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Gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials

BACKGROUND: Clinically useful biomarkers for patient stratification and monitoring of disease progression and drug response are in big demand in drug development and for addressing potential safety concerns. Many diseases influence the frequency and phenotype of cells found in the peripheral blood a...

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Autores principales: Letzkus, Martin, Luesink, Evert, Starck-Schwertz, Sandrine, Bigaud, Marc, Mirza, Fareed, Hartmann, Nicole, Gerstmayer, Bernhard, Janssen, Uwe, Scherer, Andreas, Schumacher, Martin M, Verles, Aurelie, Vitaliti, Alessandra, Nirmala, Nanguneri, Johnson, Keith J, Staedtler, Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4424390/
https://www.ncbi.nlm.nih.gov/pubmed/25984272
http://dx.doi.org/10.1186/s40169-014-0036-z
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author Letzkus, Martin
Luesink, Evert
Starck-Schwertz, Sandrine
Bigaud, Marc
Mirza, Fareed
Hartmann, Nicole
Gerstmayer, Bernhard
Janssen, Uwe
Scherer, Andreas
Schumacher, Martin M
Verles, Aurelie
Vitaliti, Alessandra
Nirmala, Nanguneri
Johnson, Keith J
Staedtler, Frank
author_facet Letzkus, Martin
Luesink, Evert
Starck-Schwertz, Sandrine
Bigaud, Marc
Mirza, Fareed
Hartmann, Nicole
Gerstmayer, Bernhard
Janssen, Uwe
Scherer, Andreas
Schumacher, Martin M
Verles, Aurelie
Vitaliti, Alessandra
Nirmala, Nanguneri
Johnson, Keith J
Staedtler, Frank
author_sort Letzkus, Martin
collection PubMed
description BACKGROUND: Clinically useful biomarkers for patient stratification and monitoring of disease progression and drug response are in big demand in drug development and for addressing potential safety concerns. Many diseases influence the frequency and phenotype of cells found in the peripheral blood and the transcriptome of blood cells. Changes in cell type composition influence whole blood gene expression analysis results and thus the discovery of true transcript level changes remains a challenge. We propose a robust and reproducible procedure, which includes whole transcriptome gene expression profiling of major subsets of immune cell cells directly sorted from whole blood. METHODS: Target cells were enriched using magnetic microbeads and an autoMACS® Pro Separator (Miltenyi Biotec). Flow cytometric analysis for purity was performed before and after magnetic cell sorting. Total RNA was hybridized on HGU133 Plus 2.0 expression microarrays (Affymetrix, USA). CEL files signal intensity values were condensed using RMA and a custom CDF file (EntrezGene-based). RESULTS: Positive selection by use of MACS® Technology coupled to transcriptomics was assessed for eight different peripheral blood cell types, CD14+ monocytes, CD3+, CD4+, or CD8+ T cells, CD15+ granulocytes, CD19+ B cells, CD56+ NK cells, and CD45+ pan leukocytes. RNA quality from enriched cells was above a RIN of eight. GeneChip analysis confirmed cell type specific transcriptome profiles. Storing whole blood collected in an EDTA Vacutainer® tube at 4°C followed by MACS does not activate sorted cells. Gene expression analysis supports cell enrichment measurements by MACS. CONCLUSIONS: The proposed workflow generates reproducible cell-type specific transcriptome data which can be translated to clinical settings and used to identify clinically relevant gene expression biomarkers from whole blood samples. This procedure enables the integration of transcriptomics of relevant immune cell subsets sorted directly from whole blood in clinical trial protocols.
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spelling pubmed-44243902015-05-15 Gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials Letzkus, Martin Luesink, Evert Starck-Schwertz, Sandrine Bigaud, Marc Mirza, Fareed Hartmann, Nicole Gerstmayer, Bernhard Janssen, Uwe Scherer, Andreas Schumacher, Martin M Verles, Aurelie Vitaliti, Alessandra Nirmala, Nanguneri Johnson, Keith J Staedtler, Frank Clin Transl Med Research BACKGROUND: Clinically useful biomarkers for patient stratification and monitoring of disease progression and drug response are in big demand in drug development and for addressing potential safety concerns. Many diseases influence the frequency and phenotype of cells found in the peripheral blood and the transcriptome of blood cells. Changes in cell type composition influence whole blood gene expression analysis results and thus the discovery of true transcript level changes remains a challenge. We propose a robust and reproducible procedure, which includes whole transcriptome gene expression profiling of major subsets of immune cell cells directly sorted from whole blood. METHODS: Target cells were enriched using magnetic microbeads and an autoMACS® Pro Separator (Miltenyi Biotec). Flow cytometric analysis for purity was performed before and after magnetic cell sorting. Total RNA was hybridized on HGU133 Plus 2.0 expression microarrays (Affymetrix, USA). CEL files signal intensity values were condensed using RMA and a custom CDF file (EntrezGene-based). RESULTS: Positive selection by use of MACS® Technology coupled to transcriptomics was assessed for eight different peripheral blood cell types, CD14+ monocytes, CD3+, CD4+, or CD8+ T cells, CD15+ granulocytes, CD19+ B cells, CD56+ NK cells, and CD45+ pan leukocytes. RNA quality from enriched cells was above a RIN of eight. GeneChip analysis confirmed cell type specific transcriptome profiles. Storing whole blood collected in an EDTA Vacutainer® tube at 4°C followed by MACS does not activate sorted cells. Gene expression analysis supports cell enrichment measurements by MACS. CONCLUSIONS: The proposed workflow generates reproducible cell-type specific transcriptome data which can be translated to clinical settings and used to identify clinically relevant gene expression biomarkers from whole blood samples. This procedure enables the integration of transcriptomics of relevant immune cell subsets sorted directly from whole blood in clinical trial protocols. Springer 2014-11-13 /pmc/articles/PMC4424390/ /pubmed/25984272 http://dx.doi.org/10.1186/s40169-014-0036-z Text en Copyright © 2014 Letzkus et al.; licensee Springer. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
spellingShingle Research
Letzkus, Martin
Luesink, Evert
Starck-Schwertz, Sandrine
Bigaud, Marc
Mirza, Fareed
Hartmann, Nicole
Gerstmayer, Bernhard
Janssen, Uwe
Scherer, Andreas
Schumacher, Martin M
Verles, Aurelie
Vitaliti, Alessandra
Nirmala, Nanguneri
Johnson, Keith J
Staedtler, Frank
Gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials
title Gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials
title_full Gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials
title_fullStr Gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials
title_full_unstemmed Gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials
title_short Gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials
title_sort gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4424390/
https://www.ncbi.nlm.nih.gov/pubmed/25984272
http://dx.doi.org/10.1186/s40169-014-0036-z
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