Flow Cytometry Detection of Anthracycline-Treated Breast Cancer Cells: An Optimized Protocol.

The use of anthracycline derivatives was approved for the treatment of a broad spectrum of human tumors (i.e., breast cancer). The need to test these drugs on cancer models has pushed the basic research to apply many types of in vitro assays, and, among them, the study of anthracycline-induced apoptosis was mainly based on the application of flow cytometry protocols. However, the chemical structure of anthracycline derivatives gives them a strong autofluorescence effect that must be considered when flow cytometry is used. Unfortunately, the guidelines on the analysis of anthracycline effects through flow cytometry are lacking. Therefore, in this study, we optimized the flow cytometry detection of doxorubicin and epirubicin-treated breast cancer cells. Their autofluorescence was assessed both by using conventional and imaging flow cytometry; we found that all the channels excited by the 488 nm laser were affected. Anthracycline-induced apoptosis was then measured via flow cytometry using the optimized setting. Consequently, we established a set of recommendations that enable the development of optimized flow cytometry settings when the in vitro assays of anthracycline effects are analyzed, with the final aim to reveal a new perspective on the use of those in vitro tests for the further implementation of precision medicine strategies in cancer.

SARS-CoV-2 and Immunity: Natural Infection Compared with Vaccination.

Recently, the protective and/or pathological role of virus-specific T cells in SARS-CoV-2 infection has been the focus of many studies. We investigated the anti-spike IgG levels and SARS-CoV-2-specific T cells in 125 donors (90 vaccinated with four different vaccine platforms, 16 individuals with a previous natural infection, and 19 not vaccinated donors who did not report previous SARS-CoV-2 infections). Our data show that anti-spike IgG titers were similar between naturally infected subjects and those vaccinated with adenoviral vector vaccines. Of note, all immunized donors produced memory CD4+ and/or CD8+ T cells. A sustained polyfunctionality of SARS-CoV-2-specific T cells in all immunized donors was also demonstrated. Altogether, our data suggest that the natural infection produces an overall response like that induced by vaccination. Therefore, this detailed immunological evaluation may be relevant for other vaccine efforts especially for the monitoring of novel vaccines effective against emerging virus variants.

Flow Cytometry Analysis of Circulating Extracellular Vesicle Subtypes from Fresh Peripheral Blood Samples.

Extracellular vesicles (EVs) are released by shedding during different physiological processes and are increasingly thought to be new potential biomarkers. However, the impact of pre-analytical processing phases on the final measurement is not predictable and for this reason, the translation of basic research into clinical practice has been precluded. Here we have optimized a simple procedure in combination with polychromatic flow cytometry (PFC), to identify, classify, enumerate, and separate circulating EVs from different cell origins. This protocol takes advantage of a lipophilic cationic dye (LCD) able to probe EVs. Moreover, the application of the newly optimized PFC protocol here described allowed the obtainment of repeatable EVs counts. The translation of this PFC protocol to fluorescence-activated cell sorting allowed us to separate EVs from fresh peripheral blood samples. Sorted EVs preparations resulted particularly suitable for proteomic analyses, which we applied to study their protein cargo. Here we show that LCD staining allowed PFC detection and sorting of EVs from fresh body fluids, avoiding pre-analytical steps of enrichment that could impact final results. Therefore, LCD staining is an essential step towards the assessment of EVs clinical significance.

Background fluorescence and spreading error are major contributors of variability in high-dimensional flow cytometry data visualization by t-distributed stochastic neighboring embedding.

Multidimensional single-cell analysis requires approaches to visualize complex data in intuitive 2D graphs. In this regard, t-distributed stochastic neighboring embedding (tSNE) is the most popular algorithm for single-cell RNA sequencing and cytometry by time-of-flight (CyTOF), but its application to polychromatic flow cytometry, including the recently developed 30-parameter platform, is still under investigation. We identified differential distribution of background values between samples, generated by either background calculation or spreading error (SE), as a major source of variability in polychromatic flow cytometry data representation by tSNE, ultimately resulting in the identification of erroneous heterogeneity among cell populations. Biexponential transformation of raw data and limiting SE during panel development dramatically improved data visualization. These aspects must be taken into consideration when using computational approaches as discovery tools in large sets of samples from independent experiments or immunomonitoring in clinical trials.

FloReMi: Flow density survival regression using minimal feature redundancy.

Advances in flow cytometry bioinformatics have resulted in a wide variety of clustering, classification and visualization techniques. To objectively evaluate the performance of such methods, common benchmarks such as the FlowCAP initiative have proven to be of great value. In this work, we report on a novel method, FloReMi, which was developed to tackle the most recent FlowCAP IV challenge. This challenge was formulated as a survival modeling problem, where participants were expected to design a model to predict the time until progression to AIDS for HIV patients. It is known that variability in progression rate cannot be fully predicted by simple CD4(+) T cell counts. However, it is hypothesized that the immunopathogenesis established early in HIV already indicates the course of future disease. Adequately estimating the progression rate of HIV patients is crucial in their treatment. Using an automated pipeline to preprocess the data, and subsequently identify and select informative cell subsets, a survival regression method based on random survival forests was built, which obtained the best results of all submitted approaches to the FlowCAP IV challenge.

Endothelial progenitor cells, defined by the simultaneous surface expression of VEGFR2 and CD133, are not detectable in healthy peripheral and cord blood.

Circulating endothelial cells (CEC) and their progenitors (EPC) are restricted subpopulations of peripheral blood (PB), cord blood (CB), and bone marrow (BM) cells, involved in the endothelial homeostasis maintenance. Both CEC and EPC are thought to represent potential biomarkers in several clinical conditions involving endothelial turnover/remodeling. Although different flow cytometry methods for CEC and EPC characterization have been published so far, none of them have reached consistent conclusions, therefore consensus guidelines with respect to CEC and EPC identification and quantification need to be established. Here, we have carried out an in depth investigation of CEC and EPC phenotypes in healthy PB, CB and BM samples, by optimizing a reliable polychromatic flow cytometry (PFC) panel. Results showed that the brightness of CD34 expression on healthy PB and CB circulating cells represents a key benchmark for the identification of CEC (CD45neg/CD34bright/CD146pos) respect to the hematopoietic stem cell (HSC) compartment (CD45dim/CD34pos/CD146neg). This approach, combined with a dual-platform counting technique, allowed a sharp CEC enumeration in healthy PB (n = 38), and resulting in consistent CEC counts with previously reported data (median = 11.7 cells/ml). In parallel, by using rigorous PFC conditions, CD34pos/CD45dim/CD133pos/VEGFR2pos EPC were not found in any healthy PB or CB sample, since VEGFR2 expression was never detectable on the surface of CD34pos/CD45dim/CD133pos cells. Notably, the putative EPC phenotype was observed in all analyzed BM samples (n = 12), and the expression of CD146 and VEGFR2, on BM cells, was not restricted to the CD34bright compartment, but also appeared on the HSC surface. Altogether, our findings suggest that the previously reported EPC antigen profile, defined by the simultaneous expression of VEGFR2 and CD133 on the surface of CD45dim/CD34pos cells, should be carefully re-evaluated and further studies should be conducted to redefine EPC features in order to translate CEC and EPC characterization into clinical practice.

FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data.

The number of markers measured in both flow and mass cytometry keeps increasing steadily. Although this provides a wealth of information, it becomes infeasible to analyze these datasets manually. When using 2D scatter plots, the number of possible plots increases exponentially with the number of markers and therefore, relevant information that is present in the data might be missed. In this article, we introduce a new visualization technique, called FlowSOM, which analyzes Flow or mass cytometry data using a Self-Organizing Map. Using a two-level clustering and star charts, our algorithm helps to obtain a clear overview of how all markers are behaving on all cells, and to detect subsets that might be missed otherwise. R code is available at https://github.com/SofieVG/FlowSOM and will be made available at Bioconductor.

Comprehensive Immunophenotyping by Polychromatic Cytometry.

The human immune system comprises a diverse array of cells involved in innate and adaptive immunity, and these immune cells coordinate immune responses against pathogens through intricate interactions. Multicolor flow cytometry is a powerful technique for qualitatively and quantitatively measuring the characteristics of immune cells, offering advantages, such as high-dimensional analysis, elucidation of cellular heterogeneity, understanding of pathogenesis, development of therapeutic strategies, and platform flexibility. Here, we demonstrate a new immunophenotyping panel that allows simultaneous evaluation of the characteristics of T and B cells. This panel enables tracking of changes in the immune status due to aging, environmental factors, pathogen infections, and vaccine administration. Additionally, it includes co-stimulatory molecules for assessing the activation state of immune cells and inhibitory checkpoint molecules for evaluating exhaustion status, thereby providing valuable insights into the features of human immune responses. These analyses contribute to understanding the pathophysiology of diseases and developing therapeutic strategies while offering crucial information for assessing the correlation of symptoms with infections and evaluating the efficacy of vaccines.

High-Dimensional Single-Cell Profiling of Tumor-Infiltrating CD4+ Regulatory T Cells.

CD4+ T regulatory cells (Tregs) are a specialized subset of T lymphocytes, which promote immune homeostasis and tumor immunosuppression by restricting effector T cell immune responses. The characterization of context-specific Treg phenotypic heterogeneity is pivotal to determine their potential contributions to diseases. In the recent years, high-dimensional single-cell technologies, such as single-cell RNA sequencing, mass cytometry, or polychromatic flow cytometry, have played a central role in elucidating the heterogeneity of the Treg compartment at the cellular and molecular levels. Here we describe an example of high-dimensional flow cytometry analysis capable of defining an effector Treg subpopulation that positively correlates with cancer progression. Moreover, we provide a workflow template of high-dimensional single-cell analysis that is readily applicable to any leukocyte subpopulation.