Panel Design and Optimization for High‐Dimensional Immunophenotyping Assays Using Spectral Flow Cytometry

2020 ◽  
Vol 92 (1) ◽  
Author(s):  
Laura Ferrer‐Font ◽  
Christophe Pellefigues ◽  
Johannes U. Mayer ◽  
Sam J. Small ◽  
Maria C. Jaimes ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
High Dimensional ◽  
Spectral Flow ◽  
Design And Optimization ◽  
Panel Design

scholarly journals Design and Optimization Protocol for High-Dimensional Immunophenotyping Assays using Spectral Flow Cytometry

2019 ◽  
Author(s):  
L Ferrer-Font ◽  
C Pellefigues ◽  
JU Mayer ◽  
S Small ◽  
MC Jaimes ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Immune System ◽  
Selection Process ◽  
High Dimensional ◽  
Spectral Flow ◽  
High Quality ◽  
Design And Optimization ◽  
Technological Advances ◽  
Large Numbers ◽  
Recent Advancement

ABSTRACTTechnological advances in fluorescence flow cytometry and an ever-expanding understanding of the complexity of the immune system has led to the development of large 20+ flow cytometry panels. Yet, as panel complexity and size increases, so does the difficulty involved in designing a high-quality panel, accessing the instrumentation capable of accommodating large numbers of parameters, and in analysing such high-dimensional data.A recent advancement is spectral flow cytometry, which in contrast to conventional flow cytometry distinguishes the full emission spectrum of each fluorochrome across all lasers, rather than identifying only the peak of emission. Fluorochromes with a similar emission maximum but distinct off-peak signatures can therefore be accommodated within the same flow cytometry panel, allowing greater flexibility in terms of panel design and fluorophore detection.Here, we highlight the specific characteristics regarding spectral flow cytometry and aim to guide users through the process of building, designing and optimising high-dimensional spectral flow cytometry panels using a comprehensive step-by-step protocol. Special considerations are also given for using highly-overlapping dyes and a logical selection process an optimal marker-fluorophore assignment is provided.

scholarly journals High‐Dimensional Data Analysis Algorithms Yield Comparable Results for Mass Cytometry and Spectral Flow Cytometry Data

2020 ◽  
Vol 97 (8) ◽  
pp. 824-831 ◽  
Author(s):  
Laura Ferrer‐Font ◽  
Johannes U. Mayer ◽  
Samuel Old ◽  
Ian F. Hermans ◽  
Jonathan Irish ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Data Analysis ◽  
High Dimensional Data ◽  
High Dimensional ◽  
Spectral Flow ◽  
Mass Cytometry ◽  
Flow Cytometry Data ◽  
High Dimensional Data Analysis

scholarly journals With great power comes great responsibility: high-dimensional spectral flow cytometry to support clinical trials

Bioanalysis ◽  
2021 ◽  
Author(s):  
Megan McCausland ◽  
Yi-Dong Lin ◽  
Tania Nevers ◽  
Christopher Groves ◽  
Vilma Decman
Keyword(s):  
Flow Cytometry ◽  
Clinical Trials ◽  
Clinical Sample ◽  
Great Power ◽  
High Dimensional ◽  
Spectral Flow ◽  
Sample Analysis ◽  
Great Responsibility ◽  
Identification And Characterization ◽  
Research Drug

Flow cytometry is a powerful technology used in research, drug development and clinical sample analysis for cell identification and characterization, allowing for the simultaneous interrogation of multiple targets on various cell subsets from limited samples. Recent advancements in instrumentation and fluorochrome availability have resulted in significant increases in the complexity and dimensionality of flow cytometry panels. Though this increase in panel size allows for detection of a broader range of markers and sub-populations, even in restricted biological samples, it also comes with many challenges in panel design, optimization, and downstream data analysis and interpretation. In the current paper we describe the practices we established for development of high-dimensional panels on the Aurora spectral flow cytometer to aid clinical sample analysis.

scholarly journals How to Prepare Spectral Flow Cytometry Datasets for High Dimensional Data Analysis: A Practical Workflow

2021 ◽  
Vol 12 ◽  
Author(s):  
Hannah den Braanker ◽  
Margot Bongenaar ◽  
Erik Lubberts
Keyword(s):  
Flow Cytometry ◽  
Dimensional Analysis ◽  
High Dimensional ◽  
Spectral Flow ◽  
Control Data ◽  
Single Experiment ◽  
Flow Cytometry Data ◽  
Healthy Control ◽  
The Common ◽  
Quality Control Data

Spectral flow cytometry is an upcoming technique that allows for extensive multicolor panels, enabling simultaneous investigation of a large number of cellular parameters in a single experiment. To fully explore the resulting high-dimensional single cell datasets, high-dimensional analysis is needed, as opposed to the common practice of manual gating in conventional flow cytometry. However, preparing spectral flow cytometry data for high-dimensional analysis can be challenging, because of several technical aspects. In this article, we will give insight into the pitfalls of handling spectral flow cytometry datasets. Moreover, we will describe a workflow to properly prepare spectral flow cytometry data for high dimensional analysis and tools for integrating new data at later time points. Using healthy control data as example, we will go through the concepts of quality control, data cleaning, transformation, correcting for batch effects, subsampling, clustering and data integration. This methods article provides an R-based pipeline based on previously published packages, that are readily available to use. Application of our workflow will aid spectral flow cytometry users to obtain valid and reproducible results.

Spectral Flow Cytometry Makes Debut

2013 ◽  
Vol 33 (21) ◽  
pp. 1, 20-21
Author(s):  
Kathy Liszewski
Keyword(s):  
Flow Cytometry ◽  
Spectral Flow

scholarly journals High dimensional flow cytometry for comprehensive leukocyte immunophenotyping (CLIP) in translational research

2011 ◽  
Vol 363 (2) ◽  
pp. 245-261 ◽  
Author(s):  
Angélique Biancotto ◽  
John C. Fuchs ◽  
Ann Williams ◽  
Pradeep K. Dagur ◽  
J. Philip McCoy
Keyword(s):  
Flow Cytometry ◽  
Translational Research ◽  
High Dimensional ◽  
Dimensional Flow

scholarly journals Training Novices in Generation and Analysis of High‐Dimensional Human Cell Phospho‐Flow Cytometry Data

2020 ◽  
Vol 93 (1) ◽  
Author(s):  
Caroline E. Roe ◽  
Madeline J. Hayes ◽  
Sierra M. Barone ◽  
Jonathan M. Irish
Keyword(s):  
Flow Cytometry ◽  
Human Cell ◽  
High Dimensional ◽  
Flow Cytometry Data

scholarly journals Identification of Novel Low-Density Neutrophil Markers Through Unbiased High-Dimensional Flow Cytometry Screening in Non-Small Cell Lung Cancer Patients

2021 ◽  
Vol 12 ◽  
Author(s):  
Paulina Valadez-Cosmes ◽  
Kathrin Maitz ◽  
Oliver Kindler ◽  
Sofia Raftopoulou ◽  
Melanie Kienzl ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Flow Cytometry ◽  
Small Cell Lung Cancer ◽  
Cancer Patients ◽  
Small Cell ◽  
High Dimensional ◽  
Surface Markers ◽  
Low Density ◽  
Small Cell Lung ◽  
Nsclc Patients

Neutrophils have been described as a phenotypically heterogeneous cell type that possess both pro- and anti-tumor properties. Recently, a subset of neutrophils isolated from the peripheral blood mononuclear cell (PBMC) fraction has been described in cancer patients. These low-density neutrophils (LDNs) show a heterogeneous maturation state and have been associated with pro-tumor properties in comparison to mature, high-density neutrophils (HDNs). However, additional studies are necessary to characterize this cell population. Here we show new surface markers that allow us to discriminate between LDNs and HDNs in non-small cell lung cancer (NSCLC) patients and assess their potential as diagnostic/prognostic tool. LDNs were highly enriched in NSCLC patients (median=20.4%, range 0.3-76.1%; n=26) but not in healthy individuals (median=0.3%, range 0.1-3.9%; n=14). Using a high-dimensional human cell surface marker screen, we identified 12 surface markers that were downregulated in LDNs when compared to HDNs, while 41 surface markers were upregulated in the LDN subset. Using flow cytometry, we confirmed overexpression of CD36, CD41, CD61 and CD226 in the LDN fraction. In summary, our data support the notion that LDNs are a unique neutrophil population and provide novel targets to clarify their role in tumor progression and their potential as diagnostic and therapeutic tool.

scholarly journals Multi-Dimensional T-Cell Functional Analysis by Spectral Flow Cytometry as a Tool to Dissect Endotypes in Allergic Disease.

2019 ◽  
Vol 143 (2) ◽  
pp. AB184
Author(s):  
Alberta GA. Paul ◽  
Jill Glesner ◽  
Josephine Lannigan ◽  
Lyndsey M. Muehling ◽  
Jacob D. Eccles ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Functional Analysis ◽  
T Cell ◽  
Allergic Disease ◽  
Spectral Flow
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