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Transforming growth factor-ß (TGF-ß) signaling is implicated in the pathogenesis of fibrosis in scleroderma or systemic sclerosis (SSc), but the precise mechanisms are poorly understood. The immediate-early gene Egr-1 is an inducible transcription factor with key roles in mediating fibrotic TGF-ß responses. To elucidate Egr-1 function in SSc-associated fibrosis, we examined change in gene expression induced by Egr-1 in human fibroblasts at the genome-wide level. Using microarray expression analysis, we derived a fibroblast "Egr-1-responsive gene signature" comprising over 600 genes involved in cell proliferation, TGF-ß signaling, wound healing, extracellular matrix synthesis and vascular development. The experimentally derived "Egr-1-responsive gene signature" was then evaluated in an expression microarray dataset comprising skin biopsies from 27 patients with localized and systemic forms of scleroderma and six healthy controls. We found that the "Egr-1 responsive gene signature" was substantially enriched in the "diffuse-proliferation" subset comprising exclusively of patients with diffuse cutaneous SSc (dcSSc) of skin biopsies. A number of Egr-1-regulated genes was also associated with the "inflammatory" intrinsic subset. Only a minority of Egr-1-regulated genes was concordantly regulated by TGF-ß. These results indicate that Egr-1 induces a distinct profibrotic/wound healing gene expression program in fibroblasts that is associated with skin biopsies from SSc patients with diffuse cutaneous disease. These observations suggest that targeting Egr-1 expression or activity might be a novel therapeutic strategy to control fibrosis in specific SSc subsets.
Pubmed ID: 21931594
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Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.
View all literature mentionsA web-based software application that enables users to analyze, integrate, and understand data derived from gene expression, microRNA, and SNP microarrays, metabolomics, proteomics, and RNA-Seq experiments, and small-scale experiments that generate gene and chemical lists. Users can search for targeted information on genes, proteins, chemicals, and drugs, and build interactive models of experimental systems. IPA allows exploration of molecular, chemical, gene, protein and miRNA interactions, creation of custom molecular pathways, and the ability to view and modify metabolic, signaling, and toxicological canonical pathways. In addition to the networks and pathways that can be created, IPA can provide multiple layering of additional information, such as drugs, disease genes, expression data, cellular functions and processes, or a researchers own genes or chemicals of interest.
View all literature mentionsSoftware package for the analysis of gene expression microarray data, especially the use of linear models for analyzing designed experiments and the assessment of differential expression.
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