Genome-wide expression profiling of glioblastoma using a large combined cohort.
Genome-wide expression profiling of glioblastoma using a large combined cohort.
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DOI：
10.1038/s41598-018-33323-z
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发表时间：
2018-10-10
影响因子：
4.6
通讯作者：
Zhang Y
中科院分区：
文献类型：
--
作者：
Tang J;He D;Yang P;He J;Zhang Y
胶质母细胞瘤（GBM）是成人中最常见的内源性脑肿瘤，几乎普遍致命。尽管在过去的几十年里，在手术、化疗和放疗方面取得了进展，但GBM患者的预后仍然很差，患有GBM的患者的平均生存时间仍然很短。发现强大的基因签名，以更好地理解复杂的分子机制，导致GBM是一个重要的先决条件，以确定新的和更有效的治疗策略。在此，通过结合来自48项研究的GBM和正常组织样本，对基因组规模的mRNA表达数据进行了综合研究。147个稳健的基因标签被鉴定为在GBM和正常样品之间显著差异表达，其中100个（68%）基因在先前的出版物中被报道与GBM密切相关。此外，基于这147个稳健DEG的功能注释分析显示某些去调控的基因表达程序（例如，细胞周期、免疫应答和p53信号通路）与GBM的发生有关，PPI网络分析显示3个新的中枢基因（RFC 4、ZWINT和TYMS）在GBM的发生中起重要作用。此外，基于TCGA GBM数据的生存分析表明，38个稳健DEG显著影响OS中GBM的预后（p < 0.05）。这些发现为GBM的分子机制提供了新的见解，并表明38个稳健的DEG可能是诊断和治疗的潜在靶点。
Glioblastomas (GBMs), are the most common intrinsic brain tumors in adults and are almost universally fatal. Despite the progresses made in surgery, chemotherapy, and radiation over the past decades, the prognosis of patients with GBM remained poor and the average survival time of patients suffering from GBM was still short. Discovering robust gene signatures toward better understanding of the complex molecular mechanisms leading to GBM is an important prerequisite to the identification of novel and more effective therapeutic strategies. Herein, a comprehensive study of genome-scale mRNA expression data by combining GBM and normal tissue samples from 48 studies was performed. The 147 robust gene signatures were identified to be significantly differential expression between GBM and normal samples, among which 100 (68%) genes were reported to be closely associated with GBM in previous publications. Moreover, function annotation analysis based on these 147 robust DEGs showed certain deregulated gene expression programs (e.g., cell cycle, immune response and p53 signaling pathway) were associated with GBM development, and PPI network analysis revealed three novel hub genes (RFC4, ZWINT and TYMS) play important role in GBM development. Furthermore, survival analysis based on the TCGA GBM data demonstrated 38 robust DEGs significantly affect the prognosis of GBM in OS (p < 0.05). These findings provided new insights into molecular mechanisms underlying GBM and suggested the 38 robust DEGs could be potential targets for the diagnosis and treatment.
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