Cao Honghao, Tong Hang, Zhu Junlong, Xie Chenchen, Qin Zijia, Li Tinghao, Liu Xudong, He Weiyang
Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Department of Urology, Rongchang Traditional Chinese Medicine Hospital, Chongqing, China.
Front Genet. 2021 Apr 1;12:638980. doi: 10.3389/fgene.2021.638980. eCollection 2021.
The prognosis of renal cell carcinoma (RCC) varies greatly among different risk groups, and the traditional indicators have limited effect in the identification of risk grade in patients with RCC. The purpose of our study is to explore a glycolysis-based long non-coding RNAs (lncRNAs) signature and verify its potential clinical significance in prognostic prediction of RCC patients.
In this study, RNA data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate cox regression displayed six significantly related lncRNAs (AC124854.1, AC078778.1, EMX2OS, DLGAP1-AS2, AC084876.1, and AC026401.3) which were utilized in construction of risk score by a formula. The accuracy of risk score was verified by a series of statistical methods such as receiver operating characteristic (ROC) curves, nomogram and Kaplan-Meier curves. Its potential clinical significance was excavated by gene enrichment analysis.
Kaplan-Meier curves and ROC curves showed reliability of the risk score to predict the prognosis of RCC patients. Stratification analysis indicated that the risk score was independent predictor compare to other traditional clinical parameters. The clinical nomogram showed highly rigorous with index of 0.73 and precisely predicted 1-, 3-, and 5-year survival time of RCC patients. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene set enrichment analysis (GSEA) depicted the top ten correlated pathways in both high-risk group and low-risk group. There are 6 lncRNAs and 25 related mRNAs including 36 lncRNA-mRNA links in lncRNA-mRNA co-expression network.
This research demonstrated that glycolysis-based lncRNAs possessed an important value in survival prediction of RCC patients, which would be a potential target for future treatment.
肾细胞癌（RCC）在不同风险组中的预后差异很大，传统指标在识别RCC患者的风险等级方面效果有限。本研究的目的是探索一种基于糖酵解的长链非编码RNA（lncRNAs）特征，并验证其在RCC患者预后预测中的潜在临床意义。
在本研究中，从癌症基因组图谱（TCGA）数据库下载了RNA数据和临床信息。单变量和多变量cox回归显示了六个显著相关的lncRNAs（AC124854.1、AC078778.1、EMX2OS、DLGAP1-AS2、AC084876.1和AC026401.3），这些lncRNAs通过一个公式用于构建风险评分。通过一系列统计方法，如受试者操作特征（ROC）曲线、列线图和Kaplan-Meier曲线，验证了风险评分的准确性。通过基因富集分析挖掘其潜在的临床意义。
Kaplan-Meier曲线和ROC曲线显示了风险评分预测RCC患者预后的可靠性。分层分析表明，与其他传统临床参数相比，风险评分是独立的预测因子。临床列线图显示出高度严谨性，指数为0.73，并精确预测了RCC患者的1年、3年和5年生存时间。京都基因与基因组百科全书（KEGG）和基因集富集分析（GSEA）描绘了高风险组和低风险组中排名前十的相关通路。lncRNA-mRNA共表达网络中有6个lncRNAs和25个相关mRNA，包括36个lncRNA-mRNA链接。
本研究表明，基于糖酵解的lncRNAs在RCC患者的生存预测中具有重要价值，这将是未来治疗的一个潜在靶点。
