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http://dx.doi.org/10.7314/APJCP.2015.16.6.2561

Analysis of Molecular Pathways in Pancreatic Ductal Adenocarcinomas with a Bioinformatics Approach  

Wang, Yan (Department of Gastroenterology, Shengjing Hospital of China Medical University)
Li, Yan (Department of Gastroenterology, Shengjing Hospital of China Medical University)
Publication Information
Asian Pacific Journal of Cancer Prevention / v.16, no.6, 2015 , pp. 2561-2567 More about this Journal
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer death worldwide. Our study aimed to reveal molecular mechanisms. Microarray data of GSE15471 (including 39 matching pairs of pancreatic tumor tissues and patient-matched normal tissues) was downloaded from Gene Expression Omnibus (GEO) database. We identified differentially expressed genes (DEGs) in PDAC tissues compared with normal tissues by limma package in R language. Then GO and KEGG pathway enrichment analyses were conducted with online DAVID. In addition, principal component analysis was performed and a protein-protein interaction network was constructed to study relationships between the DEGs through database STRING. A total of 532 DEGs were identified in the 38 PDAC tissues compared with 33 normal tissues. The results of principal component analysis of the top 20 DEGs could differentiate the PDAC tissues from normal tissues directly. In the PPI network, 8 of the 20 DEGs were all key genes of the collagen family. Additionally, FN1 (fibronectin 1) was also a hub node in the network. The genes of the collagen family as well as FN1 were significantly enriched in complement and coagulation cascades, ECM-receptor interaction and focal adhesion pathways. Our results suggest that genes of collagen family and FN1 may play an important role in PDAC progression. Meanwhile, these DEGs and enriched pathways, such as complement and coagulation cascades, ECM-receptor interaction and focal adhesion may be important molecular mechanisms involved in the development and progression of PDAC.
Keywords
Pancreatic ductal adenocarcinoma; functional enrichment analysis; principal component analysis;
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