Cytometry Part A最新文献

Among various cellular characteristics, flow cytometry can evaluate antigen expression through qualitative or quantitative approaches. For relative quantification, fluorescence intensity (FI) values are converted into quantitative measurements using appropriate reference materials. To quantitatively estimate antigen density or define ligand-binding sites per cell, antibody binding capacity (ABC) values serve as the preferred metric. Standardizing assays through the conversion of arbitrary FI units into quantitative data is essential for consistency. However, reported ABC values for well-characterized antigens vary across the literature. This study addresses the challenges in achieving robust and reproducible quantitative flow cytometry data, offering methodological recommendations for accurately assessing target expression. Our research includes a comprehensive investigation of multiple factors, such as conventional and full-spectrum instruments, antibodies, reagents, matrices, cell density/confluency, cellular autofluorescence, and quantitative kits, to identify the primary sources of variation in ABC calculations. By implementing a systematic and integrated approach, we aim to ensure the generation of reliable and reproducible ABC values. Longitudinal studies provide strong evidence of assay robustness, while the established protocol further supports biomarker evaluation across different matrices and various stages of drug development.

Imaging flow cytometry requires rapid and accurate segmentation methods to ensure high-quality cellular morphology analysis and cell counting. In deformability cytometry (DC), a specific type of imaging flow cytometry, accurately detecting cell contours is critical for evaluating mechanical properties that serve as disease markers. Traditional thresholding methods, commonly used for their speed in high-throughput applications, often struggle with low-contrast images, leading to inaccuracies in detecting the object contour. Conversely, standard neural network approaches like U-Net, though effective in medical imaging, are less suitable for high-speed imaging applications due to long inference times. To address these issues, we present a solution that enables both fast and accurate segmentation, designed for imaging flow cytometry. Our method employs a small U-Net model trained on high-quality, curated, and annotated data. This optimized model outperforms traditional thresholding methods and other neural networks, delivering a 35× speed improvement on CPU over the standard U-Net. The enhanced performance is demonstrated by a significant reduction in systematic measurement errors in blood samples analyzed using DC. The tools developed in this study are adaptable for various imaging flow cytometry applications. This approach improves segmentation quality while maintaining the rapid processing necessary for high-throughput environments.

Recovery is a key performance parameter in cell sorters, a metric that assesses the match between the number of particles reported as sorted by the instrument and the actual number of particles gathered in the collection vessels. Sorting relies on the precise timing of the charging of a droplet containing the particle of interest in a critical measurement called drop delay (DD). DD timings are typically reliant on manufacturer recommended fluorescent bead reagents. Cuvette-based cell sorters in particular depend upon these fixed-sized QC beads for an automated approach to the DD calculation using an image-based camera system. Previous literature has highlighted the mismatch between these DD values and the settings best accommodating actual samples. Here, we present a new method for DD calculation—the Three-Puddle Method (3PM), based on procedures originally described for jet-in-air cell sorters; it optimizes DD values according to the target particle to be sorted, increasing sort recoveries for a range of cell sizes and particle types. With regard to recovery, 3PM-calculated DD values correlate with those achieved via optimum DD, defined using Rmax protocol, a robust metric for recovery. The advantages of the 3PM then are that it is a simple-to-implement protocol which has limited cell expenditure, essential in the handling of precious rare samples and the success of single cell and bulk sorting and the downstream applications relying on it.

This 29-color flow cytometry panel was developed and optimized for in-depth characterization of human peripheral blood NK cells for preclinical development and monitoring of NK cell therapies. The panel includes markers associated with NK cell differentiation, cytotoxicity, tissue residency, as well as NK cell dysfunction. Panel optimization was performed on freshly isolated and ex vivo activated NK cells enriched from human peripheral blood mononuclear cells (PBMCs). Overall, this panel functions as a tool to extensively characterize human NK cells, paving the way for rapid and standardized approaches to evaluate the biological activity of therapeutic NK cell products.

Suspension and imaging mass cytometry are single-cell, proteomic-based methods used to characterize tissue composition and structure. Data assessing the consistency of these methods over an extended period of time are still sparse and are needed if mass cytometry-based methods are to be used clinically. Here, we present experimental and computational pipelines developed within the Tumor Profiler clinical study, an observational clinical trial assessing the relevance of cutting-edge technologies in guiding treatment decisions for advanced cancer patients. By using aliquots of frozen antibody panels, batch effects between independent experiments performed within a time frame of 1 year were minimized. The inclusion of well-characterized reference samples allowed us to assess and correct for batch effects. A systematic evaluation of a test tumor sample analyzed in each run showed that our batch correction approach consistently reduced signal variations. We provide an exemplary analysis of a representative patient sample including an overview of data provided to clinicians and potential treatment suggestions. This study demonstrates that standardized suspension and imaging mass cytometry measurements generate robust data that meet clinical requirements for reproducibility and provide oncologists with valuable insights on the biology of patient tumors.

Antibody titration is an important step in every cytometric workflow, with the goal being to determine antibody concentrations that ensure highly reproducible results. When aiming to compare antigen expression between samples using mean or median fluorescence intensity (MFI), reagents should be used at a saturating concentration so that unavoidable variations in staining conditions do not affect the fluorescence signal. The recommended concentrations of commercially available fluorophore-labeled monoclonal antibodies (mAbs) may not achieve plateau staining, and their saturating concentration may be too high to be experimentally useful. To address these common concerns, we present a novel method to achieve saturation of fluorophore-conjugated mAbs, by ‘spiking-in’ unlabelled antibody of the same clone. Here, we demonstrate the application of this workflow to human anti-CD3 (clone OKT3, mouse IgG2a) and anti-TCRαβ (clone IP26, mouse IgG1), two mAbs that do not achieve saturation at 2-fold above their commercially recommended concentrations. First, the saturating concentration of unlabelled (purified) OKT3 and IP26 was determined by detection with a fluorophore-labeled anti-mouse IgG (H + L) secondary antibody. Titration curves of unlabelled and labeled mAbs were compared for each clone to determine whether labeling had resulted in any loss in binding activity. Unlabelled antibody was then ‘spiked’ into the labeled antibody at varying ratios, and those that achieved saturation while maintaining an adequate fluorescence signal were identified. We demonstrate that antibody saturation can be achieved with an optimized mixture of labeled and unlabelled antibody, while maintaining a clear signal from the fluorophore. While this workflow has only been applied to OKT3 and IP26, it has potential applicability for any antibody clone for which both labeled and unlabelled preparations are available. This method has significance for robust comparison of biomarker expression when fluorophore labeled reagents do not reach saturation under standard staining conditions.