Exhaustive expansion: A novel technique for analyzing complex data generated by higher-order polychromatic flow cytometry experiments

Janet C. Siebert, Lian Wang, Daniel P. Haley, Ann Romer, Bo Zheng, Wes Munsil, Kenton Gregory, Edwin B. Walker

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Background: The complex data sets generated by higher-order polychromatic flow cytometry experiments are a challenge to analyze. Here we describe Exhaustive Expansion, a data analysis approach for deriving hundreds to thousands of cell phenotypes from raw data, and for interrogating these phenotypes to identify populations of biological interest given the experimental context.Methods: We apply this approach to two studies, illustrating its broad applicability. The first examines the longitudinal changes in circulating human memory T cell populations within individual patients in response to a melanoma peptide (gp100209-2M) cancer vaccine, using 5 monoclonal antibodies (mAbs) to delineate subpopulations of viable, gp100-specific, CD8+ T cells. The second study measures the mobilization of stem cells in porcine bone marrow that may be associated with wound healing, and uses 5 different staining panels consisting of 8 mAbs each.Results: In the first study, our analysis suggests that the cell surface markers CD45RA, CD27 and CD28, commonly used in historical lower order (2-4 color) flow cytometry analysis to distinguish memory from naïve and effector T cells, may not be obligate parameters in defining central memory T cells (TCM). In the second study, we identify novel phenotypes such as CD29+CD31+CD56+CXCR4+CD90+Sca1-CD44+, which may characterize progenitor cells that are significantly increased in wounded animals as compared to controls.Conclusions: Taken together, these results demonstrate that Exhaustive Expansion supports thorough interrogation of complex higher-order flow cytometry data sets and aids in the identification of potentially clinically relevant findings.

Original languageEnglish (US)
Article number106
JournalJournal of Translational Medicine
Volume8
DOIs
StatePublished - Oct 30 2010

Fingerprint

T-cells
Flow cytometry
Flow Cytometry
T-Lymphocytes
Phenotype
Data storage equipment
Experiments
Monoclonal Antibodies
Hematopoietic Stem Cell Mobilization
Cancer Vaccines
Stem cells
Wound Healing
Population
Melanoma
Bone
Animals
Swine
Stem Cells
Color
Bone Marrow

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Exhaustive expansion : A novel technique for analyzing complex data generated by higher-order polychromatic flow cytometry experiments. / Siebert, Janet C.; Wang, Lian; Haley, Daniel P.; Romer, Ann; Zheng, Bo; Munsil, Wes; Gregory, Kenton; Walker, Edwin B.

In: Journal of Translational Medicine, Vol. 8, 106, 30.10.2010.

Research output: Contribution to journalArticle

Siebert, Janet C. ; Wang, Lian ; Haley, Daniel P. ; Romer, Ann ; Zheng, Bo ; Munsil, Wes ; Gregory, Kenton ; Walker, Edwin B. / Exhaustive expansion : A novel technique for analyzing complex data generated by higher-order polychromatic flow cytometry experiments. In: Journal of Translational Medicine. 2010 ; Vol. 8.
@article{1fb3439383c94706baa993a8257432a7,
title = "Exhaustive expansion: A novel technique for analyzing complex data generated by higher-order polychromatic flow cytometry experiments",
abstract = "Background: The complex data sets generated by higher-order polychromatic flow cytometry experiments are a challenge to analyze. Here we describe Exhaustive Expansion, a data analysis approach for deriving hundreds to thousands of cell phenotypes from raw data, and for interrogating these phenotypes to identify populations of biological interest given the experimental context.Methods: We apply this approach to two studies, illustrating its broad applicability. The first examines the longitudinal changes in circulating human memory T cell populations within individual patients in response to a melanoma peptide (gp100209-2M) cancer vaccine, using 5 monoclonal antibodies (mAbs) to delineate subpopulations of viable, gp100-specific, CD8+ T cells. The second study measures the mobilization of stem cells in porcine bone marrow that may be associated with wound healing, and uses 5 different staining panels consisting of 8 mAbs each.Results: In the first study, our analysis suggests that the cell surface markers CD45RA, CD27 and CD28, commonly used in historical lower order (2-4 color) flow cytometry analysis to distinguish memory from na{\"i}ve and effector T cells, may not be obligate parameters in defining central memory T cells (TCM). In the second study, we identify novel phenotypes such as CD29+CD31+CD56+CXCR4+CD90+Sca1-CD44+, which may characterize progenitor cells that are significantly increased in wounded animals as compared to controls.Conclusions: Taken together, these results demonstrate that Exhaustive Expansion supports thorough interrogation of complex higher-order flow cytometry data sets and aids in the identification of potentially clinically relevant findings.",
author = "Siebert, {Janet C.} and Lian Wang and Haley, {Daniel P.} and Ann Romer and Bo Zheng and Wes Munsil and Kenton Gregory and Walker, {Edwin B.}",
year = "2010",
month = "10",
day = "30",
doi = "10.1186/1479-5876-8-106",
language = "English (US)",
volume = "8",
journal = "Journal of Translational Medicine",
issn = "1479-5876",
publisher = "BioMed Central",

}

TY - JOUR

T1 - Exhaustive expansion

T2 - A novel technique for analyzing complex data generated by higher-order polychromatic flow cytometry experiments

AU - Siebert, Janet C.

AU - Wang, Lian

AU - Haley, Daniel P.

AU - Romer, Ann

AU - Zheng, Bo

AU - Munsil, Wes

AU - Gregory, Kenton

AU - Walker, Edwin B.

PY - 2010/10/30

Y1 - 2010/10/30

N2 - Background: The complex data sets generated by higher-order polychromatic flow cytometry experiments are a challenge to analyze. Here we describe Exhaustive Expansion, a data analysis approach for deriving hundreds to thousands of cell phenotypes from raw data, and for interrogating these phenotypes to identify populations of biological interest given the experimental context.Methods: We apply this approach to two studies, illustrating its broad applicability. The first examines the longitudinal changes in circulating human memory T cell populations within individual patients in response to a melanoma peptide (gp100209-2M) cancer vaccine, using 5 monoclonal antibodies (mAbs) to delineate subpopulations of viable, gp100-specific, CD8+ T cells. The second study measures the mobilization of stem cells in porcine bone marrow that may be associated with wound healing, and uses 5 different staining panels consisting of 8 mAbs each.Results: In the first study, our analysis suggests that the cell surface markers CD45RA, CD27 and CD28, commonly used in historical lower order (2-4 color) flow cytometry analysis to distinguish memory from naïve and effector T cells, may not be obligate parameters in defining central memory T cells (TCM). In the second study, we identify novel phenotypes such as CD29+CD31+CD56+CXCR4+CD90+Sca1-CD44+, which may characterize progenitor cells that are significantly increased in wounded animals as compared to controls.Conclusions: Taken together, these results demonstrate that Exhaustive Expansion supports thorough interrogation of complex higher-order flow cytometry data sets and aids in the identification of potentially clinically relevant findings.

AB - Background: The complex data sets generated by higher-order polychromatic flow cytometry experiments are a challenge to analyze. Here we describe Exhaustive Expansion, a data analysis approach for deriving hundreds to thousands of cell phenotypes from raw data, and for interrogating these phenotypes to identify populations of biological interest given the experimental context.Methods: We apply this approach to two studies, illustrating its broad applicability. The first examines the longitudinal changes in circulating human memory T cell populations within individual patients in response to a melanoma peptide (gp100209-2M) cancer vaccine, using 5 monoclonal antibodies (mAbs) to delineate subpopulations of viable, gp100-specific, CD8+ T cells. The second study measures the mobilization of stem cells in porcine bone marrow that may be associated with wound healing, and uses 5 different staining panels consisting of 8 mAbs each.Results: In the first study, our analysis suggests that the cell surface markers CD45RA, CD27 and CD28, commonly used in historical lower order (2-4 color) flow cytometry analysis to distinguish memory from naïve and effector T cells, may not be obligate parameters in defining central memory T cells (TCM). In the second study, we identify novel phenotypes such as CD29+CD31+CD56+CXCR4+CD90+Sca1-CD44+, which may characterize progenitor cells that are significantly increased in wounded animals as compared to controls.Conclusions: Taken together, these results demonstrate that Exhaustive Expansion supports thorough interrogation of complex higher-order flow cytometry data sets and aids in the identification of potentially clinically relevant findings.

UR - http://www.scopus.com/inward/record.url?scp=77958556812&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77958556812&partnerID=8YFLogxK

U2 - 10.1186/1479-5876-8-106

DO - 10.1186/1479-5876-8-106

M3 - Article

C2 - 21034498

AN - SCOPUS:77958556812

VL - 8

JO - Journal of Translational Medicine

JF - Journal of Translational Medicine

SN - 1479-5876

M1 - 106

ER -