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.

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.

Comparative exploration of multidimensional flow cytometry software: a model approach evaluating T cell polyfunctional behavior

Advancement in flow cytometry reagents and instrumentation has allowed for simultaneous analysis of large numbers of lineage/functional immune cell markers. Highly complex datasets generated by polychromatic flow cytometry require proper analytical software to answer investigators' questions. A problem among many investigators and flow cytometry Shared Resource Laboratories (SRLs), including our own, is a lack of access to a flow cytometry-knowledgeable bioinformatics team, making it difficult to learn and choose appropriate analysis tool(s). Here, we comparatively assess various multidimensional flow cytometry software packages for their ability to answer a specific biologic question and provide graphical representation output suitable for publication, as well as their ease of use and cost. We assessed polyfunctional potential of TCR-transduced T cells, serving as a model evaluation, using multidimensional flow cytometry to analyze 6 intracellular cytokines and degranulation on a per-cell basis. Analysis of 7 parameters resulted in 128 possible combinations of positivity/negativity, far too complex for basic flow cytometry software to analyze fully. Various software packages were used, analysis methods used in each described, and representative output displayed. Of the tools investigated, automated classification of cellular expression by nonlinear stochastic embedding (ACCENSE) and coupled analysis in Pestle/simplified presentation of incredibly complex evaluations (SPICE) provided the most user-friendly manipulations and readable output, evaluating effects of altered antigen-specific stimulation on T cell polyfunctionality. This detailed approach may serve as a model for other investigators/SRLs in selecting the most appropriate software to analyze complex flow cytometry datasets. Further development and awareness of available tools will help guide proper data analysis to answer difficult biologic questions arising from incredibly complex datasets.

Streptamer technology allows accurate and specific detection of CMV-specific HLA-A*02 CD8+ T cells by flow cytometry

BACKGROUND

Multimer technology is widely used to screen antigen-specific immune recovery after allogeneic hematopoietic stem cell transplantation (allo-HSCT) as it enables identification, enumeration, phenotypic characterization and isolation of virus-specific T-cells. Novel approaches of multimerization might improve on classical tetramer staining; however, their use as standard monitoring technique to quantify antigen-specific cells has not been validated yet. We have compared two of these available multimeric complexes: pentamer and streptamer to select the best strategy for the incorporation into clinical monitoring practice.

METHODS

CMVpp65^495-503 -specific HLA-A*02:01 CD8⁺ T lymphocytes (CTL^A *^02:01 -CMVpp65^495-503 ) were examined with pentamer and streptamer in peripheral blood cells of 77 healthy volunteers. Quantitative and qualitative analyses were performed to compare the precision and repeatability, sensitivity and accuracy and specificity of both technologies by flow cytometry.

RESULTS

Standard deviation for both techniques was less than 0.05 showing that they are repetitive and precise. Both techniques significantly correlated at high frequencies (r_Spearman  = 0.9422; P < 0.0001) but it was lost at lower levels (<1%) of CTL^A *^02:01 -CMVpp65^495-503 (r_Spearman  = 0.3351; P = 0.1376). Streptamer is more accurate for the detection of CTL^A *^02:01 -CMVpp65^495-503 providing significantly closer values to the theoretical ones (P < 0.0001) as pentamer binds unspecifically to a notable proportion of non-CMV-specific CD8⁺ T-cells.

CONCLUSION

Our results suggest that streptamer multimer provides precise, accurate and specific results to detect CTL^A *^02:01 -CMVpp65^495-503 by flow cytometry. Streptamer multimer can be used not only for the monitoring of early CTL^A *^02:01 -CMVpp65^495-503 reconstitution in immunosuppressed patients following allo-HSCT but also, in conjunction with its reversibility role, for the isolation of CTL^A *^02:01 -CMVpp65^495-503 for its future use in adoptive immunotherapy. © 2016 International Clinical Cytometry Society.

RchyOptimyx: cellular hierarchy optimization for flow cytometry

Analysis of high-dimensional flow cytometry datasets can reveal novel cell populations with poorly understood biology. Following discovery, characterization of these populations in terms of the critical markers involved is an important step, as this can help to both better understand the biology of these populations and aid in designing simpler marker panels to identify them on simpler instruments and with fewer reagents (i.e., in resource poor or highly regulated clinical settings). However, current tools to design panels based on the biological characteristics of the target cell populations work exclusively based on technical parameters (e.g., instrument configurations, spectral overlap, and reagent availability). To address this shortcoming, we developed RchyOptimyx (cellular hieraRCHY OPTIMization), a computational tool that constructs cellular hierarchies by combining automated gating with dynamic programming and graph theory to provide the best gating strategies to identify a target population to a desired level of purity or correlation with a clinical outcome, using the simplest possible marker panels. RchyOptimyx can assess and graphically present the trade-offs between marker choice and population specificity in high-dimensional flow or mass cytometry datasets. We present three proof-of-concept use cases for RchyOptimyx that involve 1) designing a panel of surface markers for identification of rare populations that are primarily characterized using their intracellular signature; 2) simplifying the gating strategy for identification of a target cell population; 3) identification of a non-redundant marker set to identify a target cell population.

Detection of low avidity CD8(+) T cell populations with coreceptor-enhanced peptide-major histocompatibility complex class I tetramers

The development of soluble recombinant peptide-major histocompatibility complex class I (pMHCI) molecules conjugated in multimeric form to fluorescent labels has enabled the physical quantification and characterization of antigen-specific CD8(+) T cell populations by flow cytometry. Several factors determine the binding threshold that enables visualization of cognate CD8(+) T cells with these reagents; these include the affinity of the T cell receptor (TCR) for pMHCI antigen. Here, we show that multimers constructed from peptide-human leukocyte antigen (pHLA) A0201 monomers engineered in the heavy chain alpha2 domain to enhance CD8 binding (K(D) approximately 85 microM) without impacting the TCR binding platform can detect cognate CD8(+) T cells bearing low affinity TCRs that are not visible with the corresponding wildtype pHLA A0201 multimeric complexes. Mechanistically, this effect is mediated by a disproportionate enhancement of the TCR/pMHCI association rate. In direct ex vivo applications, these coreceptor-enhanced multimers exhibit faithful cognate binding properties; concomitant increases in background staining within the non-cognate CD8(+) T cell population can be resolved phenotypically using polychromatic flow cytometry as a mixture of naïve and memory cells. These findings provide the first validation of a novel approach to the physical detection of low avidity antigen-specific CD8(+) T cell populations; such coreceptor-enhanced multimeric reagents are likely to be useful in a multitude of settings for the detection of auto-immune, tumor-specific and cross-reactive CD8(+) T cells.

Nine-color flow cytometry for accurate measurement of T cell subsets and cytokine responses. Part I: Panel design by an empiric approach

Polychromatic flow cytometry offers the unprecedented ability to investigate multiple antigens per cell. Unfortunately, unwanted spectral overlaps and compensation problems increase when more than four colors are used, but these problems can be minimized if staining combinations are chosen carefully. We used an empiric approach to design, test and identify six-color T cell immunophenotyping reagent panels that can be expanded to include three or more functional or other markers in the FITC, PE, and APC channels without significant spectral limitations. Thirty different six-color T cell surface antigen reagent panels were constructed to identify major T cell subsets and maturational subtypes as defined by CCR7 and CD45RA expression, while excluding monocytes, B and non-viable cells. Staining performance of each panel was compared on cryopreserved cells from a single healthy donor recorded on a multiparameter cell sorter. Ten of the thirty reagent panels offered reliable resolution of T cell major and maturational surface markers. Of these, two panels were selected that showed the least spectral overlap and resulting background increase in the FITC, PE, and APC channels. These channels were left unoccupied for inclusion of additional phenotypic or functional markers, such as cytokines. Careful reagent titration and testing of multiple candidate panels are necessary to ensure quality results in multiparametric measurements.