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A Method for Identification and Analysis of Non-Overlapping Myeloid Immunophenotypes in Humans
The development of flow cytometric biomarkers in human studies and clinical trials has been slowed by inconsistent sample processing, use of cell surface markers, and reporting of immunophenotypes. Additionally, the function(s) of distinct cell types as biomarkers cannot be accurately defined withou...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4370675/ https://www.ncbi.nlm.nih.gov/pubmed/25799053 http://dx.doi.org/10.1371/journal.pone.0121546 |
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author | Gustafson, Michael P. Lin, Yi Maas, Mary L. Van Keulen, Virginia P. Johnston, Patrick B. Peikert, Tobias Gastineau, Dennis A. Dietz, Allan B. |
author_facet | Gustafson, Michael P. Lin, Yi Maas, Mary L. Van Keulen, Virginia P. Johnston, Patrick B. Peikert, Tobias Gastineau, Dennis A. Dietz, Allan B. |
author_sort | Gustafson, Michael P. |
collection | PubMed |
description | The development of flow cytometric biomarkers in human studies and clinical trials has been slowed by inconsistent sample processing, use of cell surface markers, and reporting of immunophenotypes. Additionally, the function(s) of distinct cell types as biomarkers cannot be accurately defined without the proper identification of homogeneous populations. As such, we developed a method for the identification and analysis of human leukocyte populations by the use of eight 10-color flow cytometric protocols in combination with novel software analyses. This method utilizes un-manipulated biological sample preparation that allows for the direct quantitation of leukocytes and non-overlapping immunophenotypes. We specifically designed myeloid protocols that enable us to define distinct phenotypes that include mature monocytes, granulocytes, circulating dendritic cells, immature myeloid cells, and myeloid derived suppressor cells (MDSCs). We also identified CD123 as an additional distinguishing marker for the phenotypic characterization of immature LIN(-)CD33(+)HLA-DR(-) MDSCs. Our approach permits the comprehensive analysis of all peripheral blood leukocytes and yields data that is highly amenable for standardization across inter-laboratory comparisons for human studies. |
format | Online Article Text |
id | pubmed-4370675 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-43706752015-04-04 A Method for Identification and Analysis of Non-Overlapping Myeloid Immunophenotypes in Humans Gustafson, Michael P. Lin, Yi Maas, Mary L. Van Keulen, Virginia P. Johnston, Patrick B. Peikert, Tobias Gastineau, Dennis A. Dietz, Allan B. PLoS One Research Article The development of flow cytometric biomarkers in human studies and clinical trials has been slowed by inconsistent sample processing, use of cell surface markers, and reporting of immunophenotypes. Additionally, the function(s) of distinct cell types as biomarkers cannot be accurately defined without the proper identification of homogeneous populations. As such, we developed a method for the identification and analysis of human leukocyte populations by the use of eight 10-color flow cytometric protocols in combination with novel software analyses. This method utilizes un-manipulated biological sample preparation that allows for the direct quantitation of leukocytes and non-overlapping immunophenotypes. We specifically designed myeloid protocols that enable us to define distinct phenotypes that include mature monocytes, granulocytes, circulating dendritic cells, immature myeloid cells, and myeloid derived suppressor cells (MDSCs). We also identified CD123 as an additional distinguishing marker for the phenotypic characterization of immature LIN(-)CD33(+)HLA-DR(-) MDSCs. Our approach permits the comprehensive analysis of all peripheral blood leukocytes and yields data that is highly amenable for standardization across inter-laboratory comparisons for human studies. Public Library of Science 2015-03-23 /pmc/articles/PMC4370675/ /pubmed/25799053 http://dx.doi.org/10.1371/journal.pone.0121546 Text en © 2015 Gustafson et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Gustafson, Michael P. Lin, Yi Maas, Mary L. Van Keulen, Virginia P. Johnston, Patrick B. Peikert, Tobias Gastineau, Dennis A. Dietz, Allan B. A Method for Identification and Analysis of Non-Overlapping Myeloid Immunophenotypes in Humans |
title | A Method for Identification and Analysis of Non-Overlapping Myeloid Immunophenotypes in Humans |
title_full | A Method for Identification and Analysis of Non-Overlapping Myeloid Immunophenotypes in Humans |
title_fullStr | A Method for Identification and Analysis of Non-Overlapping Myeloid Immunophenotypes in Humans |
title_full_unstemmed | A Method for Identification and Analysis of Non-Overlapping Myeloid Immunophenotypes in Humans |
title_short | A Method for Identification and Analysis of Non-Overlapping Myeloid Immunophenotypes in Humans |
title_sort | method for identification and analysis of non-overlapping myeloid immunophenotypes in humans |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4370675/ https://www.ncbi.nlm.nih.gov/pubmed/25799053 http://dx.doi.org/10.1371/journal.pone.0121546 |
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