Bioinformatics and functional analyses of key genes in smoking-associated lung adenocarcinoma
Bioinformatics and functional analyses of key genes in smoking-associated lung adenocarcinoma
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吸烟相关肺腺癌关键基因的生物信息学和功能分析
DOI：
10.3892/ol.2019.10733
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发表时间：
2019-08
期刊：
影响因子：
--
通讯作者：
Ma X
中科院分区：
文献类型：
--
作者：
Zhou D;Sun Y;Jia Y;Liu D;Wang J;Chen X;Zhang Y;Ma X
吸烟是与肺癌发展相关的最重要因素之一。然而，吸烟相关肺腺癌的信号通路和驱动基因仍然未知。本研究分析了来自癌症基因组图谱数据库的433例吸烟相关肺腺癌和75例非吸烟肺腺癌样本。使用用于注释、可视化和集成发现的数据库和ggplot 2 R/Bioconductor包进行基因本体（GO）分析。使用R软件包RSQLite和org.Hs.eg.db进行京都基因和基因组百科全书（KEGG）途径分析。采用多因素考克斯回归分析筛选与患者生存相关的因素。Kaplan-Meier和受试者工作特征曲线用于分析鉴定的生物标志物作为5年总生存时间的分子预后标志物的潜在临床意义。共检测到373个差异表达基因（DEG;|对数2倍变化|≥2.0和P<0.01），其中71个下调，302个上调。这些DEG与28个显著的GO功能和11个显著的KEGG通路相关（错误发现率<0.05）。238个蛋白质与373个差异表达基因相关联，构建了蛋白质-蛋白质相互作用网络。多元回归分析显示，细胞色素P450家族17亚家族A成员1、PKHD 1样1、维甲酸异构水解酶RPE 65、神经降压素受体1、胎球蛋白B、胰岛素样生长因子结合蛋白1和葡萄糖-6-磷酸酶催化亚基7种mRNA在非吸烟和吸烟相关腺癌中具有显著性差异。Kaplan-Meier分析显示，7种mRNA高风险组患者的预后显著差于低风险组。本研究中获得的数据表明，这些基因可能作为潜在的新的吸烟相关肺腺癌的预后生物标志物。
Smoking is one of the most important factors associated with the development of lung cancer. However, the signaling pathways and driver genes in smoking-associated lung adenocarcinoma remain unknown. The present study analyzed 433 samples of smoking-associated lung adenocarcinoma and 75 samples of non-smoking lung adenocarcinoma from the Cancer Genome Atlas database. Gene Ontology (GO) analysis was performed using the Database for Annotation, Visualization and Integrated Discovery and the ggplot2 R/Bioconductor package. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed using the R packages RSQLite and org.Hs.eg.db. Multivariate Cox regression analysis was performed to screen factors associated with patient survival. Kaplan-Meier and receiver operating characteristic curves were used to analyze the potential clinical significance of the identified biomarkers as molecular prognostic markers for the five-year overall survival time. A total of 373 differentially expressed genes (DEGs; |log2-fold change|≥2.0 and P<0.01) were identified, of which 71 were downregulated and 302 were upregulated. These DEGs were associated with 28 significant GO functions and 11 significant KEGG pathways (false discovery rate <0.05). Two hundred thirty-eight proteins were associated with the 373 differentially expressed genes, and a protein-protein interaction network was constructed. Multivariate regression analysis revealed that 7 mRNAs, cytochrome P450 family 17 subfamily A member 1, PKHD1 like 1, retinoid isomerohydrolase RPE65, neurotensin receptor 1, fetuin B, insulin-like growth factor binding protein 1 and glucose-6-phosphatase catalytic subunit, significantly distinguished between non-smoking and smoking-associated adenocarcinomas. Kaplan-Meier analysis demonstrated that patients in the 7 mRNAs-high-risk group had a significantly worse prognosis than those of the low-risk group. The data obtained in the current study suggested that these genes may serve as potential novel prognostic biomarkers of smoking-associated lung adenocarcinoma.
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影响因子：
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作者：
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DOI：
--
发表时间：
2015-02
期刊：
Morbidity and Mortality Weekly Report
影响因子：
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作者：
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通讯作者：
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影响因子：
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Xiong WN