Hu Qi, Wu Weining, Zeng Ailiang, Yu Tianfu, Shen Feng, Nie Er, Wang Yingyi, Liu Ning, Zhang Junxia, You Yongping
Department of Neurosurgery, First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China.
Oncol Lett. 2017 Apr;13(4):2583-2590. doi: 10.3892/ol.2017.5753. Epub 2017 Feb 20.
Polycomb group (PcG) proteins form at least two key complexes, namely polycomb repressive complex 1 and polycomb repressive complex 2. These complexes are involved in the progression of various cancers. Systematic research has not been conducted on the aberrant expression of PcG members in gliomas. Using the Chinese Glioma Genome Atlas data set, PcG expression patterns between normal brain tissues and glioma samples were analyzed, and a PcG-based classifier was then developed using BRB Cox regression and risk-score model. These results were validated in an independent GSE16011 set. A total of six PcGs [chromobox protein homolog (CBX) 6, CBX7, PHD finger protein 1, enhancer of zeste homolog 2 (EZH2), DNA (cytosine-5-)-methyltransferase 3β (DNMT3B) and polyhomeotic-like protein 2] were identified to be associated with glioma grade. Survival analysis then revealed a five-PcG gene signature one protective gene (enhancer of zeste homolog 1) and four risky genes (EZH2, PHD finger protein 19, DNMT3A and DNMT3B), which may identify patients with high risk of poor prognosis of glioma. Multivariate Cox analysis indicated that the five-PcG signature was an independent prognostic biomarker. These findings indicated that a novel prognostic classifier, five-PcG signature, served as an independent prognostic marker for patients with glioma.
多梳蛋白家族(PcG)形成至少两种关键复合物,即多梳抑制复合物1和多梳抑制复合物2。这些复合物参与多种癌症的进展。尚未对胶质瘤中PcG成员的异常表达进行系统研究。利用中国胶质瘤基因组图谱数据集,分析了正常脑组织和胶质瘤样本之间的PcG表达模式,然后使用BRB Cox回归和风险评分模型开发了基于PcG的分类器。这些结果在独立的GSE16011数据集中得到验证。共鉴定出6种PcG [染色体盒蛋白同源物(CBX)6、CBX7、含PHD结构域蛋白1、zeste同源物2增强子(EZH2)、DNA(胞嘧啶-5-)-甲基转移酶3β(DNMT3B)和多同源样蛋白2]与胶质瘤分级相关。生存分析随后揭示了一个由5个PcG基因组成的特征——1个保护基因(zeste同源物1增强子)和4个风险基因(EZH2、含PHD结构域蛋白19、DNMT3A和DNMT3B),这可能识别出胶质瘤预后不良高风险患者。多变量Cox分析表明,5个PcG特征是一个独立的预后生物标志物。这些发现表明,一种新的预后分类器——5个PcG特征,可作为胶质瘤患者的独立预后标志物。