Xu Axiang, Wang Chunyang, Sun Shengkun
Department of Urology, PLA General Hospital, Beijing 100853, P.R. China.
Mol Med Rep. 2014 Dec;10(6):3087-91. doi: 10.3892/mmr.2014.2667. Epub 2014 Oct 15.
The aim of the present study was to screen candidate genes that are closely associated with bladder cancer and to select the most distinct candidate target genes in order to provide theoretical evidence and direction for improved treatment of bladder cancer. The gene microarray dataset GSE45184 was downloaded from the Gene Expression Omnibus database. There were a total of six expression prolife microarrays from three pairs of freshly frozen bladder cancer tissues and corresponding normal adjacent tissues. Differentially expressed genes (DEGs) were identified using the limma package in R software and then subjected to further biological information analysis, including hierarchical clustering analysis and gene ontology enrichment analysis. Co‑expression networks and functional interaction networks were established using the up‑ and downregulated genes. Pathway enrichment analysis was then performed for the genes in the functional interaction networks. A total of 522 DEGs were identified, including 223 upregulated and 299 downregulated genes. Functional enrichment analysis of the target genes indicated that downregulated genes were associated with the regulation of biological processes, while the upregulated genes participated in the processes involved in the cell cycle. The functional network of the upregulated genes comprised 1,518 connections and 92 gene nodes that were associated with 10 closely‑related functions, while the network of the downregulated genes consisted of 129 connections and 24 gene nodes involving 11 significantly related functions. Pathway enrichment analysis revealed that the downregulated genes were mainly involved in the mitogen‑activated protein kinase signaling pathway, while the upregulated genes were closely associated with the cell cycle. These DEGs and the relevant cell cycle pathways have the potential to be used as targets for the treatment of bladder cancer.
本研究的目的是筛选与膀胱癌密切相关的候选基因，并选择最具特色的候选靶基因，为改善膀胱癌治疗提供理论依据和方向。基因芯片数据集GSE45184从基因表达综合数据库下载。共有来自三对新鲜冷冻膀胱癌组织及相应正常相邻组织的六个表达谱芯片。使用R软件中的limma包鉴定差异表达基因（DEG），然后进行进一步的生物信息分析，包括层次聚类分析和基因本体富集分析。利用上调和下调基因建立共表达网络和功能相互作用网络。然后对功能相互作用网络中的基因进行通路富集分析。共鉴定出522个DEG，包括223个上调基因和299个下调基因。对靶基因的功能富集分析表明，下调基因与生物过程的调控相关，而上调基因参与细胞周期相关过程。上调基因的功能网络包含1518个连接和92个基因节点，与10个密切相关的功能相关，而下调基因的网络由129个连接和24个基因节点组成，涉及11个显著相关的功能。通路富集分析显示，下调基因主要参与丝裂原活化蛋白激酶信号通路，而上调基因与细胞周期密切相关。这些DEG和相关的细胞周期通路有潜力用作膀胱癌治疗的靶点。
