) 6 isotopes of palladium; and (iii) 1 isotope of bismuth. Bifunctional chelating agents containing coordinative ligands of monomeric DOTA (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid) or polymeric pentetic acid (DTPA) were used to stably sequester isotopic cations in aqueous solutions and were subsequently coupled to IgG antibodies using site-specific biorthogonal reactions. Furthermore, quantification methods based on antibody inherent absorption at 280 nm and on extrinsic absorption at 562 nm after staining with bicinchoninic acid (BCA) are reported to determine metal-isotope-tagged antibodies. In addition, a freeze-drying procedure to prepare palladium isotopic mass tags is described. To demonstrate the utility, experiments using six palladium-tagged CD45 antibodies for barcoding assays of live immune cells in cytometry by time-of-flight (CyTOF) are described. Conjugation of pure isotopes of lanthanides, indium, or yttrium takes ~3.5 h. Conjugation of bismuth takes ~4 h. Preparation of palladium mass tags takes ~8 h. Conjugation of pure isotopes of palladium takes ~2.5 h. Antibody titration takes ~4 h.

The FGFR1 V561M Gatekeeper Mutation Drives AZD4547 Resistance through STAT3 Activation and EMT

FGFR1 has been implicated in numerous cancer types including squamous cell lung cancer, a subset of non-small cell lung cancer with a dismal 5-year survival rate. Small-molecule inhibitors targeting FGFR1 are currently in clinical trials, with AZD4547 being one of the furthest along; however, the development of drug resistance is a major challenge for targeted therapies. A prevalent mechanism of drug resistance in kinases occurs through mutation of the gatekeeper residue, V561M in FGFR1; however, mechanisms underlying V561M resistance to AZD4547 are not fully understood. Here, the cellular consequences of the V561M gatekeeper mutation were characterized, and it was found that although AZD4547 maintains nanomolar affinity for V561M FGFR1, based on in vitro binding assays, cells expressing V561M demonstrate dramatic resistance to AZD4547 driven by increased STAT3 activation downstream of V561M FGFR1. The data reveal that the V561M mutation biases cells toward a more mesenchymal phenotype, including increased levels of proliferation, migration, invasion, and anchorage-independent growth, which was confirmed using CyTOF, a novel single-cell analysis tool. Using shRNA knockdown, loss of STAT3 restored sensitivity of cancer cells expressing V561M FGFR1 to AZD4547. Thus, the data demonstrate that combination therapies including FGFR and STAT3 may overcome V561M FGFR1-driven drug resistance in the clinic. IMPLICATIONS: The V561M FGFR1 gatekeeper mutation leads to devastating drug resistance through activation of STAT3 and the epithelial-mesenchymal transition; this study demonstrates that FGFR1 inhibitor sensitivity can be restored upon STAT3 knockdown.

Novel therapeutic strategy for cancer and autoimmune conditions: Modulating cell metabolism and redox capacity

Dysregulation of cell metabolism and redox balance is implicated in the pathogenesis and progression of cancer and autoimmune diseases. Because the cell proliferation and apoptotic regulatory pathways are interconnected with metabolic and redox signalling pathways, the current mono-target treatment is ineffective, and multi-drug resistance remains common. Complex diseases are often implicated in a network-based context of pathology; therefore, a new holistic intervention approach is required to block multi-crosstalk in such complicated circumstances. The use of therapeutic agents isolated from herbs to holistically modulate metabolism and redox state has been shown to relieve carcinoma growth and the inflammatory response in autoimmune disorders. Multiple clinically applied or novel herbal chemicals with metabolic and redox modulatory capacity as well as low toxicity have recently been identified. Moreover, new metabolic targets and mechanisms of drug action have been discovered, leading to the exploration of new pathways for drug repositioning, clinical biomarker spectra, clinical treatment strategies and drug development. Taken together with multiple supporting examples, the modulation of cell metabolism and the redox capacity using herbal chemicals is emerging as a new, alternative strategy for the holistic treatment of cancer and autoimmune disorders. In the future, the development of new diagnostic tools based on the detection of metabolic and redox biomarkers, reformulation of optimized herbal compositions using artificial intelligence, and the combination of herbs with mono-targeting drugs will reveal new potential for clinical application.

Single-Cell Protein Assays: A Review

Quantification of single-cell proteomics provides key insights in the field of cellular heterogeneity. This chapter discusses the emerging techniques that are being used to measure the protein copy numbers at the single-cell level, which includes flow cytometry, mass cytometry, droplet cytometry, microengraving, and single-cell barcoding microchip. The advantages and limitations of each technique are compared, and future research opportunities are highlighted.

Gating mass cytometry data by deep learning

MOTIVATION

Mass cytometry or CyTOF is an emerging technology for high-dimensional multiparameter single cell analysis that overcomes many limitations of fluorescence-based flow cytometry. New methods for analyzing CyTOF data attempt to improve automation, scalability, performance and interpretation of data generated in large studies. Assigning individual cells into discrete groups of cell types (gating) involves time-consuming sequential manual steps, untenable for larger studies.

RESULTS

We introduce DeepCyTOF, a standardization approach for gating, based on deep learning techniques. DeepCyTOF requires labeled cells from only a single sample. It is based on domain adaptation principles and is a generalization of previous work that allows us to calibrate between a target distribution and a source distribution in an unsupervised manner. We show that DeepCyTOF is highly concordant (98%) with cell classification obtained by individual manual gating of each sample when applied to a collection of 16 biological replicates of primary immune blood cells, even when measured across several instruments. Further, DeepCyTOF achieves very high accuracy on the semi-automated gating challenge of the FlowCAP-I competition as well as two CyTOF datasets generated from primary immune blood cells: (i) 14 subjects with a history of infection with West Nile virus (WNV), (ii) 34 healthy subjects of different ages. We conclude that deep learning in general, and DeepCyTOF specifically, offers a powerful computational approach for semi-automated gating of CyTOF and flow cytometry data.

AVAILABILITY AND IMPLEMENTATION

Our codes and data are publicly available at https://github.com/KlugerLab/deepcytof.git.

CONTACT

yuval.kluger@yale.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Application and utility of mass cytometry in vaccine development

Mass cytometry enables highly multiplexed profiling of cellular immune responses in limited-volume samples, advancing prospects of a new era of systems immunology. The capabilities of mass cytometry offer expanded potential for deciphering immune responses to infectious diseases and to vaccines. Several studies have used mass cytometry to profile protective immune responses, both postinfection and postvaccination, although no vaccine-development program has yet systematically employed the technology from the outset to inform both candidate design and clinical evaluation. In this article, we review published mass cytometry studies relevant to vaccine development, briefly compare immune profiling by mass cytometry to other systems-level technologies, and discuss some general considerations for deploying mass cytometry in the context of vaccine development.-Reeves, P. M., Sluder, A. E., Raju Paul, S., Scholzen, A., Kashiwagi, S., Poznansky, M. C. Application and utility of mass cytometry in vaccine development.

Lanthanide-Coordinated Semiconducting Polymer Dots Used for Flow Cytometry and Mass Cytometry

Simultaneous monitoring of biomarkers as well as single-cell analyses based on flow cytometry and mass cytometry are important for investigations of disease mechanisms, drug discovery, and signaling-network studies. Flow cytometry and mass cytometry are complementary to each other; however, probes that can satisfy all the requirements for these two advanced technologies are limited. In this study, we report a probe of lanthanide-coordinated semiconducting polymer dots (Pdots), which possess fluorescence and mass signals. We demonstrated the usage of this dual-functionality probe for both flow cytometry and mass cytometry in a mimetic cell mixture and human peripheral blood mononuclear cells as model systems. The probes not only offer high fluorescence signal for use in flow cytometry, but also show better performance in mass cytometry than the commercially available counterparts.

Applying Mass Cytometry to the Analysis of Lymphoid Populations in Transplantation

Single-cell flow cytometric techniques have been indispensable to improving our understanding of the phenotype and function of immune cell subsets that are important in both rejection and tolerance after transplant. Mass cytometry, or cytometry by time of flight, is a single-cell-based platform that utilizes antibodies conjugated to rare heavy metal ions for analysis of cellular proteins by a time-of-flight mass spectrometer. This new technology allows for the evaluation of >40 simultaneous cellular parameters in a single sample because the limitation of spectral overlap, seen in conventional flow cytometry, is eliminated. In this review, we discuss the current state of mass cytometry, describe the advantages and disadvantages compared with multiparameter flow cytometry, introduce novel methods of high-dimensional data analysis and visualization, and review some recent studies using mass cytometry to profile the immune systems of healthy people and transplant recipients.

Proteomics to study macrophage response to viral infection

Viral infections are a major burden to human and animal health. Immune response against viruses consists of innate and adaptive immunity which are both critical for the eradication of the viral infection. The innate immune system is the first line of defense against viral infections. Proper innate immune response is required for the activation of adaptive, humoral and cell-mediated immunity. Macrophages are innate immune cells which have a central role in detecting viral infections including influenza A and human immunodeficiency viruses. Macrophages and other host cells respond to viral infection by modulating their protein expression levels, proteins' posttranslational modifications, as well as proteins' intracellular localization and secretion. Therefore the detailed characterization how viruses dynamically manipulate host proteome is needed for understanding the molecular mechanisms of viral infection. It is critical to identify cellular host factors which are exploited by different viruses, and which are less prone for mutations and could serve as potential targets for novel antiviral compounds. Here, we review how proteomics studies have enhanced our understanding of macrophage response to viral infection with special focus on Influenza A and Human immunodeficiency viruses, and virus infections of swine.

SIGNIFICANCE

Influenza A viruses (IAVs) and human immunodeficiency viruses (HIV) infect annually millions of people worldwide and they form a severe threat to human health. Both IAVs and HIV-1 can efficiently antagonize host response and develop drug-resistant variants. Most current antiviral drugs are directed against viral proteins, and there is a constant need to develop new next-generation drugs targeting host proteins that are essential for viral replication. Porcine reproductive and respiratory syndrome virus (PRRSV) and porcine circovirus type 2 (PCV2) are economically important swine pathogens. Both PRRSV and PCV2 cause severe respiratory tract illnesses in swine. IAVs, HIV-1, and swine viruses infect macrophages activating antiviral response against these viruses. Macrophages also have a central role in the replication and spread of these viruses. However, macrophage response to these viruses is incompletely understood. Current proteomics methods can provide a global view of host-response to viral infection which is needed for in-depth understanding the molecular mechanisms of viral infection. Here we review the current proteomics studies on macrophage response to viral infection and provide insight into the global host proteome changes upon viral infection.

Current Advances in Highly Multiplexed Antibody-Based Single-Cell Proteomic Measurements

Single-cell measurements have played a critical role in revealing the complex signaling dynamics and heterogeneity present in cells, but there is still much to learn. Measuring samples from bulk populations of cells often masks the information and dynamics present in subsets of cells. Common single-cell protein studies rely on fluorescent microscopy and flow cytometry but are limited in multiplexing ability owing to spectral overlap. Recently, technology advancements in single-cell proteomics have allowed highly multiplexed measurement of multiple parameters simultaneously by using barcoded microfluidic enzyme-linked immunosorbent assays and mass cytometry techniques. In this review, we will describe recent work around multiparameter single-cell protein measurements and critically analyze the techniques.

Mass spectrometry-based proteomic exploration of the human immune system: focus on the inflammasome, global protein secretion, and T cells

INTRODUCTION

The immune system is our defense system against microbial infections and tissue injury, and understanding how it works in detail is essential for developing drugs for different diseases. Mass spectrometry-based proteomics can provide in-depth information on the molecular mechanisms involved in immune responses. Areas covered: Summarized are the key immunology findings obtained with MS-based proteomics in the past five years, with a focus on inflammasome activation, global protein secretion, mucosal immunology, immunopeptidome and T cells. Special focus is on extracellular vesicle-mediated protein secretion and its role in immune responses. Expert commentary: Proteomics is an essential part of modern omics-scale immunology research. To date, MS-based proteomics has been used in immunology to study protein expression levels, their subcellular localization, secretion, post-translational modifications, and interactions in immune cells upon activation by different stimuli. These studies have made major contributions to understanding the molecular mechanisms involved in innate and adaptive immune responses. New developments in proteomics offer constantly novel possibilities for exploring the immune system. Examples of these techniques include mass cytometry and different MS-based imaging approaches which can be widely used in immunology.

Categorizing Cells on the Basis of their Chemical Profiles: Progress in Single-Cell Mass Spectrometry

The chemical differences between individual cells within large cellular populations provide unique information on organisms' homeostasis and the development of diseased states. Even genetically identical cell lineages diverge due to local microenvironments and stochastic processes. The minute sample volumes and low abundance of some constituents in cells hinder our understanding of cellular heterogeneity. Although amplification methods facilitate single-cell genomics and transcriptomics, the characterization of metabolites and proteins remains challenging both because of the lack of effective amplification approaches and the wide diversity in cellular constituents. Mass spectrometry has become an enabling technology for the investigation of individual cellular metabolite profiles with its exquisite sensitivity, large dynamic range, and ability to characterize hundreds to thousands of compounds. While advances in instrumentation have improved figures of merit, acquiring measurements at high throughput and sampling from large populations of cells are still not routine. In this Perspective, we highlight the current trends and progress in mass-spectrometry-based analysis of single cells, with a focus on the technologies that will enable the next generation of single-cell measurements.

Harnessing the power of proteomics for identification of oncogenic, druggable signalling pathways in cancer

INTRODUCTION

Genomic and transcriptomic profiling of tumours has revolutionised our understanding of cancer. However, the majority of tumours possess multiple mutations, and determining which oncogene, or even which pathway, to target is difficult. Proteomics is emerging as a powerful approach to identify the functionally important pathways driving these cancers, and how they can be targeted therapeutically. Areas covered: The authors provide a technical overview of mass spectrometry based approaches for proteomic profiling, and review the current and emerging strategies available for the identification of dysregulated networks, pathways, and drug targets in cancer cells, with a key focus on the ability to profile cancer kinomes. The potential applications of mass spectrometry in the clinic are also highlighted. Expert opinion: The addition of proteomic information to genomic platforms - 'proteogenomics' - is providing unparalleled insight in cancer cell biology. Application of improved mass spectrometry technology and methodology, in particular the ability to analyse post-translational modifications (the PTMome), is providing a more complete picture of the dysregulated networks in cancer, and uncovering novel therapeutic targets. While the application of proteomics to discovery research will continue to rise, improved workflow standardisation and reproducibility is required before mass spectrometry can enter routine clinical use.

Effect of cryopreservation on delineation of immune cell subpopulations in tumor specimens as determinated by multiparametric single cell mass cytometry analysis

Background

Comprehensive understanding of cellular immune subsets involved in regulation of tumor progression is central to the development of cancer immunotherapies. Single cell immunophenotyping has historically been accomplished by flow cytometry (FC) analysis, enabling the analysis of up to 18 markers. Recent advancements in mass cytometry (MC) have facilitated detection of over 50 markers, utilizing high resolving power of mass spectrometry (MS). This study examined an analytical and operational feasibility of MC for an in-depth immunophenotyping analysis of the tumor microenvironment, using the commercial CyTOF™ instrument, and further interrogated challenges in managing the integrity of tumor specimens.

Results

Initial longitudinal studies with frozen peripheral blood mononuclear cells (PBMCs) showed minimal MC inter-assay variability over nine independent runs. In addition, detection of common leukocyte lineage markers using MC and FC detection confirmed that these methodologies are comparable in cell subset identification. An advanced multiparametric MC analysis of 39 total markers enabled a comprehensive evaluation of cell surface marker expression in fresh and cryopreserved tumor samples. This comparative analysis revealed significant reduction of expression levels of multiple markers upon cryopreservation. Most notably myeloid derived suppressor cells (MDSC), defined by co-expression of CD66b⁺ and CD15⁺, HLA-DR^dim and CD14⁻ phenotype, were undetectable in frozen samples.

Conclusion

These results suggest that optimization and evaluation of cryopreservation protocols is necessary for accurate biomarker discovery in frozen tumor specimens.

Electronic supplementary material

The online version of this article (doi:10.1186/s12865-017-0192-1) contains supplementary material, which is available to authorized users.

New tools in cytometry

Cytometry aims to analyze cells, of any type, using dedicated instruments. The quantitative aspect makes flow cytometry (FCM) a good complementary tool for morphology. Most of the identification tools are based on immunostaining of cell structure details and more and more tools are available in terms of specificities and labels. FCM is under exponential development thanks to technical, immunological and data analysis progresses. Actual generations are now routinely using 6 to 10 simultaneous immuno-labeling on 20 to 100,000 cells, at high speed and short sample preparation and can easily detect rare events at frequency below 10^-4 cells. Data interpretation is complex and requires expertise. Mathematical tools are available to support analysis and classification of cells based. Cells from tissues can also be analyzed by FCM after mechanical and or enzymatic separation, but in situ cells can also be analyzed with the help of cytometry. Very new instruments bring spectral analysis, image in flow and mass spectrometry. Medical applications are very broad, notably in hemopathies, immunology, solid tumors, but also microbiology, toxicology, drug discovery, food and environmental industry. But, the limit of FCM is its dependence on operator from sample preparation, instrument settings up to data analysis and a strong effort is now under progress for standardization and constitution of international data bank for references and education.

Cytofkit: A Bioconductor Package for an Integrated Mass Cytometry Data Analysis Pipeline

Single-cell mass cytometry significantly increases the dimensionality of cytometry analysis as compared to fluorescence flow cytometry, providing unprecedented resolution of cellular diversity in tissues. However, analysis and interpretation of these high-dimensional data poses a significant technical challenge. Here, we present cytofkit, a new Bioconductor package, which integrates both state-of-the-art bioinformatics methods and in-house novel algorithms to offer a comprehensive toolset for mass cytometry data analysis. Cytofkit provides functions for data pre-processing, data visualization through linear or non-linear dimensionality reduction, automatic identification of cell subsets, and inference of the relatedness between cell subsets. This pipeline also provides a graphical user interface (GUI) for ease of use, as well as a shiny application (APP) for interactive visualization of cell subpopulations and progression profiles of key markers. Applied to a CD14⁻CD19⁻ PBMCs dataset, cytofkit accurately identified different subsets of lymphocytes; applied to a human CD4⁺ T cell dataset, cytofkit uncovered multiple subtypes of T_FH cells spanning blood and tonsils. Cytofkit is implemented in R, licensed under the Artistic license 2.0, and freely available from the Bioconductor website, https://bioconductor.org/packages/cytofkit/. Cytofkit is also applicable for flow cytometry data analysis.

Convergence of Highly Resolved and Rapid Screening Platforms with Dynamically Engineered, Cell Phenotype-Prescriptive Biomaterials

Biophysical and biochemical cues from the cellular microenvironment initiate intracellular signaling through cellular membrane receptors and trigger specific cell developmental programs. Extracellular substrates and matrix scaffolds engineered to mimic cell's native physiological environment must incorporate the multifactorial parameters (composition, micro and nanoscale organization and topography) of the extracellular matrix as well as the dynamic nature of the matrix. The design of such engineered biomaterials is challenged by the inherent complexity and dynamic nature of the cell-extracellular matrix reciprocity, while the validation of robust microenvironments requires a deeper, higher content phenotypic resolution of cell-matrix interactions alongside a rapid screening capability. To this end, high-throughput platforms are integral to facilitating the screening and optimization of complex engineered microenvironments for directing desired cell developmental pathway. This review highlights the recent advances in biomaterial platforms that present dynamic cues and enable high throughput screening of cell's response to a combination of micro-environmental factors. We also address some newer techniques involving high content image informatics to elucidate emergent cellular behaviors with a focus on stem cell regenerative endpoints.

Role of Proteomics in the Development of Personalized Medicine

Advances in proteomic technologies have made import contribution to the development of personalized medicine by facilitating detection of protein biomarkers, proteomics-based molecular diagnostics, as well as protein biochips and pharmacoproteomics. Application of nanobiotechnology in proteomics, nanoproteomics, has further enhanced applications in personalized medicine. Proteomics-based molecular diagnostics will have an important role in the diagnosis of certain conditions and understanding the pathomechanism of disease. Proteomics will be a good bridge between diagnostics and therapeutics; the integration of these will be important for advancing personalized medicine. Use of proteomic biomarkers and combination of pharmacoproteomics with pharmacogenomics will enable stratification of clinical trials and improve monitoring of patients for development of personalized therapies. Proteomics is an important component of several interacting technologies used for development of personalized medicine, which is depicted graphically. Finally, cancer is a good example of applications of proteomic technologies for personalized management of cancer.