Tu Zewei, Shu Lei, Li Jingying, Wu Lei, Tao Chuming, Ye Minhua, Zhu Xingen, Huang Kai
Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
East China Institute of Digital Medical Engineering, Shangrao, China.
Front Cell Dev Biol. 2021 Jan 28;8:588368. doi: 10.3389/fcell.2020.588368. eCollection 2020.
RNA binding proteins (RBPs) have been reported to be involved in cancer malignancy but related functions in glioma have been less studied. Herein, we screened 14 prognostic RBP genes and constructed a risk signature to predict the prognosis of glioma patients. Univariate Cox regression was used to identify overall survival (OS)-related RBP genes. Prognostic RBP genes were screened and used to establish the RBP-signature using the least absolute shrinkage and selection operator (Lasso) method in The Cancer Genome Atlas (TCGA) cohort. The 14 RBP genes signature showed robust and stable prognostic value in the TCGA training ( = 562) cohort and in three independent validation cohorts (Chinese Glioma Genome Atlas [CGGA]seq1, CGGAseq2, and GSE16011 datasets comprising 303, 619, and 250 glioma patients, respectively). Risk scores were calculated for each patient and high-risk gliomas were defined by the median risk score in each cohort. Survival analysis in subgroups of glioma patients showed that the RBP-signature retained its prognostic value in low-grade gliomas (LGGs) and glioblastomas (GBM)s. Univariate and multivariate Cox regression analysis in each dataset and the meta cohort revealed that the RBP-signature stratification could efficiently recognize high-risk gliomas [Hazard Ratio (HR):3.662, 95% confidence interval (CI): 3.187-4.208, < 0.001] and was an independent prognostic factor for OS (HR:1.594, 95% CI: 1.244-2.043, < 0.001). Biological process and KEGG pathway analysis revealed the RBP gene signature was associated with immune cell activation, the p53 signaling pathway, and the PI3K-Akt signaling pathway and so on. Moreover, a nomogram model was constructed for clinical application of the RBP-signature, which showed stable predictive ability. In summary, the RBP-signature could be a robust indicator for prognostic evaluation and identifying high-risk glioma patients.
据报道,RNA结合蛋白(RBPs)与癌症恶性肿瘤有关,但在胶质瘤中的相关功能研究较少。在此,我们筛选了14个预后RBP基因,并构建了一个风险特征来预测胶质瘤患者的预后。单因素Cox回归用于识别与总生存期(OS)相关的RBP基因。在癌症基因组图谱(TCGA)队列中,使用最小绝对收缩和选择算子(Lasso)方法筛选预后RBP基因并用于建立RBP特征。14个RBP基因特征在TCGA训练队列(n = 562)以及三个独立验证队列(分别包含303、619和250例胶质瘤患者的中国胶质瘤基因组图谱[CGGA]seq1、CGGAseq2和GSE16011数据集)中显示出强大且稳定的预后价值。为每位患者计算风险评分,并根据每个队列中的中位风险评分定义高危胶质瘤。胶质瘤患者亚组的生存分析表明,RBP特征在低级别胶质瘤(LGGs)和成胶质细胞瘤(GBMs)中保留了其预后价值。每个数据集和meta队列中的单因素和多因素Cox回归分析表明,RBP特征分层可以有效识别高危胶质瘤[风险比(HR):3.662,95%置信区间(CI):3.187 - 4.208,P < 0.001],并且是OS的独立预后因素(HR:1.594,95% CI:1.244 - 2.043,P < 0.001)。生物学过程和KEGG通路分析表明,RBP基因特征与免疫细胞激活、p53信号通路和PI3K - Akt信号通路等有关。此外,构建了一个列线图模型用于RBP特征的临床应用,该模型显示出稳定的预测能力。总之,RBP特征可能是预后评估和识别高危胶质瘤患者的有力指标。