scholarly journals Assessment of Protocol Impact on Subjectivity Uncertainty When Analyzing Peripheral Blood Mononuclear Cell Flow Cytometry Data Files

2021 ◽  
Vol 4 (2) ◽  
pp. 24
Author(s):  
Rebecca Grant ◽  
Karen Coopman ◽  
Sandro Silva-Gomes ◽  
Jonathan J. Campbell ◽  
Bo Kara ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Measurement Uncertainty ◽  
Target Cells ◽  
Peripheral Blood Mononuclear ◽  
Flow Cytometry Data ◽  
Uncertainty In Measurement ◽  
Cell Flow Cytometry ◽  
Data Files ◽  
Cell And Gene Therapy ◽  
Dying Cells

Measured variability of product within Cell and Gene Therapy (CGT) manufacturing arises from numerous sources across pre-analytical to post-analytical phases of testing. Operators are a function of the manufacturing process and are an important source of variability as a result of personal differences impacted by numerous factors. This research uses measurement uncertainty in comparison to Coefficient of Variation to quantify variation of participants when they complete Flow Cytometry data analysis through a 5-step gating sequence. Two study stages captured participants applying gates using their own judgement, and then following a diagrammatical protocol, respectively. Measurement uncertainty was quantified for each participant (and analysis phase) by following Guide to the Expression of Uncertainty in Measurement protocols, combining their standard deviations in quadrature from each gating step in the respective protocols. When participants followed a diagrammatical protocol, variation between participants reduced by 57%, increasing confidence in a more uniform reported cell count percentage. Measurement uncertainty provided greater resolution to the analysis processes, identifying that most variability contributed in the Flow Cytometry gating process is from the very first gate, where isolating target cells from dead or dying cells is required. This work has demonstrated the potential for greater usage of measurement uncertainty within CGT manufacturing scenarios, due to the resolution it provides for root cause analysis and continuous improvement.

Generation of flow cytometry data files with a potentially infinite number of dimensions

2008 ◽  
Vol 73A (9) ◽  
pp. 834-846 ◽  
Author(s):  
Carlos E. Pedreira ◽  
Elaine S. Costa ◽  
Susana Barrena ◽  
Quentin Lecrevisse ◽  
Julia Almeida ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Infinite Number ◽  
Flow Cytometry Data ◽  
Data Files

scholarly journals High-Dimensional Analysis of Single-Cell Flow Cytometry Data Predicts Relapse in Childhood Acute Lymphoblastic Leukaemia

Cancers ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 17
Author(s):  
Salvador Chulián ◽  
Álvaro Martínez-Rubio ◽  
Víctor M. Pérez-García ◽  
María Rosa ◽  
Cristina Blázquez Goñi ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Acute Lymphoblastic Leukaemia ◽  
B Cell ◽  
Lymphoblastic Leukaemia ◽  
High Dimensional ◽  
Full Potential ◽  
Flow Cytometry Data ◽  
Cell Flow Cytometry ◽  
Fisher’S Ratio ◽  
Response Biomarkers

Artificial intelligence methods may help in unveiling information that is hidden in high-dimensional oncological data. Flow cytometry studies of haematological malignancies provide quantitative data with the potential to be used for the construction of response biomarkers. Many computational methods from the bioinformatics toolbox can be applied to these data, but they have not been exploited in their full potential in leukaemias, specifically for the case of childhood B-cell Acute Lymphoblastic Leukaemia. In this paper, we analysed flow cytometry data that were obtained at diagnosis from 56 paediatric B-cell Acute Lymphoblastic Leukaemia patients from two local institutions. Our aim was to assess the prognostic potential of immunophenotypical marker expression intensity. We constructed classifiers that are based on the Fisher’s Ratio to quantify differences between patients with relapsing and non-relapsing disease. We also correlated this with genetic information. The main result that arises from the data was the association between subexpression of marker CD38 and the probability of relapse.

scholarly journals An active, collaborative approach to learning skills in flow cytometry

2016 ◽  
Vol 40 (2) ◽  
pp. 176-185 ◽  
Author(s):  
Kathryn Fuller ◽  
Matthew D. Linden ◽  
Tracey Lee-Pullen ◽  
Clayton Fragall ◽  
Wendy N. Erber ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Data Analysis ◽  
Learning Outcomes ◽  
Undergraduate Students ◽  
Immune Cell ◽  
Complex Data ◽  
Collaborative Approach ◽  
Flow Cytometry Data ◽  
Antibody Staining ◽  
Data Files

Advances in science education research have the potential to improve the way students learn to perform scientific interpretations and understand science concepts. We developed active, collaborative activities to teach skills in manipulating flow cytometry data using FlowJo software. Undergraduate students were given compensated clinical flow cytometry listmode output (FCS) files and asked to design a gating strategy to diagnose patients with different hematological malignancies on the basis of their immunophenotype. A separate cohort of research trainees was given uncompensated data files on which they performed their own compensation, calculated the antibody staining index, designed a sequential gating strategy, and quantified rare immune cell subsets. Student engagement, confidence, and perceptions of flow cytometry were assessed using a survey. Competency against the learning outcomes was assessed by asking students to undertake tasks that required understanding of flow cytometry dot plot data and gating sequences. The active, collaborative approach allowed students to achieve learning outcomes not previously possible with traditional teaching formats, for example, having students design their own gating strategy, without forgoing essential outcomes such as the interpretation of dot plots. In undergraduate students, favorable perceptions of flow cytometry as a field and as a potential career choice were correlated with student confidence but not the ability to perform flow cytometry data analysis. We demonstrate that this new pedagogical approach to teaching flow cytometry is beneficial for student understanding and interpretation of complex concepts. It should be considered as a useful new method for incorporating complex data analysis tasks such as flow cytometry into curricula.

scholarly journals Understanding the contribution of operator measurement variability within Flow Cytometry data analysis for Quality Control of Cell and Gene Therapy manufacturing

Measurement ◽  
2020 ◽  
Vol 150 ◽  
pp. 106998
Author(s):  
Rebecca Grant ◽  
Karen Coopman ◽  
Nicholas Medcalf ◽  
Sandro Silva-Gomes ◽  
Jonathan J. Campbell ◽  
...  
Keyword(s):  
Gene Therapy ◽  
Flow Cytometry ◽  
Quality Control ◽  
Data Analysis ◽  
Measurement Variability ◽  
Flow Cytometry Data ◽  
Cell And Gene Therapy

scholarly journals OP0186 CHANGES IN CIRCULATING B CELL LEVELS AND IMMUNOPHENOTYPE ARE ASSOCIATED WITH DEVELOPMENT OF ARTHRITIS FOLLOWING TREATMENT WITH CHECKPOINT INHIBITORS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 112.2-113
Author(s):  
M. Gatto ◽  
S. Bjursten ◽  
C. Jonell ◽  
C. Jonsson ◽  
S. Mcgrath ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
B Cells ◽  
Adverse Events ◽  
B Cell ◽  
Mononuclear Cells ◽  
Checkpoint Inhibitors ◽  
Therapy Monitoring ◽  
Cell Subset ◽  
Peripheral Blood Mononuclear ◽  
Transitional B Cells

Background:Inflammatory arthritis (IA) is frequent among rheumatic side effects induced by checkpoint inhibitor (CPI) therapy for metastatic malignancies1. While T cells are likely to sustain the inflammatory process2, fewer data are available concerning the role of B cells3.Objectives:To investigate the phenotype of circulating B cells in patients who develop CPI-induced IA (CPI-IA) and to compare it with features of B cells in patients not developing immune-related adverse events (irAE) upon CPI treatment.Methods:B cell subsets at baseline (before CPI initiation) and during CPI treatment were analyzed in CPI-IA patients and in patients receiving CPI but who did not develop irAE (non-irAE). Peripheral blood mononuclear cells (PBMC) were analyzed by flow cytometry and B cells were identified as CD19+ and divided into naïve (CD27-IgD+), memory (CD27+IgD+/-), double negative (CD27-IgD-) and transitional (CD10+CD24+CD38+/hi) B cells. Levels of CD21, an activation marker on transitional B cells, were also analyzed. Non-parametric tests were used for analysis of differences between groups.Results:Six CPI-IA and 7 non-irAE patients matched for age, gender and CPI treatment were included, who had received CPI treatment due to metastatic melanoma. Flow cytometry revealed a significant increase of circulating B cells (p=0.002) (Figure 1A) and especially of transitional B cells in CPI-IA patients vs. non-irAE (median %, range: 7.8 (4.5-11.4) vs. 3.2 (1.6-4.3),p=0.007) (Figure 1B), while no remarkable changes were seen across other subsets. Transitional B cell levels significantly decreased from active to quiescent CPI-IA in all patients (p=0.008). In two CPI-IA patients for whom baseline sampling was available, the increase of transitional levels occurred early after CPI treatment and before CPI-IA onset. Levels of expression of CD21 on transitional B cells were increased in CPI-IA vs. non-irAE (p=0.01).Conclusion:Transitional B cells are expanded in CPI-IA patients and seem to increase early after start of CPI therapy. Monitoring this B cell subset might lead to closer follow-up and earlier diagnosis of CPI-IA.References:[1]Ramos-Casals M, Brahmer JR, Callahan MK, et al. Immune-related adverse events of checkpoint inhibitors. Nat Rev Dis Primers 2020;6:38[2]Murray-Brown W, Wilsdon TD, Weedon H, et al. Nivolumab-induced synovitis is characterized by florid T cell infiltration and rapid resolution with synovial biopsy-guided therapy. J Immunother Cancer 2020;8:e000281[3]Das R, Bar N, Ferreira M, et al. Early B cell changes predict autoimmunity following combination immune checkpoint blockade. J Clin Invest. 2018;128:715-2Disclosure of Interests:None declared

ISO/TS 20914:2019 – a critical commentary

2020 ◽  
Vol 58 (8) ◽  
pp. 1182-1190 ◽  
Author(s):  
Ian Farrance ◽  
Robert Frenkel ◽  
Tony Badrick
Keyword(s):  
Measurement Uncertainty ◽  
Measurement Data ◽  
International Normalized Ratio ◽  
Medical Laboratory ◽  
Uncertainty In Measurement ◽  
Medical Laboratories ◽  
Functional Relationships ◽  
Critical Commentary ◽  
Combined Uncertainty ◽  
Expression Of Uncertainty

AbstractThe long-anticipated ISO/TS 20914, Medical laboratories – Practical guidance for the estimation of measurement uncertainty, became publicly available in July 2019. This ISO document is intended as a guide for the practical application of estimating uncertainty in measurement (measurement uncertainty) in a medical laboratory. In some respects, the guide does indeed meet many of its stated objectives with numerous very detailed examples. Even though it is claimed that this ISO guide is based on the Evaluation of measurement data – Guide to the expression of uncertainty in measurement (GUM), JCGM 100:2008, it is with some concern that we believe several important statements and statistical procedures are incorrect, with others potentially misleading. The aim of this report is to highlight the major concerns which we have identified. In particular, we believe the following items require further comment: (1) The use of coefficient of variation and its potential for misuse requires clarification, (2) pooled variance and measurement uncertainty across changes in measuring conditions has been oversimplified and is potentially misleading, (3) uncertainty in the results of estimated glomerular filtration rate (eGFR) do not include all known uncertainties, (4) the international normalized ratio (INR) calculation is incorrect, (5) the treatment of bias uncertainty is considered problematic, (6) the rules for evaluating combined uncertainty in functional relationships are incomplete, and (7) specific concerns with some individual statements.

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