Dataset Information

Expression profiling of laser-microdissected intrapulmonary arteries in hypoxia-induced pulmonary hypertension.

ABSTRACT: Chronic hypoxia influences gene expression in the lung resulting in pulmonary hypertension and vascular remodelling. For specific investigation of the vascular compartment, laser-microdissection of intrapulmonary arteries was combined with array profiling.Analysis was performed on mice subjected to 1, 7 and 21 days of hypoxia (FiO2 = 0.1) using nylon filters (1176 spots). Changes in the expression of 29, 38, and 42 genes were observed at day 1, 7, and 21, respectively. Genes were grouped into 5 different classes based on their time course of response. Gene regulation obtained by array analysis was confirmed by real-time PCR. Additionally, the expression of the growth mediators PDGF-B, TGF-beta, TSP-1, SRF, FGF-2, TIE-2 receptor, and VEGF-R1 were determined by real-time PCR. At day 1, transcription modulators and ion-related proteins were predominantly regulated. However, at day 7 and 21 differential expression of matrix producing and degrading genes was observed, indicating ongoing structural alterations. Among the 21 genes upregulated at day 1, 15 genes were identified carrying potential hypoxia response elements (HREs) for hypoxia-induced transcription factors. Three differentially expressed genes (S100A4, CD36 and FKBP1a) were examined by immunohistochemistry confirming the regulation on protein level. While FKBP1a was restricted to the vessel adventitia, S100A4 and CD36 were localised in the vascular tunica media.Laser-microdissection and array profiling has revealed several new genes involved in lung vascular remodelling in response to hypoxia. Immunohistochemistry confirmed regulation of three proteins and specified their localisation in vascular smooth muscle cells and fibroblasts indicating involvement of different cells types in the remodelling process. The approach allows deeper insight into hypoxic regulatory pathways specifically in the vascular compartment of this complex organ.

SUBMITTER: Kwapiszewska G

PROVIDER: S-EPMC1261535 | biostudies-literature | 2005 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Expression profiling of laser-microdissected intrapulmonary arteries in hypoxia-induced pulmonary hypertension.

Kwapiszewska Grazyna G Wilhelm Jochen J Wolff Stephanie S Laumanns Isabel I Koenig Inke R IR Ziegler Andreas A Seeger Werner W Bohle Rainer M RM Weissmann Norbert N Fink Ludger L

Respiratory research 20050919

<h4>Background</h4>Chronic hypoxia influences gene expression in the lung resulting in pulmonary hypertension and vascular remodelling. For specific investigation of the vascular compartment, laser-microdissection of intrapulmonary arteries was combined with array profiling.<h4>Methods and results</h4>Analysis was performed on mice subjected to 1, 7 and 21 days of hypoxia (FiO2 = 0.1) using nylon filters (1176 spots). Changes in the expression of 29, 38, and 42 genes were observed at day 1, 7, a ...[more]

PMID: 16171515

Similar Datasets

Project description:Objective: Pulmonary hypertension (PH) associated with hypoxia and lung disease (Group 3) is the second most common form of PH and associated with increased morbidity and mortality. This study was aimed to identify hypoxia induced metabolism associated genes (MAGs) for better understanding of hypoxic PH. Methods: Rat pulmonary arterial smooth muscle cells (PASMCs) were isolated and cultured in normoxic or hypoxic condition for 24 h. Cells were harvested for liquid chromatography-mass spectrometry analysis. Functional annotation of distinguishing metabolites was performed using Metaboanalyst. Top 10 enriched metabolite sets were selected for the identification of metabolism associated genes (MAGs) with a relevance score >8 in Genecards. Transcriptomic data from lungs of hypoxic PH in mice/rats or of PH patients were accessed from Gene Expression Omnibus (GEO) database or open-access online platform. Connectivity Map analysis was performed to identify potential compounds to reverse the metabolism associated gene profile under hypoxia stress. The construction and module analysis of the protein-protein interaction (PPI) network was performed. Hub genes were then identified and used to generate LASSO model to determine its accuracy to predict occurrence of PH. Results: A total of 36 altered metabolites and 1,259 unique MAGs were identified in rat PASMCs under hypoxia. 38 differentially expressed MAGs in mouse lungs of hypoxic PH were revealed, with enrichment in multi-pathways including regulation of glucose metabolic process, which might be reversed by drugs such as blebbistatin. 5 differentially expressed MAGs were displayed in SMCs of Sugen 5416/hypoxia induced PH rats at the single cell resolution. Furthermore, 6 hub genes (Cat, Ephx1, Gpx3, Gstm4, Gstm5, and Gsto1) out of 42 unique hypoxia induced MAGs were identified. Higher Cat, Ephx1 and lower Gsto1 were displayed in mouse lungs under hypoxia (all p < 0.05), in consistent with the alteration in lungs of PH patients. The hub gene-based LASSO model can predict the occurrence of PH (AUC = 0.90). Conclusion: Our findings revealed six hypoxia-induced metabolism associated hub genes, and shed some light on the molecular mechanism and therapeutic targets in hypoxic PH.

Project description:BACKGROUND:In the new pathologic classification of lung adenocarcinoma proposed by IASLC/ATS/ERS in 2011, lepidic type adenocarcinomas are constituted by three subtypes; adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and lepidic predominant invasive adenocarcinoma (LPIA). Although these subtypes are speculated to show sequential progression from preinvasive lesion to invasive lung cancer, changes of protein expressions during these processes have not been fully studied yet. This study aims to glimpse a proteomic view of the early lepidic type lung adenocarcinomas. METHODS:A total of nine formalin-fixed and paraffin-embedded (FFPE) lepidic type lung adenocarcinoma tissues were selected from our archives, three tissues each in AIS, MIA and LPIA. The tumor and peripheral non-tumor cells in these FFPE tissues were collected with laser microdissection (LMD). Using liquid chromatography-tandem mass spectrometry (MS/MS), protein compositions were compared with respect to the peptide separation profiles among tumors collected from three types of tissues, AIS, MIA and LPIA. Proteins identified were semi-quantified by spectral counting-based or identification-based protein-based approach, and statistical evaluation was performed by pairwise G-tests. RESULTS:A total of 840 proteins were identified. Spectral counting-based semi-quantitative comparisons of all identified proteins through AIS to LPIA have revealed that the protein expression profile of LPIA was significantly differentiated from other subtypes. 70 proteins including HPX, CTTN, CDH1, EGFR, MUC1 were found as LPIA-type marker candidates, 15 protein candidates for MIA-type marker included CRABP2, LMO7, and NPEP, and 26 protein candidates for AIS-type marker included LTA4H and SOD2. The STRING gene set enrichment resulted from the protein-protein interaction (PPI) network analysis suggested that AIS was rather associated with pathways of focal adhesion, adherens junction, tight junction, that MIA had a strong association predominantly with pathways of proteoglycans in cancer and with PI3K-Akt. In contrast, LPIA was associated broadly with numerous tumor-progression pathways including ErbB, Ras, Rap1 and HIF-1 signalings. CONCLUSIONS:The proteomic profiles obtained in this study demonstrated the technical feasibility to elucidate protein candidates differentially expressed in FFPE tissues of LPIA. Our results may provide candidates of disease-oriented proteins which may be related to mechanisms of the early-stage progression of lung adenocarcinoma.

Dataset Information

Expression profiling of laser-microdissected intrapulmonary arteries in hypoxia-induced pulmonary hypertension.

Publications

Expression profiling of laser-microdissected intrapulmonary arteries in hypoxia-induced pulmonary hypertension.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets