Department of Urology, Qilu Hospital, Shandong University, Jinan, Shandong, China (mainland).
Med Sci Monit. 2018 May 9;24:3024-3033. doi: 10.12659/MSM.909514.
BACKGROUND Bladder cancer (BC) is the most common urological malignant tumor. In BC, aberrant DNA methylation is believed to be associated with carcinogenesis. Therefore, the identification of key genes and pathways could help determine the potential molecular mechanisms of BC development. MATERIAL AND METHODS Microarray data on gene expression and gene methylation were downloaded from the Gene Expression Omnibus (GEO) database. Abnormal methylated/expressed genes were analyzed by GEO2R and statistical software R. Gene Ontology term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the DAVID database and KOBAS 3.0. STRING and Cytoscape software were used to construct protein-protein interaction (PPI) networks and analyze modules of the PPI network. RESULTS A total of 71 hypomethylated/upregulated genes were significantly enriched in cell-cell adhesion and blood vessel development. KEGG pathway analysis highlighted p53 signaling and metabolic pathways. Five core genes in the PPI network were determined: CDH1, DDOST, CASP8, DHX15, and PTPRF. Additionally, 89 hypermethylated/downregulated genes were found. These genes were enriched mostly in cell adhesion and signal transduction. KEGG pathway analysis revealed enrichment in focal adhesion. The top 5 core genes in the PPI network were GNG4, ADCY9, NPY, ADRA2B, and PENK. We found most of the core genes were also significantly altered in the Cancer Genome Atlas database. CONCLUSIONS Abnormal methylated/expressed genes and key signaling pathways involved in BC were identified through integrated bioinformatics analysis. In the future, these genes may serve as biomarkers for diagnosis and therapeutic targets in BC.
膀胱癌（BC）是最常见的泌尿系统恶性肿瘤。在 BC 中，异常的 DNA 甲基化被认为与致癌作用有关。因此，确定关键基因和通路可以帮助确定 BC 发展的潜在分子机制。
从基因表达综合数据库（GEO）下载基因表达和基因甲基化的微阵列数据。使用 GEO2R 和统计软件 R 分析异常甲基化/表达的基因。使用 DAVID 数据库和 KOBAS 3.0 进行基因本体论术语富集和京都基因与基因组百科全书（KEGG）通路分析。STRING 和 Cytoscape 软件用于构建蛋白质-蛋白质相互作用（PPI）网络并分析 PPI 网络的模块。
共有 71 个低甲基化/上调基因在细胞-细胞黏附和血管发育中显著富集。KEGG 通路分析强调了 p53 信号和代谢途径。PPI 网络中的 5 个核心基因是 CDH1、DDOST、CASP8、DHX15 和 PTPRF。此外，还发现了 89 个高甲基化/下调基因。这些基因主要富集在细胞黏附和信号转导中。KEGG 通路分析显示焦点黏附的富集。PPI 网络中的 5 个核心基因是 GNG4、ADCY9、NPY、ADRA2B 和 PENK。我们发现大多数核心基因在癌症基因组图谱数据库中也发生了显著改变。
通过综合生物信息学分析，确定了参与 BC 的异常甲基化/表达基因和关键信号通路。未来，这些基因可能成为 BC 诊断和治疗靶点的生物标志物。
