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基于转录水平芯片数据构建胰腺癌双因素调控网络。

Construction of pancreatic cancer double-factor regulatory network based on chip data on the transcriptional level.

作者信息

Zhao Li-Li, Zhang Tong, Liu Bing-Rong, Liu Tie-Fu, Tao Na, Zhuang Li-Wei

机构信息

Department of Gastroenterology, The Fourth Affiliated Hospital of Harbin Medical University, No. 37 Yiyuan Street, Nangang District, Harbin, 150001, Heilongjiang, China.

出版信息

Mol Biol Rep. 2014 May;41(5):2875-83. doi: 10.1007/s11033-014-3143-4. Epub 2014 Jan 28.

Abstract

Transcription factor (TF) and microRNA (miRNA) have been discovered playing crucial roles in cancer development. However, the effect of TFs and miRNAs in pancreatic cancer pathogenesis remains vague. We attempted to reveal the possible mechanism of pancreatic cancer based on transcription level. Using GSE16515 datasets downloaded from gene expression omnibus database, we first identified the differentially expressed genes (DEGs) in pancreatic cancer by the limma package in R. Then the DEGs were mapped into DAVID to conduct the kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis. TFs and miRNAs that DEGs significantly enriched were identified by Fisher's test, and then the pancreatic cancer double-factor regulatory network was constructed. In our study, total 1117 DEGs were identified and they significantly enriched in 4 KEGG pathways. A double-factor regulatory network was established, including 29 DEGs, 24 TFs, 25 miRNAs. In the network, LAMC2, BRIP1 and miR155 were identified which may be involved in pancreatic cancer development. In conclusion, the double-factor regulatory network was found to play an important role in pancreatic cancer progression and our results shed new light on the molecular mechanism of pancreatic cancer.

摘要

转录因子(TF)和微小RNA(miRNA)已被发现在癌症发展中发挥关键作用。然而,TF和miRNA在胰腺癌发病机制中的作用仍不明确。我们试图从转录水平揭示胰腺癌可能的发病机制。利用从基因表达综合数据库下载的GSE16515数据集,我们首先通过R语言中的limma软件包鉴定出胰腺癌中差异表达基因(DEG)。然后将这些DEG映射到DAVID中进行京都基因与基因组百科全书(KEGG)通路富集分析。通过Fisher检验鉴定出DEG显著富集的TF和miRNA,进而构建胰腺癌双因子调控网络。在我们的研究中,共鉴定出1117个DEG,它们显著富集于4条KEGG通路。建立了一个双因子调控网络,包括29个DEG、24个TF和25个miRNA。在该网络中,鉴定出可能参与胰腺癌发展的LAMC2、BRIP1和miR155。总之,发现双因子调控网络在胰腺癌进展中起重要作用,我们的研究结果为胰腺癌的分子机制提供了新的线索。

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