Liu Si, Zhou Honglan, Wang Gang, Lian Xin
Department of Urology, The First Hospital of Jilin University, Changchun, China.
Front Cell Dev Biol. 2021 Sep 28;9:709490. doi: 10.3389/fcell.2021.709490. eCollection 2021.
This study focuses on investigating the metabolism-related gene profile and prognosis of clear cell renal cell carcinoma (ccRCC) patients. The research data from the Gene Expression Omnibus database, including GSE40435, GSE53757, and GSE53000, were used to analyze the consistently differentially expressed RNAs (cDERs) by the MetaDE limma package. Gene expression profiling associated with metabolism was downloaded from the GSEA database. The cancer genome atlas (TCGA) dataset of ccRCC (the training set) and RNA sequencing data of E-MTAB-3267 from EBI ArrayExpress database (the validation set) were obtained to construct a prognostic model. A series of bioinformatics analysis, including functional enrichment analysis, Cox regression analysis, and constructing a prognostic score (PS) model, was performed. Further experiments including cell proliferation assay and flow cytometry were performed to validate our results. We constructed a metabolism-related prognostic model based on 27 DElncRNAs and 126 DEGs. Gene Set Enrichment Analysis revealed that 19 GO terms and 9 KEGG signaling pathways were significantly associated with lipid metabolic pathways. Furthermore, we generated a nomogram illustrating the association between the identified DERs and the tumor recurrence risk in ccRCC. The results from experimental validation showed that lncRNA SNHG20 was significantly upregulated in tumor tissues compared with adjacent tissues. Knockdown of SNHG20 suppressed the proliferation and induced cell cycle G0/G1 arrest, and apoptosis in ccRCC cells. Our study might contribute to a better understanding of metabolic pathways and to the further development of novel therapeutic approaches for ccRCC.
本研究聚焦于调查透明细胞肾细胞癌（ccRCC）患者的代谢相关基因谱及预后。来自基因表达综合数据库（Gene Expression Omnibus database）的研究数据，包括GSE40435、GSE53757和GSE53000，被用于通过MetaDE limma软件包分析一致性差异表达RNA（cDERs）。从基因集富集分析（GSEA）数据库下载与代谢相关的基因表达谱。获取ccRCC的癌症基因组图谱（TCGA）数据集（训练集）以及来自欧洲生物信息研究所阵列表达数据库（EBI ArrayExpress database）的E-MTAB-3267的RNA测序数据（验证集），以构建预后模型。进行了一系列生物信息学分析，包括功能富集分析、Cox回归分析以及构建预后评分（PS）模型。进一步开展了包括细胞增殖试验和流式细胞术在内的实验以验证我们的结果。我们基于27个差异表达长链非编码RNA（DElncRNAs）和126个差异表达基因（DEGs）构建了一个代谢相关预后模型。基因集富集分析表明，19个基因本体（GO）术语和9条京都基因与基因组百科全书（KEGG）信号通路与脂质代谢途径显著相关。此外，我们生成了一个列线图，说明了所鉴定的差异表达RNA（DERs）与ccRCC肿瘤复发风险之间的关联。实验验证结果显示lncRNA SNHG20在肿瘤组织中相比于相邻组织显著上调。敲低SNHG20可抑制ccRCC细胞的增殖并诱导细胞周期G0/G1期阻滞以及细胞凋亡。我们的研究可能有助于更好地理解代谢途径，并推动ccRCC新型治疗方法的进一步发展。
