Li Feng, Guo Peiyuan, Dong Keqin, Guo Peng, Wang Haoyuan, Lv Xianqiang
Department of Urology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, P.R. China.
School of Basic Medical Sciences, Hebei Medical University, Shijiazhuang, P.R. China.
J Comput Biol. 2019 Nov;26(11):1278-1295. doi: 10.1089/cmb.2019.0145. Epub 2019 Jun 24.
Renal cell carcinoma (RCC) is the most common form of kidney cancer, caused by renal epithelial cells. RCC remains to be a challenging public health problem worldwide. Metastases that are resistant to radiotherapy and chemotherapy are the major cause of death from cancer. However, the underlying molecular mechanism regulating the metastasis of RCC is poorly known. Publicly available databases of RCC were obtained from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using GEO2R analysis, whereas the Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by Gene Set Enrichment Analysis (GSEA) and Metascape. Protein-protein interaction (PPI) network of DEGs was analyzed by STRING online database, and Cytoscape software was used for visualizing PPI network. Survival analysis of hub genes was conducted using GEPIA online database. The expression levels of hub genes were investigated from The Human Protein Atlas online database and GEPIA online database. Finally, the comparative toxicogenomics database (CTD; http://ctdbase.org) was used to identify hub genes associated with tumor or metastasis. We identified 229 DEGs comprising 135 downregulated genes and 94 upregulated genes. Functional analysis revealed that these DEGs were associates with cell recognition, regulation of immune, negative regulation of adaptive immune response, and other functions. And these DEGs mainly related to P53 signaling pathway, cytokine-cytokine receptor interaction, Natural killer cell mediated cytotoxicity, and other pathways are involved. Ten genes were identified as hub genes through module analyses in the PPI network. Finally, survival analysis of 10 hub genes was conducted, which showed that the MMP2 (matrix metallo peptidase 2), DCN, COL4A1, CASR (calcium sensing receptor), GPR4 (G protein-coupled receptor 4), UTS2 (urotensin 2), and LDLR (low density lipoprotein receptor) genes were significant for survival. In this study, the DEGs between RCC and metastatic RCC were analyzed, which assist us in systematically understanding the pathogeny underlying metastasis of RCC. The MMP2, DCN, COL4A1, CASR, GPR4, UTS2, and LDLR genes might be used as potential targets to improve diagnosis and immunotherapy biomarkers for RCC.
肾细胞癌（RCC）是最常见的肾癌形式，由肾上皮细胞引起。RCC在全球范围内仍然是一个具有挑战性的公共卫生问题。对放疗和化疗耐药的转移是癌症死亡的主要原因。然而，调节RCC转移的潜在分子机制尚不清楚。从基因表达综合数据库（GEO）获取公开可用的RCC数据库。使用GEO2R分析鉴定差异表达基因（DEG），而基因本体（GO）分析和京都基因与基因组百科全书（KEGG）分析则通过基因集富集分析（GSEA）和Metascape进行。通过STRING在线数据库分析DEG的蛋白质-蛋白质相互作用（PPI）网络，并使用Cytoscape软件可视化PPI网络。使用GEPIA在线数据库对枢纽基因进行生存分析。从人类蛋白质图谱在线数据库和GEPIA在线数据库研究枢纽基因的表达水平。最后，使用比较毒理基因组学数据库（CTD；http://ctdbase.org）鉴定与肿瘤或转移相关的枢纽基因。我们鉴定出229个DEG，包括135个下调基因和94个上调基因。功能分析表明，这些DEG与细胞识别、免疫调节、适应性免疫反应的负调节等功能相关。并且这些DEG主要涉及P53信号通路、细胞因子-细胞因子受体相互作用、自然杀伤细胞介导的细胞毒性等途径。通过PPI网络中的模块分析鉴定出10个基因作为枢纽基因。最后，对10个枢纽基因进行生存分析，结果表明基质金属肽酶2（MMP2）、核心蛋白聚糖（DCN）、IV型胶原α1链（COL4A1）、钙敏感受体（CASR）、G蛋白偶联受体4（GPR4）、尾加压素2（UTS2）和低密度脂蛋白受体（LDLR）基因对生存具有显著意义。在本研究中，分析了RCC与转移性RCC之间的DEG，这有助于我们系统地了解RCC转移的发病机制。MMP2、DCN、COL4A1、CASR、GPR4、UTS2和LDLR基因可能用作改善RCC诊断和免疫治疗生物标志物的潜在靶点。
