Peng Longfei, Cao Zhangjun, Wang Qi, Fang Lu, Yan Songbai, Xia Dian, Wang Jinyou, Bi Liangkuan
Department of Urology, Second Hospital of Anhui Medical University, Hefei, China.
Front Oncol. 2022 Oct 13;12:963483. doi: 10.3389/fonc.2022.963483. eCollection 2022.
Renal cell carcinoma (RCC), as one of the most common urological malignancies, has many histologic and molecular subtypes, among which clear cell renal cell carcinoma (ccRCC) is one of the most common causes of tumor-related deaths. However, the molecular mechanism of ccRCC remains unclear. In order to identify the candidate genes that may exist in the occurrence and development of ccRCC, microarray datasets GSE6344, GSE16441, GSE36895, GSE53757 and GSE76351 had been downloaded from Gene Expression Omnibus (GEO) database. Apart from that, the differentially expressed genes (DEGs) were screened through Bioinformatics & Evolutionary Genomics. In addition, the protein-protein interaction network (PPI) was constructed, and the module analysis was performed using STRING and Cytoscape. By virtue of DAVID online database, GO/KEGG enrichment analysis of DEGs was performed. Consequently, a total of 118 DEGs were screened, including 24 up-regulated genes and 94 down-regulated genes. The plug-in MCODE of Cytoscape was adopted to analyze the most significant modules of DEGs. What's more, the genes with degree greater than 10 in DEGs were selected as the hub genes. The overall survival (OS) and disease progression free survival (DFS) of 9 hub genes were analyzed through GEPIA2 online platform. As shown by the survival analysis, SLC34A1, SLC12A3, SLC12A1, PLG, and ENO2 were closely related to the OS of ccRCC, whereas SLC34A1 and LOX were closely related to DFS. Among 11 SLC members, 6 SLC members were highly expressed in non-cancerous tissues (SLC5A2, SLC12A1, SLC12A3, SLC34A1, SLC34A2, SLC34A3). Besides, SLC12A5 and SLC12A7 were highly expressed in ccRCC. Furthermore, SLC12A1-A7, SLC34A1 and SLC34A3 were closely related to OS, whereas SLC12A2/A4/A6/A7 and SLC34A1/A3 were closely related to DFS. In addition, 5 algorithms were used to analyze hub genes, the overlapping genes were AQP2 and KCNJ1. To sum up, hub gene can help us understand the molecular mechanism of the occurrence and development of ccRCC, thereby providing a theoretical basis for the diagnosis and targeted therapy of ccRCC.
肾细胞癌（RCC）是最常见的泌尿系统恶性肿瘤之一，有多种组织学和分子亚型，其中透明细胞肾细胞癌（ccRCC）是肿瘤相关死亡的最常见原因之一。然而，ccRCC的分子机制仍不清楚。为了鉴定可能在ccRCC发生和发展中存在的候选基因，从基因表达综合数据库（GEO）下载了微阵列数据集GSE6344、GSE16441、GSE36895、GSE53757和GSE76351。除此之外，通过生物信息学与进化基因组学筛选差异表达基因（DEG）。此外，构建了蛋白质-蛋白质相互作用网络（PPI），并使用STRING和Cytoscape进行模块分析。借助DAVID在线数据库，对DEG进行GO/KEGG富集分析。结果，共筛选出118个DEG，包括24个上调基因和94个下调基因。采用Cytoscape的插件MCODE分析DEG中最显著的模块。此外，将DEG中度数大于10的基因选为枢纽基因。通过GEPIA2在线平台分析9个枢纽基因的总生存期（OS）和无疾病进展生存期（DFS）。生存分析表明，SLC34A1、SLC12A3、SLC12A1、PLG和ENO2与ccRCC的OS密切相关，而SLC34A1和LOX与DFS密切相关。在11个溶质载体（SLC）成员中，6个SLC成员在非癌组织中高表达（SLC5A2、SLC12A1、SLC12A3、SLC34A1、SLC34A2、SLC34A3）。此外，SLC12A5和SLC12A7在ccRCC中高表达。此外，SLC12A1-A7、SLC34A1和SLC34A3与OS密切相关，而SLC12A2/A4/A6/A7和SLC34A1/A3与DFS密切相关。此外，使用5种算法分析枢纽基因，重叠基因是水通道蛋白2（AQP2）和内向整流钾通道蛋白1（KCNJ1）。综上所述，枢纽基因有助于我们了解ccRCC发生和发展的分子机制，从而为ccRCC的诊断和靶向治疗提供理论依据。
