Bioinformatic Profiling Identifies a Glucose-Related Risk Signature for the Malignancy of Glioma and the Survival of Patients
Bioinformatic Profiling Identifies a Glucose-Related Risk Signature for the Malignancy of Glioma and the Survival of Patients
复制标题
生物信息分析确定了神经胶质瘤恶性肿瘤和患者生存的葡萄糖相关风险特征。
DOI：
10.1007/s12035-016-0314-4
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发表时间：
2017-12-01
影响因子：
5.1
通讯作者：
Fan, Lihua
中科院分区：
文献类型：
--
作者：
Zhao, Shihong;Cai, Jinquan;Fan, Lihua
本研究的目的是探讨脑胶质瘤的糖代谢状态及其预后价值。中国胶质瘤基因组图谱(CGGA)、癌症基因组图谱(TCGA)和GSE16011数据集被用来开发与葡萄糖相关的信号。从中国胶质瘤基因组图谱数据库中获得全基因组微阵列表达数据的305例胶质瘤样本作为研究对象。使用TCGA和GSE16011数据集进行验证。利用基因集浓缩分析(GSEA)和细胞图像分析技术探讨其生物信息学意义。GSEA揭示了与葡萄糖相关的信号相关的生物学过程。Cytoscape可视化了基因之间的相关性分析。我们还收集了胶质瘤患者的血糖信息，分析其与肿瘤恶性程度和患者生存的关系。在这项研究中，我们发现葡萄糖相关基因集可以区分胶质瘤的临床和分子特征，参与胶质瘤的恶性程度。然后，我们在CGGA数据集中为胶质母细胞瘤患者开发了一个与葡萄糖相关的预后标志，并在其他公共数据集中进行了验证。GSEA显示，葡萄糖相关信号风险分数较高的肿瘤可能与细胞周期时相相关。此外，血糖浓度与脑胶质瘤的恶性程度和患者的生存有关。这些结果可能为脑胶质瘤的恶性研究和个体化治疗提供新的视角。我们的研究为进一步深入研究脑胶质瘤中糖代谢的作用提供了重要资源。
The aim of this study is to investigate the glucose metabolic status and its prognostic value in glioma. The Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), and GSE16011 datasets were used to develop the glucose-related signature. A cohort of 305 glioma samples with whole genome microarray expression data from the Chinese Glioma Genome Atlas database was included for discovery. TCGA and GSE16011 datasets were used for validation. Gene Set Enrichment Analysis (GSEA) and Cytoscape were used to explore the bioinformatic implication. GSEA revealed the biological process associated with the glucose-related signature. Cytoscape visualized the correlation analysis among the genes. We also collected the blood glucose information of patients with gliomas to analyze the association with tumor malignancy and patients' survival. In this study, we identified that glucose-related gene sets could distinguish the clinical and molecular features of gliomas, involved in the malignancy of gliomas. And then, we developed a glucose-related prognostic signature for patients with glioblastoma in the CGGA dataset, validated in other additional public datasets. GSEA illustrated that tumor with higher risk score of glucose-related signature could correlate with cell cycle phase. In addition, blood glucose concentration was associated with the malignancy of glioma and the survival of patients. These results might provide new view for the research of glioma malignancy and individual treatment. Our research provided important resources for future dissection of glucose metabolic role in glioma.