Stromal transcriptional profiles reveal hierarchies of anatomical site, serum response and disease and identify disease specific pathways.

Synovial fibroblasts in persistent inflammatory arthritis have been suggested to have parallels with cancer growth and wound healing, both of which involve a stereotypical serum response programme. We tested the hypothesis that a serum response programme can be used to classify diseased tissues, and...

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Main Authors: Andrew Filer, Philipp Antczak, Greg N Parsonage, Holly M Legault, Margot O'Toole, Mark J Pearson, Andrew M Thomas, Dagmar Scheel-Toellner, Karim Raza, Christopher D Buckley, Francesco Falciani
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0120917
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author Andrew Filer
Philipp Antczak
Greg N Parsonage
Holly M Legault
Margot O'Toole
Mark J Pearson
Andrew M Thomas
Dagmar Scheel-Toellner
Karim Raza
Christopher D Buckley
Francesco Falciani
author_facet Andrew Filer
Philipp Antczak
Greg N Parsonage
Holly M Legault
Margot O'Toole
Mark J Pearson
Andrew M Thomas
Dagmar Scheel-Toellner
Karim Raza
Christopher D Buckley
Francesco Falciani
author_sort Andrew Filer
collection DOAJ
description Synovial fibroblasts in persistent inflammatory arthritis have been suggested to have parallels with cancer growth and wound healing, both of which involve a stereotypical serum response programme. We tested the hypothesis that a serum response programme can be used to classify diseased tissues, and investigated the serum response programme in fibroblasts from multiple anatomical sites and two diseases. To test our hypothesis we utilized a bioinformatics approach to explore a publicly available microarray dataset including rheumatoid arthritis (RA), osteoarthritis (OA) and normal synovial tissue, then extended those findings in a new microarray dataset representing matched synovial, bone marrow and skin fibroblasts cultured from RA and OA patients undergoing arthroplasty. The classical fibroblast serum response programme discretely classified RA, OA and normal synovial tissues. Analysis of low and high serum treated fibroblast microarray data revealed a hierarchy of control, with anatomical site the most powerful classifier followed by response to serum and then disease. In contrast to skin and bone marrow fibroblasts, exposure of synovial fibroblasts to serum led to convergence of RA and OA expression profiles. Pathway analysis revealed three inter-linked gene networks characterising OA synovial fibroblasts: Cell remodelling through insulin-like growth factors, differentiation and angiogenesis through _3 integrin, and regulation of apoptosis through CD44. We have demonstrated that Fibroblast serum response signatures define disease at the tissue level, and that an OA specific, serum dependent repression of genes involved in cell adhesion, extracellular matrix remodelling and apoptosis is a critical discriminator between cultured OA and RA synovial fibroblasts.
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spelling doaj-art-e27e205633494cda815af25738c138562025-08-20T02:34:07ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01103e012091710.1371/journal.pone.0120917Stromal transcriptional profiles reveal hierarchies of anatomical site, serum response and disease and identify disease specific pathways.Andrew FilerPhilipp AntczakGreg N ParsonageHolly M LegaultMargot O'TooleMark J PearsonAndrew M ThomasDagmar Scheel-ToellnerKarim RazaChristopher D BuckleyFrancesco FalcianiSynovial fibroblasts in persistent inflammatory arthritis have been suggested to have parallels with cancer growth and wound healing, both of which involve a stereotypical serum response programme. We tested the hypothesis that a serum response programme can be used to classify diseased tissues, and investigated the serum response programme in fibroblasts from multiple anatomical sites and two diseases. To test our hypothesis we utilized a bioinformatics approach to explore a publicly available microarray dataset including rheumatoid arthritis (RA), osteoarthritis (OA) and normal synovial tissue, then extended those findings in a new microarray dataset representing matched synovial, bone marrow and skin fibroblasts cultured from RA and OA patients undergoing arthroplasty. The classical fibroblast serum response programme discretely classified RA, OA and normal synovial tissues. Analysis of low and high serum treated fibroblast microarray data revealed a hierarchy of control, with anatomical site the most powerful classifier followed by response to serum and then disease. In contrast to skin and bone marrow fibroblasts, exposure of synovial fibroblasts to serum led to convergence of RA and OA expression profiles. Pathway analysis revealed three inter-linked gene networks characterising OA synovial fibroblasts: Cell remodelling through insulin-like growth factors, differentiation and angiogenesis through _3 integrin, and regulation of apoptosis through CD44. We have demonstrated that Fibroblast serum response signatures define disease at the tissue level, and that an OA specific, serum dependent repression of genes involved in cell adhesion, extracellular matrix remodelling and apoptosis is a critical discriminator between cultured OA and RA synovial fibroblasts.https://doi.org/10.1371/journal.pone.0120917
spellingShingle Andrew Filer
Philipp Antczak
Greg N Parsonage
Holly M Legault
Margot O'Toole
Mark J Pearson
Andrew M Thomas
Dagmar Scheel-Toellner
Karim Raza
Christopher D Buckley
Francesco Falciani
Stromal transcriptional profiles reveal hierarchies of anatomical site, serum response and disease and identify disease specific pathways.
PLoS ONE
title Stromal transcriptional profiles reveal hierarchies of anatomical site, serum response and disease and identify disease specific pathways.
title_full Stromal transcriptional profiles reveal hierarchies of anatomical site, serum response and disease and identify disease specific pathways.
title_fullStr Stromal transcriptional profiles reveal hierarchies of anatomical site, serum response and disease and identify disease specific pathways.
title_full_unstemmed Stromal transcriptional profiles reveal hierarchies of anatomical site, serum response and disease and identify disease specific pathways.
title_short Stromal transcriptional profiles reveal hierarchies of anatomical site, serum response and disease and identify disease specific pathways.
title_sort stromal transcriptional profiles reveal hierarchies of anatomical site serum response and disease and identify disease specific pathways
url https://doi.org/10.1371/journal.pone.0120917
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