Liu Yun, Wu Xia, Wang Guokun, Hu Shisong, Zhang Yuandong, Zhao Shenglong
Department of Urology, the Affiliated Zhaotong Hospital of Kunming Medical University, Zhaotong, Yunnan Province, China.
Medicine (Baltimore). 2019 Jan;98(2):e13847. doi: 10.1097/MD.0000000000013847.
Bladder cancer (BC) is one of the most common malignant neoplasms in the genitourinary tract. We employed the GSE13507 data set from the Gene Expression Omnibus (GEO) database in order to identify key genes related to tumorigenesis, progression, and prognosis in BC patients.
The data set used in this study included 10 normal bladder mucosae tissue samples and 165 primary BC tissue samples. Differentially expressed genes (DEGs) in the 2 types of samples were identified by GEO2R. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the online website DAVID. The online website STRING was used to construct a protein-protein interaction network. Moreover, the plugins in MCODE and cytoHubba in Cytoscape were employed to find the hub genes and modules in these DEGs.
We identified 154 DEGs comprising 135 downregulated genes and 19 upregulated genes. The GO enrichment results were mainly related to the contractile fiber part, extracellular region part, actin cytoskeleton, and extracellular region. The KEGG pathway enrichment results mainly comprised type I diabetes mellitus, asthma, systemic lupus erythematosus, and allograft rejection. A module was identified from the protein-protein interaction network. In total, 15 hub genes were selected and 3 of them comprising CALD1, CNN1, and TAGLN were associated with both overall survival and disease-free survival.
CALD1, CNN1, and TAGLN may be potential biomarkers for diagnosis as well as therapeutic targets in BC patients.
膀胱癌（BC）是泌尿生殖道最常见的恶性肿瘤之一。我们使用了来自基因表达综合数据库（GEO）的GSE13507数据集，以识别与BC患者肿瘤发生、进展和预后相关的关键基因。
本研究使用的数据集包括10个正常膀胱黏膜组织样本和165个原发性BC组织样本。通过GEO2R识别这两种样本中的差异表达基因（DEG）。使用在线网站DAVID进行基因本体论（GO）和京都基因与基因组百科全书（KEGG）通路富集分析。使用在线网站STRING构建蛋白质-蛋白质相互作用网络。此外，采用Cytoscape中MCODE和cytoHubba的插件来寻找这些DEG中的枢纽基因和模块。
我们鉴定出154个DEG，包括135个下调基因和19个上调基因。GO富集结果主要与收缩纤维部分、细胞外区域部分、肌动蛋白细胞骨架和细胞外区域有关。KEGG通路富集结果主要包括I型糖尿病、哮喘、系统性红斑狼疮和同种异体移植排斥。从蛋白质-蛋白质相互作用网络中鉴定出一个模块。总共选择了15个枢纽基因，其中3个包括CALD1、CNN1和TAGLN与总生存期和无病生存期均相关。
CALD1、CNN1和TAGLN可能是BC患者诊断的潜在生物标志物以及治疗靶点。
