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通过生物信息学分析鉴定胰腺导管腺癌中的潜在靶基因

Identification of potential target genes in pancreatic ductal adenocarcinoma by bioinformatics analysis.

作者信息

Tang Yuchen, Zhang Zixiang, Tang Yaocheng, Chen Xinyu, Zhou Jian

机构信息

Department of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, P.R. China.

Pancreatic Disease Research Center, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, P.R. China.

出版信息

Oncol Lett. 2018 Aug;16(2):2453-2461. doi: 10.3892/ol.2018.8912. Epub 2018 Jun 6.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the most complicated and fatally pathogenic human malignancies. Therefore, there is an urgent need to improve our understanding of the underlying molecular mechanism that drives the initiation, progression, and metastasis of PDAC. The aim of the present study was to identify the key genes and signaling pathways associated with PDAC using bioinformatics analysis. Four transcriptome microarray datasets (GSE15471, GSE55643, GSE62165 and GSE91035) were acquired from Gene Expression Omnibus datasets, which included 226 PDAC samples and 65 normal pancreatic tissue samples. We screened differentially expressed genes (DEGs) with GEO2R and investigated their biological function by Gene Ontology (GO) and Kyoto Encyclopedia of Genes (KEGG) analysis. The overall survival data was obtained from UALCAN, which calculated the data shared with The Cancer Genome Atlas. In addition, a protein-protein interaction (PPI) network of the DEGs was constructed by STRING and Cytoscape software. The four sets of DEGs exhibited an intersection consisting of 205 genes (142 up-regulated and 63 down-regulated), which may be associated with PDAC. GO analysis showed that the 205 DEGs were significantly enriched in the plasma membrane, cell adhesion molecule activity and the Energy pathways, and glycine, serine, threonine metabolism were the most enriched pathways according to KEGG pathway analysis. Kaplan-Meier survival analysis revealed that 22 of 205 common genes were significantly associated with the overall survival of pancreatic cancer patients. In the PPI network and sub-network, DKK1 and HMGA2 were considered as hub genes with high connectivity degrees. DKK1 and HMGA2 are strongly associated with WNT3A and TP53 separately, which indicates that they may play an important role in the Wnt and P53 signaling pathways. Using integrated bioinformatics analysis, we identified DKK1 and HMGA2 as candidate genes in PDAC, which may improve our understanding of the mechanisms of the pathogenesis and integration; the two genes may be therapeutic targets and prognostic markers for PDAC.

摘要

胰腺导管腺癌(PDAC)是最复杂且具有致命致病性的人类恶性肿瘤之一。因此,迫切需要加深我们对驱动PDAC发生、发展和转移的潜在分子机制的理解。本研究的目的是通过生物信息学分析确定与PDAC相关的关键基因和信号通路。从基因表达综合数据库(Gene Expression Omnibus datasets)中获取了四个转录组微阵列数据集(GSE15471、GSE55643、GSE62165和GSE91035),其中包括226个PDAC样本和65个正常胰腺组织样本。我们使用GEO2R筛选差异表达基因(DEGs),并通过基因本体论(GO)和京都基因与基因组百科全书(KEGG)分析研究它们的生物学功能。总生存数据来自UALCAN,该数据库计算了与癌症基因组图谱共享的数据。此外,通过STRING和Cytoscape软件构建了DEGs的蛋白质-蛋白质相互作用(PPI)网络。这四组DEGs呈现出一个由205个基因组成的交集(142个上调和63个下调),这些基因可能与PDAC相关。GO分析表明,这205个DEGs在质膜、细胞粘附分子活性和能量途径中显著富集,根据KEGG通路分析,甘氨酸、丝氨酸、苏氨酸代谢是最富集的途径。Kaplan-Meier生存分析显示,205个常见基因中的22个与胰腺癌患者的总生存显著相关。在PPI网络和子网中,DKK1和HMGA2被视为具有高连接度的枢纽基因。DKK1和HMGA2分别与WNT3A和TP53密切相关,这表明它们可能在Wnt和P53信号通路中发挥重要作用。通过综合生物信息学分析,我们确定DKK1和HMGA2为PDAC中的候选基因,这可能增进我们对发病机制和整合机制的理解;这两个基因可能是PDAC的治疗靶点和预后标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bb/6036577/eb85efe7175b/ol-16-02-2453-g00.jpg

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