Li Can-Xuan, Chen Jie, Xu Zheng-Guang, Yiu Wing-Keung, Lin Yen-Ting
Department of Urology, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Transl Cancer Res. 2020 Dec;9(12):7415-7431. doi: 10.21037/tcr-20-2393.
RNA binding proteins (RBPs) have previously been demonstrated to be involved in the initiation and development of human cancers. However, its role in clear cell renal cell carcinoma (ccRCC) is not yet clear. The study was intended to explore the diagnostic and prognostic value of RBPs in ccRCC via bioinformatics methods of public datasets.
Data download from the Cancer Genome Atlas (TCGA) database was used to identify differentially expressed RBPs between normal renal samples and cancerous samples. Then, we performed the gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of differentially expressed genes (DEGs) using the ClusterProfiler package. Next, the protein-protein interaction (PPI) network was built by the online tool STRING database and Cytoscape software. The significant module and hub genes were screened by MCODE and Cytohubba plugin, respectively. Lastly, we performed a systematical analysis to investigate the diagnostic and prognostic value of candidate RBPs.
A total of 133 DEGs, including 39 upregulated RBPs and 94 downregulated RBPs, were screened between ccRCC samples and noncancerous samples. From these data, eight candidate RBPs (RPS2, GAPDH, RPS20, EIF4A1, RPL18, RPL13, RPL18A, and RPS19) were identified.
In summary, we screened differentially expressed RBPs of ccRCC, which were enriched mainly in various biological processes and signaling pathways. Furthermore, we identified eight candidate RBPs, which could serve as potential biomarkers of ccRCC.
RNA结合蛋白(RBPs)先前已被证明参与人类癌症的发生和发展。然而,其在透明细胞肾细胞癌(ccRCC)中的作用尚不清楚。本研究旨在通过公共数据集的生物信息学方法探索RBPs在ccRCC中的诊断和预后价值。
使用从癌症基因组图谱(TCGA)数据库下载的数据来鉴定正常肾样本和癌样本之间差异表达的RBPs。然后,我们使用ClusterProfiler软件包对差异表达基因(DEGs)进行基因本体(GO)注释和京都基因与基因组百科全书(KEGG)通路富集分析。接下来,通过在线工具STRING数据库和Cytoscape软件构建蛋白质-蛋白质相互作用(PPI)网络。分别通过MCODE和Cytohubba插件筛选显著模块和枢纽基因。最后,我们进行了系统分析以研究候选RBPs的诊断和预后价值。
在ccRCC样本和非癌样本之间共筛选出133个DEGs,包括39个上调的RBPs和94个下调的RBPs。从这些数据中,鉴定出8个候选RBPs(RPS2、GAPDH、RPS20、EIF4A1、RPL18、RPL13、RPL18A和RPS19)。
总之,我们筛选了ccRCC中差异表达的RBPs,它们主要富集于各种生物学过程和信号通路。此外,我们鉴定出8个候选RBPs,它们可作为ccRCC的潜在生物标志物。