Rare-Event Analysis in Flow Cytometry

doi:10.1016/j.cll.2007.05.013

Clinics in Laboratory Medicine

Volume 27, Issue 3, September 2007, Pages 627-652

https://doi.org/10.1016/j.cll.2007.05.013 Get rights and content

Technical aspects of rare-event detection are discussed in this article in a practical context, with two real-life examples. A growing number of flow cytometry-based assays depend on rare-event detection for basic science and clinical applications.

Section snippets

A survey of rare-event applications

The major histocompatibility complex (MHC)/tetramer assay has been developed to detect peptide-specific T cells [7]. Peptides are presented to T cells in the context of PE or allophycocyanine (APC)-labeled self-MHC tetramers. Tetramers bind specifically to T cells having the appropriate receptor. MHC class I tetramers, which detect peptide-specific CD8⁺ T cells, have been well characterized, whereas MHC class II tetramers, recognized by CD4⁺ T cells, now are coming into use. Tetramer

Sample concentration and flow rate

Because the event frequency is an inherent property of the sample, there is not much to be done about it, save preprocessing the sample to enrich the event of interest. Immunomagnetic separation sometimes is performed before flow cytometry for this purpose [50]. This is preferable for rare-event isolation, because it can greatly decrease time required to sort a rare population on a fluorescence-activated cell sorter, but the uncertainties of event recovery after preseparation may obscure the

Detection of cells expressing stem cell markers in normal human lung tissue

Performing rare-event flow cytometry on cells from solid organs presents several challenges. Tissue fragments must be digested and disaggregated mechanically before staining. Even the most meticulous preparation leaves cell clusters, dead cells, and cellular debris, all of which can interfere with analysis. In this example, human lung tissue was minced using a Becton Dickinson Medimachine, filtered though a 70-μ cell strainer, digested with collagenase, and separated on a Ficoll-Hypaque

Coda

Maximization of signal over noise, running appropriate controls, determining the lower limit of detection, and acquisition of an appropriate number of events are the elements of successful rare-event detection. When dealing with multiparameter datasets, it is useful to think of parameters as classifiers or outcomes. This facilitates a hierarchic analysis that avoids the all possible permutations problem (ie, 112 distinct parameter combinations in the last example). Having done this, it is

Acknowledgments

The authors would like to thank Kit Snow, Tom Franks, Erin McClelland, E. Michael Meyer, Darlene Monlish, Linda Moore, Peter Nobes, Melanie Pfeiffer, and David Roberts for their assistance with various aspects of the original data presented here.

References (61)

G. van den Engh
New applications of flow cytometry
Curr Opin Biotechnol
(1993)
N. Baumgarth et al.
A practical approach to multicolor flow cytometry for immunophenotyping
J Immunol Methods
(2000)
P.A. Muraro et al.
Rapid identification of local T cell expansion in inflammatory organ diseases by flow cytometric T cell receptor Vbeta analysis
J Immunol Methods
(2000)
D.H. Ryan et al.
Improved detection of rare CALLA-positive cells in peripheral blood using multiparameter flow cytometry
J Immunol Methods
(1984)
D. Ribatti
The discovery of endothelial progenitor cells. An historical review
Leuk Res
(2007)
O. Geifman-Holtzman et al.
The clinical utility of fetal cell sorting to determine prenatally fetal E/e or e/e Rh genotype from peripheral maternal blood
Am J Obstet Gynecol
(2000)
D. McIlroy et al.
Investigation of human spleen dendritic cell phenotype and distribution reveals evidence of in vivo activation in a subset of organ donors
Blood
(2001)
A.E. Morelli et al.
Potential of tolerogenic dendritic cells for transplantation
Semin Immunol
(2001)
H.J. Gross et al.
Model study detecting breast cancer cells in peripheral blood mononuclear cells at frequencies as low as 10(−7)
Proc Natl Acad Sci U S A
(1995)
J.I. Rosenblatt et al.
Theoretical basis for sampling statistics useful for detecting and isolating rare cells using flow cytometry and cell sorting
Cytometry
(1997)

A.D. Donnenberg et al.

Principles of rare event analysis by flow cytometry: detection of injected dendritic cells in draining lymphatic tissue

Clinical Immunology Newsletter

(1999)

V.S. Donnenberg et al.

Identification, rare-event detection and analysis of dendritic cell subsets in broncho-alveolar lavage fluid and peripheral blood by flow cytometry

Front Biosci

(2003)

J.D. Altman et al.

Phenotypic analysis of antigen-specific T lymphocytes

Science

(1996)

NIH Tetramer Core Facility at Emory University. Available at:...

V.C. Maino et al.

Identification of functional subsets by flow cytometry: intracellular detection of cytokine expression

Cytometry

(1998)

J.A. Listman et al.

Detection of rare apoptotic T cells in vivo

Cytometry

(1998)

A.J. Walle et al.

Aneuploidy as a marker of minimal residual disease in leukemia

Cancer Detect Prev

(1985)

M. Hussain et al.

Prostate cancer: flow cytometric methods for detection of bone marrow micrometastases

Cytometry

(1996)

M. Balic et al.

Comparison of two methods for enumerating circulating tumor cells in carcinoma patients

Cytometry B Clin Cytom

(2005)

W.J. Allard et al.

Tumor cells circulate in the peripheral blood of all major carcinomas but not in healthy subjects or patients with nonmalignant diseases

Clin Cancer Res

(2004)

J.E. Dick

Breast cancer stem cells revealed

Proc Natl Acad Sci U S A

(2003)

V.S. Donnenberg et al.

Multiple drug resistance in cancer revisited: the cancer stem cell hypothesis

J Clin Pharmacol

(2005)

Donnenberg VS, Luketich JD, Landreneau RJ, et al. Tumorigenic epithelial stem cells and their normal counterparts....

Donnenberg VS, Landreneau RJ, Donnenberg AD. Tumorigenic stem and progenitor cells: implications for the therapeutic...

M. Al-Hajj et al.

Prospective identification of tumorigenic breast cancer cells

Proc Natl Acad Sci U S A

(2003)

S.K. Singh et al.

Identification of human brain tumour initiating cells

Nature

(2004)

P.P. Szotek et al.

Ovarian cancer side population defines cells with stem cell-like characteristics and Mullerian Inhibiting Substance responsiveness

Proc Natl Acad Sci U S A

(2006)

M.A. Goodell et al.

Isolation and functional properties of murine hematopoietic stem cells that are replicating in vivo

J Exp Med

(1996)

S. Zhou et al.

The ABC transporter Bcrp1/ABCG2 is expressed in a wide variety of stem cells and is a molecular determinant of the side-population phenotype

Nat Med

(2001)

C. Muller et al.

Flow cytometric analysis of protein phosphorylation in the hematopoetic system

Leuk Lymphoma

(1998)

Cited by (79)

Data-centric workloads with MPI_Sort
2024, Journal of Parallel and Distributed Computing
Sorting is a fundamental task in computing and plays a central role in information technology. The advent of rack-scale and warehouse-size data processing shaped the architecture of data analysis platforms towards supercomputing. In turn, established techniques on supercomputers have become relevant to a wider range of application domains. This work is concerned with multi-way mergesort with exact splitting on distributed memory architectures. At its core, our approach leverages a novel and parallel algorithm for multi-way selection problems. Remarkably concise, the algorithm relies on MPI_Allgather and MPI_ReduceScatter_block, two collective communication schemes that find hardware support in most high-end networks. A software implementation of our approach is used to process the Terabyte-size Data Challenge 2 signal, released by the SKA radio telescopes organization. On the supercomputer considered herein, our approach outperforms the state of the art by up to 2.6X using 9,216 cores. Our implementation is released as a compact open source library compliant to the MPI programming model. By supporting the most popular elementary key types, and arbitrary fixed-size value types, the library can be straightforwardly integrated into third-party MPI-based software.
Mitigation and suppression of rare events in weakly coupled lasers
2023, Chaos, Solitons and Fractals
We consider an asymmetric laser system which displays mixed-mode oscillations and hyperchaos. This system consists of two laser oscillators which are weakly and bidirectionally coupled, where the asymmetry is induced by a mismatch between the laser pump parameters. The coupling scheme via saturable absorbers, however, is built up with a beam combining process which incorporates the electric fields of both laser oscillators. This procedure, which is relevant in semiconductor and solid-state lasers, is implemented in the present molecular laser model.
In our numerical simulations and time series analysis we show that for small enough coupling strength, below the chaotic phase synchronization threshold, the asymmetric laser system displays extreme rare events in one of the lasers whose occurrence can be mitigated and suppressed by optical feedback. These episodes are outliers in the time series from the laser intensity and the return time intervals, and are reminiscent of Dragon-Kings. We estimate the correlation dimensions and Lyapunov exponents from the time series, which suggest the ubiquity of hyperchaotic dynamics irrespective of the occurrence or lack of extreme rare events in these time series.
Acquired B-cell deficiency secondary to B-cell-depleting therapies
2022, Journal of Immunological Methods
The advantage of the newer biological therapies is that the immunosuppressive effect is targeted, in contrast, to the standard, traditional immunomodulatory agents, which have a more global effect. However, there are unintended targets and consequences, even to these “precise” therapeutics, leading to acquired or secondary immunodeficiencies. Besides depleting specific cellular immune subsets, these biological agents, which include monoclonal antibodies against biologically relevant molecules, often have broader functional immune consequences, which become apparent over time. This review focuses on acquired B-cell immunodeficiency, secondary to the use of B-cell depleting therapeutic agents. Among the many adverse consequences of B-cell depletion is the risk of hypogammaglobulinemia, failure of B-cell recovery, impaired B-cell differentiation, and risk of infections. Factors, which modulate the outcomes of B-cell depleting therapies, include the intrinsic nature of the underlying disease, the concomitant use of other immunomodulatory agents, and the clinical status of the patient and other co-existing morbidities. This article seeks to explore the mechanism of action of B-cell depleting agents, the clinical utility and adverse effects of these therapies, and the relevance of systematic and serial laboratory immune monitoring in identifying patients at risk for developing immunological complications, and who may benefit from early intervention to mitigate the secondary consequences. Though these biological drugs are gaining widespread use, a harmonized approach to immune evaluation pre-and post-treatment has not yet gained traction across multiple clinical specialties, because of which, the true prevalence of these adverse events cannot be determined in the treated population, and a systematic and evidence-based dosing schedule cannot be developed. The aim of this review is to bring these issues into focus, and initiate a multi-specialty, data-driven approach to immune monitoring.
Development and validation of a sensitive flow cytometric method for determining CECs in RBC products
2022, Clinica Chimica Acta
Citation Excerpt :
Manipulation of WB may reduce the accuracy for determination of CECs due to their rarity and fragility. Alternatively, non-manipulated WB could be assessed directly, which has been used to determine rare cell populations at a frequency lower than 1 / 1000 [13]. The application of counting beads (ie.
Subpopulations of immature red blood cells (RBCs) named CD71⁺ erythroid cells (CECs) with different properties may contribute to RBC transfusion outcomes. However, it is challenging to quantify CECs in leukoreduced RCCs and whole blood due to their rarity and fragility. Current flow cytometry methods are not applicable to leukoreduced RCCs as there is limited peripheral blood mononuclear cells (PBMCs) to use for determination of CECs. We have developed and validated a flow cytometry method for quantifying CECs in WB.
We determined optimal PE-Cy7-CD235a, BV711-CD71, APC-CD45 concentrations and instrument setting by titration. Linearity and level of detection was determined by spiking labelled PBMCs from cord blood units into unlabeled WB. Low, medium, high levels of CECs were used to determine intra- and inter -run precision.
Detection of CECs was linear (R² = 0.98) over the range of concentrations assessed with a limit of detection of 0.005%. The overall CVs for the intra- and inter-run precision were 6.9% and 9.7%.
We developed a simple, sensitive, and cost-effective flow cytometric method for quantifying the proportion of CECs in non-manipulated WB, which could help understand the impact of RBC products on recipient transfusion outcomes.
Image Analysis Using Machine Learning for Automated Detection of Hemoglobin H Inclusions in Blood Smears - A Method for Morphologic Detection of Rare Cells
2021, Journal of Pathology Informatics
Background: Morphologic rare cell detection is a laborious, operator-dependent process which has the potential to be improved by the use of image analysis using artificial intelligence. Detection of rare hemoglobin H (HbH) inclusions in red cells in the peripheral blood is a common screening method for alpha-thalassemia. This study aims to develop a convolutional neural network-based algorithm for the detection of HbH inclusions. Methods: Digital images of HbH-positive and HbH-negative blood smears were used to train and test the software. The software performance was tested on images obtained at various magnifications and on different scanning platforms. Another model was developed for total red cell counting and was used to confirm HbH cell frequency in alpha-thalassemia trait. The threshold minimum red cells to image for analysis was determined by Poisson modeling and validated on image sets. Results: The sensitivity and specificity of the software for HbH+ cells on images obtained at ×100, ×60, and ×40 objectives were close to 91% and 99%, respectively. When an AI-aided diagnostic model was tested on a pilot of 40 whole slide images (WSIs), good inter-rater reliability and high sensitivity and specificity of slide-level classification were obtained. Using the lowest frequency of HbH+ cells (1 in 100,000) observed in our study, we estimated that a minimum of 2.4 × 10⁶ red cells would need to be analyzed to reduce misclassification at the slide level. The minimum required smear size was validated on 78 image sets which confirmed its validity. Conclusions: WSI image analysis can be utilized effectively for morphologic rare cell detection. The software can be further developed on WISs and evaluated in future clinical validation studies comparing AI-aided diagnosis with the routine diagnostic method.
Can flow cytometry reinvent the sentinel lymph node concept in gastric cancer patients?
2018, Journal of Surgical Research
Citation Excerpt :
Flow cytometry has been used for diagnosis of hematological malignancies and also for the analysis of malignant effusions of various epithelial tumors.11,12 It has been shown to be a fast and reliable method that combines the high specificity of morphological methods and the high sensitivity of molecular methods.11,12 To evaluate the accuracy and usefulness of flow cytometry for intraoperative detection of SLN metastases, the data obtained with flow cytometry were compared with the frozen section data and with the use of RT-qPCR for SLN metastases detection.
The focused sentinel lymph node (SLN) concept we proposed previously relied on real time-quantitative polymerase chain reaction (RT-qPCR) to detect tumor cells, which is too elaborate for intraoperative use. Therefore, we evaluated flow cytometry for intraoperative detection of tumor cells in SLNs.
Sixty-five consecutive gastric cancer patients were included. SLN analysis was carried out for a single SLN from each patient, using the molecular methods of RT-qPCR (first 30 patients) and flow cytometry (final 35 patients). All LNs underwent hematoxylin and eosin staining and immunohistochemical examination.
Extraction of the SLN from a high-risk station was an important determinant for accurate prediction of LN metastases. For RT-qPCR, the sensitivity and specificity of detection were 72.7% and 81.8%, respectively, and for flow cytometry, 36.8% and 100%, respectively. When only high-risk SLNs were analyzed and specimens with <10% viability of leukocytes were excluded, the sensitivity and specificity of flow cytometry were 60% and 100%, respectively. Multivariate analysis identified significant predictors for LN metastases as the molecular method of SLN analysis (P = 0.021; 95% confidence interval [CI]: 1.304-24.284) and lymphovascular invasion (P = 0.002; 95% CI: 2.142-28.555). In subgroup analysis of high-risk SLNs, only RT-qPCR was a significant predictor for LN metastases (P = 0.016; 95% CI: 1.581-91.084).
Flow cytometry of high-risk SLNs, excluding specimens with low cell viability is a rapid, cost-effective, widely obtainable, and highly specific method for SLN metastases detection although it lacks the necessary sensitivity. Therefore, it cannot be recommended as a stand-alone method for the detection of LN metastases during operations.

View all citing articles on Scopus

: This work was supported by grants BC044784 and BC032981 from the Department of Defense, a grant from the National Institutes of Health National Institute of Arthritis and Musculoskeletal and Skin Diseases (NO1 AR9 2239), and the generous support of the Hillman Foundation.

View full text

Rare-Event Analysis in Flow Cytometry

Section snippets

A survey of rare-event applications

Sample concentration and flow rate

Detection of cells expressing stem cell markers in normal human lung tissue

Coda

Acknowledgments

Curr Opin Biotechnol

J Immunol Methods

J Immunol Methods

J Immunol Methods

Leuk Res

Am J Obstet Gynecol

Blood

Semin Immunol

Model study detecting breast cancer cells in peripheral blood mononuclear cells at frequencies as low as 10(−7)

Proc Natl Acad Sci U S A

Theoretical basis for sampling statistics useful for detecting and isolating rare cells using flow cytometry and cell sorting

Cytometry

Principles of rare event analysis by flow cytometry: detection of injected dendritic cells in draining lymphatic tissue

Clinical Immunology Newsletter

Identification, rare-event detection and analysis of dendritic cell subsets in broncho-alveolar lavage fluid and peripheral blood by flow cytometry

Front Biosci

Phenotypic analysis of antigen-specific T lymphocytes

Science

Identification of functional subsets by flow cytometry: intracellular detection of cytokine expression

Cytometry

Detection of rare apoptotic T cells in vivo

Cytometry

Aneuploidy as a marker of minimal residual disease in leukemia

Cancer Detect Prev

Prostate cancer: flow cytometric methods for detection of bone marrow micrometastases

Cytometry

Comparison of two methods for enumerating circulating tumor cells in carcinoma patients

Cytometry B Clin Cytom

Tumor cells circulate in the peripheral blood of all major carcinomas but not in healthy subjects or patients with nonmalignant diseases

Clin Cancer Res

Breast cancer stem cells revealed

Proc Natl Acad Sci U S A

Multiple drug resistance in cancer revisited: the cancer stem cell hypothesis

J Clin Pharmacol

Prospective identification of tumorigenic breast cancer cells

Proc Natl Acad Sci U S A

Identification of human brain tumour initiating cells

Nature

Ovarian cancer side population defines cells with stem cell-like characteristics and Mullerian Inhibiting Substance responsiveness

Proc Natl Acad Sci U S A

Isolation and functional properties of murine hematopoietic stem cells that are replicating in vivo

J Exp Med

The ABC transporter Bcrp1/ABCG2 is expressed in a wide variety of stem cells and is a molecular determinant of the side-population phenotype

Nat Med

Flow cytometric analysis of protein phosphorylation in the hematopoetic system

Leuk Lymphoma