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Identification of key genes and construction of microRNA-mRNA regulatory networks in non-small cell lung cancer

机译:非小细胞肺癌中微小荷纳霉菌调控网络的关键基因和构建的鉴定

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Non-small cell lung cancer (NSCLC) is the most common type of lung tumor. Deregulation of microRNA may be involved in the occurrence of NSCLC and we aimed to find the potential prognostic biomarkers for NSCLC. The microRNA microarray expression profiles were downloaded from GEO dataset and then generated by applying robust multi-array average (RMA). The normalized data was analyzed with a Bioconductor package linear model for microarray data and an independent dataset was used to inspect the results. Then, the differentially expressed genes were identified using the limma package. Besides, in order to investigate the function of the differentially expressed microRNA in NSCLC, the GO and KEGG functional enrichment analysis were applied, and the GSEA analysis was performed for mining the therapeutic candidates. A total of 160 differentially expressed microRNAs were identified, among which 37 microRNAs showed significant expression changes (up-regulated and down-regulated) with the same method in the validation dataset GSE74190. Multiple cancer-related pathways, such as AMPK signaling pathway, AMPK signaling pathway, non-small cell lung cancer signaling pathway, were determined by performing the functional enrichment analysis. Besides, the results of GSEA analysis showed that the CCND1 was mostly enriched in lung cancer group. In conclusion, a set of differentially expressed microRNAs in NSCLC was identified and the CCND1 gene was determined as the potential prognostic biomarkers for NSCLC, providing useful information for discovery of future therapeutic targets and candidates in the clinical management of NSCLC.
机译:非小细胞肺癌(NSCLC)是最常见的肺肿瘤类型。 MicroRNA的放松管制可能参与NSCLC的发生,我们的目标是为NSCLC找到潜在的预后生物标志物。 MicroRNA微阵列表达式配置文件从Geo DataSet下载,然后通过应用鲁棒的多阵列平均值(RMA)生成。使用用于微阵列数据的生物导体包线性模型来分析归一化数据,并使用独立数据集来检查结果。然后,使用蕾丝包来鉴定差异表达的基因。此外,为了研究NSCLC中差异表达的微小RORNA的功能,施加GO和KEGG功能性富集分析,并进行GSEA分析用于开采治疗候选者。鉴定了总共160个差异表达的微小RNA,其中37微针在验证数据集GSE74190中具有相同的方法,显示出显着的表达变化(上调和下调)。通过进行功能性富集分析,确定多种癌症相关途径,例如AMPK信号通路,AMPK信号通路,非小细胞肺癌信号通路。此外,GSEA分析结果表明,CCND1大多富含肺癌组。总之,鉴定了一组NSCLC中的差异表达的微小RNA,并将CCND1基因定位为NSCLC的潜在预后生物标志物,提供了在NSCLC临床管理中发现未来治疗目标和候选人的有用信息。

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