A Glycolysis-Based Long Non-coding RNA Signature Accurately Predicts Prognosis in Renal Carcinoma Patients - Cao, Honghao; Tong, Hang; Zhu, Junlong; Xie, Chenchen; Qin, Zijia; Li, Tinghao; Liu, Xudong; He, Weiyang (Frontiers in Genetics, 2021)
Abstract Background: 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 noncoding RNAs (lncRNAs) signature and verify its potential clinical significance in predicting the prognosis of patients with RCC. Methods: In this study, RNA data and clinical information were downloaded from the The Cancer Genome Atlas (TCGA) database. Univariate and multivariate cox regression displayed 6 significantly related lncRNAs (AC124854.1, AC078778.1, EMX2OS, DLGAP1-AS2, AC084876.1 and AC026401.3) which were used to construct risk score by a formula. The accuracy of risk score was verified by a series of statistical methods such as Kaplan-Meier curves, nomogram and time-dependent receiver operating characteristic (ROC) curves. Its potential clinical significance was excavated by gene enrichment analysis. Results: 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 accurately predicted 1-, 3-, and 5-year survival time of RCC patients. Gene set enrichment analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) depicted the top ten correlated pathways in both high- and low- risk groups. The lncRNA-mRNA co-expression network contained 36 lncRNA-mRNA links among 6 lncRNAs and 25 related mRNAs. Conclusions: 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. Keywords: glycolysis; lncRNAs; renal cell carcinoma