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采用生物信息学方法分析胰腺导管腺癌中的分子通路。

Analysis of molecular pathways in pancreatic ductal adenocarcinomas with a bioinformatics approach.

作者信息

Wang Yan, Li Yan

机构信息

Department of Gastroenterology, Shengjing Hospital of China Medical University, Shenyang, China E-mail :

出版信息

Asian Pac J Cancer Prev. 2015;16(6):2561-7. doi: 10.7314/apjcp.2015.16.6.2561.

DOI:10.7314/apjcp.2015.16.6.2561
PMID:25824797
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.

摘要

胰腺导管腺癌(PDAC)是全球癌症死亡的主要原因之一。我们的研究旨在揭示其分子机制。从基因表达综合数据库(GEO)下载了GSE15471的微阵列数据(包括39对匹配的胰腺肿瘤组织和患者匹配的正常组织)。我们使用R语言中的limma软件包鉴定了与正常组织相比,PDAC组织中差异表达的基因(DEG)。然后通过在线DAVID进行基因本体(GO)和京都基因与基因组百科全书(KEGG)通路富集分析。此外,进行了主成分分析,并通过STRING数据库构建了蛋白质-蛋白质相互作用网络,以研究DEG之间的关系。与33个正常组织相比,在38个PDAC组织中总共鉴定出532个DEG。前20个DEG的主成分分析结果可以直接将PDAC组织与正常组织区分开来。在蛋白质-蛋白质相互作用网络中,20个DEG中的8个都是胶原蛋白家族的关键基因。此外,纤连蛋白1(FN1)也是该网络中的一个枢纽节点。胶原蛋白家族的基因以及FN1在补体和凝血级联、细胞外基质-受体相互作用和粘着斑途径中显著富集。我们的结果表明,胶原蛋白家族的基因和FN1可能在PDAC进展中起重要作用。同时,这些DEG和富集的途径,如补体和凝血级联、细胞外基质-受体相互作用和粘着斑,可能是参与PDAC发生和发展的重要分子机制。

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