Identification of common signatures in idiopathic pulmonary fibrosis and lung cancer using gene expression modeling
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RESEARCH ARTICLE
Open Access
Identification of common signatures in idiopathic pulmonary fibrosis and lung cancer using gene expression modeling Dong Leng1†, Jiawen Yi2†, Maodong Xiang3, Hongying Zhao4 and Yuhui Zhang2*
Abstract Background: Idiopathic pulmonary fibrosis (IPF) is associated with an increased risk for lung cancer, but the underlying mechanisms driving malignant transformation remain largely unknown. This study aimed to identify differentially expressed genes (DEGs) distinguishing IPF and lung cancer from healthy individuals and common genes driving the transformation from healthy to IPF and lung cancer. Methods: The gene expression data for IPF and non-small cell lung cancer (NSCLC) were retrieved from the Gene Expression Omnibus (GEO) database. The DEG signatures were identified via unsupervised two-way clustering (TWC) analysis, supervised support vector machine analysis, dimensional reduction, and mutual exclusivity analysis. Gene enrichment and pathway analyses were performed to identify common signaling pathways. The most significant signature genes in common among IPF and lung cancer were further verified by immunohistochemistry. Results: The gene expression data from GSE24206 and GSE18842 were merged into a super array dataset comprising 86 patients with lung disorders (17 IPF and 46 NSCLC) and 51 healthy controls and measuring 23,494 unique genes. Seventy-nine signature DEGs were found among IPF and NSCLC. The peroxisome proliferatoractivated receptor (PPAR) signaling pathway was the most enriched pathway associated with lung disorders, and matrix metalloproteinase-1 (MMP-1) in this pathway was mutually exclusive with several genes in IPF and NSCLC. Subsequent immunohistochemical analysis verified enhanced MMP1 expression in NSCLC associated with IPF. Conclusions: For the first time, we defined common signature genes for IPF and NSCLC. The mutually exclusive sets of genes were potential drivers for IPF and NSCLC. Keywords: Idiopathic pulmonary fibrosis, Lung cancer, Gene expression, Data mining, Mutual exclusivity
Background Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and usually fatal interstitial lung disease that is characterized by dysfunction and damage of lung epithelial cells and aberrant pulmonary remodeling. After diagnosis, patients usually have a median survival of 3–5 * Correspondence: [email protected] † Dong Leng and Jiawen Yi contributed equally to this work. 2 Department of Respiratory and Critical Care Medicine, Beijing Chao-Yang Hospital, Capital Medical University, No. 8 Gongti South Road, Beijing 100020, China Full list of author information is available at the end of the article
years, and the main cause of death is respiratory failure [1, 2]. Although the exact mechanisms remain largely unknown, it is widely accepted that genetic and environmental factors leading to alveolar epithelial cell injury trigger the repair process and induce the formation of fibroblast foci, ultimately causing pulmonary fibrosis [3]. IPF is considered as a precancerous l
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