Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Gene Expression Profiling in the Lungs of Patients with Chronic Obstructive Pulmonary Disease (COPD) and Lung Cancer

ABSTRACT: COPD is a common and disabling lung disease for which very few therapeutic options are currently available. We reasoned that global gene expression profiling of COPD lungs could reveal previously unidentified disease pathways for potential therapeutic interventions. Forty-eight human lung samples were obtained from lungs or lobes resected for small peripheral lung lesions (5 non-smokers, 21 GOLD 0, 9 GOLD 1, 10 GOLD 2 and 3 GOLD 3 patients). mRNA from the specimens was profiled using Agilent’s Functional ID v2.0 array which contains 23,720 sequences. Quantitative morphometric analysis of the specimens revealed that the samples contained a variable proportion of airways, blood vessels and parenchyma. Incorporating these data into a model relating gene expression to % predicted forced expiratory flow between 25 and 75% of forced expiratory volume (FEF 25-75 % P) revealed a signature gene set of 203 transcripts. Genes involved in extracellular matrix synthesis/degradation, oxidative stress and cell proliferation were among the up-regulated genes whereas genes which participate in nicotine metabolism, elastic fiber homeostasis and anti-inflammatory response were down-regulated. Immunohistochemistry confirmed expression of urokinase (PLAU), urokinanse receptor (PLAUR) and thrombospondin (THBS1) by alveolar macrophages and small airway epithelial cells. Genes in this pathway have been shown to be involved in transforming growth factor beta-1 (TGF?1) and matrix metalloproteinase (MMP) activation and are subject to inhibition by serpin E2. Interestingly, both TGF?1 and serpin E2 have been identified as candidate genes in COPD genetic linkage and association studies. The results thus provide a possible link between these two powerful approaches to identify potential therapeutic targets. (255 words) Forty-eight human lung samples were obtained from lungs or lobes resected for small peripheral lung lesions (5 non-smokers, 21 GOLD 0, 9 GOLD 1, 10 GOLD 2 and 3 GOLD 3 patients). mRNA from the specimens was profiled using Agilent’s Functional ID v2.0 array which contains 23,720 sequences. Quantitative morphometric analysis of the specimens revealed that the samples contained a variable proportion of airways, blood vessels and parenchyma. Incorporating these data into a model relating gene expression to % predicted forced expiratory flow between 25 and 75% of forced expiratory volume (FEF 25-75 % P) revealed a signature gene set of 203 transcripts.

ORGANISM(S): Homo sapiens

SUBMITTER: serguei stepaniants

PROVIDER: E-GEOD-8500 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Gene expression profiling in patients with chronic obstructive pulmonary disease and lung cancer.

Wang I-Ming IM Stepaniants Sergey S Boie Yves Y Mortimer James R JR Kennedy Brian B Elliott Mark M Hayashi Shizu S Loy Leanna L Coulter Silvija S Cervino Sandra S Harris Jennifer J Thornton Michele M Raubertas Richard R Roberts Chris C Hogg Jim C JC Crackower Michael M O'Neill Gary G Paré Peter D PD

American journal of respiratory and critical care medicine 20071101 4

<h4>Rationale</h4>Chronic obstructive lung disease (COPD) is a common and disabling lung disease for which there are few therapeutic options.<h4>Objectives</h4>We reasoned that gene expression profiling of COPD lungs could reveal previously unidentified disease pathways.<h4>Methods</h4>Forty-eight human lung samples were obtained from tissue resected from five nonsmokers, 21 GOLD (Global Initiative for Chronic Obstructive Lung Disease) stage 0, 9 GOLD stage 1, 10 GOLD stage 2, and 3 GOLD stage 3 ...[more]

PMID: 17975202

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Project description:<p>Progressive decline in lung function is a hallmark of chronic obstructive pulmonary disease (COPD). Although airway dysbiosis occurs in COPD, whether it contributes to disease progression remains unknown. Here, through a longitudinal analysis on 181 COPD individuals from two large cohorts involving four UK clinical centers, we showed that baseline airway dysbiosis, characterized by enrichment of opportunistic pathogenic taxa, was associated with rapid forced expiratory volume in one second (FEV1) decline over two years. Co-presence of Moraxella, Staphylococcus and Stenotrophomonas was associated with an accelerated FEV1 decline by 139.7 mL/year. The dysbiosis was associated with exacerbation-related FEV1 fall and sudden FEV1 fall at clinical stability, two critical events contributing to long-term FEV1 decline. The microbiota association with FEV1 decline was validated in a third, independent cohort in China. Human multi-omics, murine and cellular mechanistic studies showed that chronic airway colonization of Staphylococcus aureus promoted lung function decline through producing homocysteine, which elicited an apoptosis-to-NETosis shift in neutrophils toward persistent inflammation via AKT1-S100A8/A9 axis. Prophylactic and therapeutic depletion of S. aureus via bacteriophage restored lung function in emphysema mice. These results provide a fresh approach to slow COPD progression by targeting the airway microbiome.</p><p><br></p><p><strong>Linked studies:</strong></p><p><strong>UPLC-MS/MS assays</strong> of human samples are reported in this study.</p><p><strong>UPLC-MS/MS assays</strong> of murine samples are reported in<strong> </strong><a href='https://www.ebi.ac.uk/metabolights/MTBLS6894' rel='noopener noreferrer' target='_blank'><strong>MTBLS6894</strong></a>.</p><p><strong>UPLC-MS/MS assays</strong> of original cohort human samples are reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS4017' rel='noopener noreferrer' target='_blank'><strong>MTBLS4017</strong></a>.</p>

Dataset Information

Gene Expression Profiling in the Lungs of Patients with Chronic Obstructive Pulmonary Disease (COPD) and Lung Cancer

Publications

Gene expression profiling in patients with chronic obstructive pulmonary disease and lung cancer.

Similar Datasets

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