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Molecular phenotypes distinguish patients with relatively stable from progressive idiopathic pulmonary fibrosis (IPF).


ABSTRACT: BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, chronic interstitial lung disease that is unresponsive to current therapy and often leads to death. However, the rate of disease progression differs among patients. We hypothesized that comparing the gene expression profiles between patients with stable disease and those in which the disease progressed rapidly will lead to biomarker discovery and contribute to the understanding of disease pathogenesis. METHODOLOGY AND PRINCIPAL FINDINGS: To begin to address this hypothesis, we applied Serial Analysis of Gene Expression (SAGE) to generate lung expression profiles from diagnostic surgical lung biopsies in 6 individuals with relatively stable (or slowly progressive) IPF and 6 individuals with progressive IPF (based on changes in DLCO and FVC over 12 months). Our results indicate that this comprehensive lung IPF SAGE transcriptome is distinct from normal lung tissue and other chronic lung diseases. To identify candidate markers of disease progression, we compared the IPF SAGE profiles in stable and progressive disease, and identified a set of 102 transcripts that were at least 5-fold up regulated and a set of 89 transcripts that were at least 5-fold down regulated in the progressive group (P-value

SUBMITTER: Boon K 

PROVIDER: S-EPMC2661376 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

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Molecular phenotypes distinguish patients with relatively stable from progressive idiopathic pulmonary fibrosis (IPF).

Boon Kathy K   Bailey Nathaniel W NW   Yang Jun J   Steel Mark P MP   Groshong Steve S   Kervitsky Dolly D   Brown Kevin K KK   Schwarz Marvin I MI   Schwartz David A DA  

PloS one 20090406 4


<h4>Background</h4>Idiopathic pulmonary fibrosis (IPF) is a progressive, chronic interstitial lung disease that is unresponsive to current therapy and often leads to death. However, the rate of disease progression differs among patients. We hypothesized that comparing the gene expression profiles between patients with stable disease and those in which the disease progressed rapidly will lead to biomarker discovery and contribute to the understanding of disease pathogenesis.<h4>Methodology and pr  ...[more]

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