Gene expression profiles in asbestos-exposed epithelial and mesothelial lung cell lines.pdfVIP

Gene expression profiles in asbestos-exposed epithelial and mesothelial lung cell lines.pdf

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Gene expression profiles in asbestos-exposed epithelial and mesothelial lung cell lines

BioMed CentralBMC Genomics ssOpen AcceResearch article Gene expression profiles in asbestos-exposed epithelial and mesothelial lung cell lines Penny Nymark?1,2, Pamela M Lindholm?2, Mikko V Korpela3, Leo Lahti3, Salla Ruosaari1,2,3, Samuel Kaski3, Jaakko Hollmén3, Sisko Anttila1, Vuokko L Kinnula4 and Sakari Knuutila*2 Address: 1Health and Work Ability, Biological Mechanisms and Prevention of Work-related Diseases, Finnish Institute of Occupational Health, Helsinki, Finland, 2Department of Pathology, Haartman Institute and HUSLAB, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland, 3Helsinki Institute for Information Technology, Laboratory of Computer and Information Science, Helsinki University of Technology, Espoo, Finland and 4Department of Medicine, Pulmonary Division, University of Helsinki and Helsinki University Hospital, Helsinki, Finland Email: Penny Nymark - penny.nymark@helsinki.fi; Pamela M Lindholm - pamela.lindholm@helsinki.fi; Mikko V Korpela - mvkorpel@cc.hut.fi; Leo Lahti - leo.lahti@hut.fi; Salla Ruosaari - salla.ruosaari@helsinki.fi; Samuel Kaski - samuel.kaski@hut.fi; Jaakko Hollmén - jaakko.hollmen@hut.fi; Sisko Anttila - sisko.anttila@ttl.fi; Vuokko L Kinnula - vuokko.kinnula@helsinki.fi; Sakari Knuutila* - sakari.knuutila@helsinki.fi * Corresponding author ?Equal contributors Abstract Background: Asbestos has been shown to cause chromosomal damage and DNA aberrations. Exposure to asbestos causes many lung diseases e.g. asbestosis, malignant mesothelioma, and lung cancer, but the disease-related processes are still largely unknown. We exposed the human cell lines A549, Beas-2B and Met5A to crocidolite asbestos and determined time-dependent gene expression profiles by using Affymetrix arrays. The hybridization data was analyzed by using an algorithm specifically designed for clustering of short time series expression data. A canonical correlation analysis was applied to identify correlations between t

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