Zhang Qiang, Liu Wenhao, Luo Shun-Bin, Xie Fu-Chen, Liu Xiao-Jun, Xu Ren-Ai, Chen Lixi, Su Zhilin
Department of Clinical Laboratory, The People's Hospital of Lishui, Lishui, China.
Guangdong-Hong Kong-Macao Greater Bay Area (GBA) Research Innovation Institute for Nanotechnology, Guangzhou, China.
Front Neurol. 2021 Jul 6;12:633390. doi: 10.3389/fneur.2021.633390. eCollection 2021.
Diffuse lower-grade gliomas (LGGs) are infiltrative and heterogeneous neoplasms. Gene signature including multiple protein-coding genes (PCGs) is widely used as a tumor marker. This study aimed to construct a multi-PCG signature to predict survival for LGG patients. LGG data including PCG expression profiles and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Survival analysis, receiver operating characteristic (ROC) analysis, and random survival forest algorithm (RSFVH) were used to identify the prognostic PCG signature. From the training ( = 524) and test ( = 431) datasets, a five-PCG signature which can classify LGG patients into low- or high-risk group with a significantly different overall survival (log rank < 0.001) was screened out and validated. In terms of prognosis predictive performance, the five-PCG signature is stronger than other clinical variables and IDH mutation status. Moreover, the five-PCG signature could further divide radiotherapy patients into two different risk groups. GO and KEGG analysis found that PCGs in the prognostic five-PCG signature were mainly enriched in cell cycle, apoptosis, DNA replication pathways. The new five-PCG signature is a reliable prognostic marker for LGG patients and has a good prospect in clinical application.
弥漫性低级别胶质瘤(LGGs)是浸润性和异质性肿瘤。包括多个蛋白质编码基因(PCGs)的基因特征被广泛用作肿瘤标志物。本研究旨在构建一个多PCG特征来预测LGG患者的生存情况。从癌症基因组图谱(TCGA)和中国胶质瘤基因组图谱(CGGA)下载了包括PCG表达谱和临床信息的LGG数据。使用生存分析、受试者工作特征(ROC)分析和随机生存森林算法(RSFVH)来识别预后PCG特征。从训练集(n = 524)和测试集(n = 431)数据集中,筛选出并验证了一个能将LGG患者分为总生存期有显著差异的低风险或高风险组的五PCG特征(对数秩P < 0.001)。在预后预测性能方面,五PCG特征比其他临床变量和异柠檬酸脱氢酶(IDH)突变状态更强。此外,五PCG特征可进一步将放疗患者分为两个不同风险组。基因本体(GO)和京都基因与基因组百科全书(KEGG)分析发现,预后五PCG特征中的PCGs主要富集在细胞周期、凋亡、DNA复制途径中。新的五PCG特征是LGG患者可靠的预后标志物,在临床应用中有良好前景。