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A 16-gene expression signature to distinguish stage I from stage II lung squamous carcinoma

机译:区分I期与II期肺鳞癌的16基因表达特征

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摘要

The present study aimed to perform screening of a gene signature for the discrimination and prognostic prediction of stage I and II lung squamous carcinoma. A microarray meta-analysis was performed to identify differentially expressed genes (DEGs) between stage I and II lung squamous carcinoma samples in seven microarray datasets collected from the Gene Expression Omnibus database via the MetaQC and MetaDE package in R. The important DEGs were selected according to the betweenness centrality value of the protein-protein interaction (PPI) network. Support vector machine (SVM) analysis was performed to screen the feature genes for discrimination and prognosis. One independent dataset downloaded from The Cancer Genome Atlas was used to validate the reliability. Pathway enrichment analysis was also performed for the feature genes. A total of 924 DEGs were identified to construct a PPI network consisting of 392 nodes and 686 edges. The top 100 of the 392 nodes were selected as crucial genes to construct an SVM classifier, and a 16-gene signature (caveolin 1, eukaryotic translation elongation factor 1γ, casein kinase 2α1, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation η, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation θ, pleiotrophin, insulin receptor, insulin receptor substrate 1, 3-phosphoinositide-dependent protein kinase-1, specificity protein 1, COP9 signalosome subunit 6, N-myc downstream regulated gene 1, retinoid X receptor α, heat shock protein 90α A1, karyopherin subunit β1 and erythrocyte membrane protein band 4.1) with high discrimination accuracy was identified. This 16-gene signature had significant prognostic value, and patients with stage II lung squamous carcinoma exhibited shorter survival rates, compared with those with stage I disease. Seven DEGs of the 16-gene signature were significantly involved in the phosphoinositide 3-kinase-Akt signaling pathway. The 16-gene signature identified in the present study may be useful for stratifying the patients with stage I or II lung squamous carcinoma and predicting prognosis.
机译:本研究旨在对I,II期肺鳞癌的鉴别和预后预测进行基因签名筛选。进行了微阵列荟萃分析,以鉴定通过R中的MetaQC和MetaDE软件包从Gene Expression Omnibus数据库收集的七个微阵列数据集中的I和II期肺鳞癌样品之间的差异表达基因(DEG)。蛋白质-蛋白质相互作用(PPI)网络的中间性中心值。进行支持向量机(SVM)分析以筛选特征基因以进行区分和预后。从The Cancer Genome Atlas下载的一个独立数据集用于验证可靠性。还对特征基因进行了途径富集分析。共确定了924个DEG,以构建一个由392个节点和686个边组成的PPI网络。从392个结点的前100个中选择关键基因来构建SVM分类器,并获得16个基因的签名(小窝蛋白1,真核翻译延伸因子1γ,酪蛋白激酶2α1,酪氨酸3-单加氧酶/色氨酸5-单加氧酶激活η,酪氨酸3-单加氧酶/色氨酸5-单加氧酶激活θ,促营养素,胰岛素受体,胰岛素受体底物1,3-磷酸肌醇依赖性蛋白激酶-1,特异性蛋白1,COP9信号体亚基6,N-myc下游调节基因1,维甲酸鉴定出X受体α,热休克蛋白90αA1,核球蛋白亚基β1和红细胞膜蛋白带(4.1),具有较高的识别准确度。这个具有16个基因的特征具有显着的预后价值,与I期疾病相比,II期肺鳞癌患者的生存率更短。具有16个基因标记的7个DEG明显参与了磷酸肌醇3-激酶-Akt信号通路。在本研究中确定的16个基因的特征可能有助于对I或II期肺鳞癌患者进行分层并预测预后。

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