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  5. LSC Abstract – GM-CSF drives human lung tissue macrophages towards a more pro-inflammatory phenotype

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Article
en
2016

LSC Abstract – GM-CSF drives human lung tissue macrophages towards a more pro-inflammatory phenotype

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en
2016
DOI: 10.1183/13993003.congress-2016.pp206

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Peter J Barnes
Peter J Barnes

Imperial College London

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Jessica Tilman
Peter J Barnes
Louise Donnelly

Abstract

COPD is associated with elevated matrix metalloprotease-9 (MMP9) and pro-inflammatory cytokines, e.g. TNFα, which may be derived from macrophages (mΦ). Altering mΦ phenotype towards a resolving cell maybe therapeutic. GM-CSF and M-CSF are used during differentiation of monocytes in vitro to influence phenotype, thus this study assessed whether GM-CSF or M-CSF could alter mature mΦ phenotype. Human lung tissue mΦ (TmΦ) from controls (C;n=5) and COPD patients (n=5) were cultured in media alone or with GM-CSF or M-CSF for 6d to assess plasticity. Levels of TNFα were measured by ELISA after 24h stimulation with LPS (10ng/ml) and MMP9 expressing by RTqPCR. Basal release of TNFα did not differ between culture conditions or subject group but following LPS stimulation, TmΦ cultured in GM-CSF had significantly (p<0.01) higher TNFα release compared to mΦ cultured in media, with M-CSF having no effect (Fig 1A). MMP9 expression did not change between culture conditions for any subject group (Fig 1B), however there is a trend towards higher TNFα and MMP9 in COPD TmΦ compared to control. TmΦ can be manipulated by GM-CSF towards a more inflammatory phenotype, although this is limited to changes in TNFα. Elevated GM-CSF in COPD patients may be driving altered mΦ phenotype, thus targeting the GM-CSF driven phenotype might be a novel anti-inflammatory strategy. Changes in TNFα and MMP9

How to cite this publication

Jessica Tilman, Peter J Barnes, Louise Donnelly (2016). LSC Abstract – GM-CSF drives human lung tissue macrophages towards a more pro-inflammatory phenotype. , DOI: https://doi.org/10.1183/13993003.congress-2016.pp206.

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Publication Details

Type

Article

Year

2016

Authors

3

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1183/13993003.congress-2016.pp206

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