Imaging regional gene expression variability in brain tumor associated seizures

 描述(申请人提供)：肿瘤相关癫痫(TAS)出现在大约一半的脑肿瘤患者中，并导致这些患者的生活质量显著下降。TAS的多因素性质阻碍了对TAS潜在机制的理解，因为成像和基因组特征都起着关键作用。TAS是开发新疗法的关键。联合检测神经影像和基因表达在TAS中的作用，将比单独评估任何一种模式更容易发现TAS的生物学相关机制。这项研究的中心假设是，肿瘤基因的表达与TAS以大脑区域特有的方式相关。这项研究将利用来自精心管理的公共存储库的基因组和MRI数据：癌症基因组图谱(TCGA)、分子脑肿瘤数据存储库(伦勃朗，用于验证)和癌症成像档案库(TCIA)。具体目标是：1)使用TCGA数据集，识别在有和没有TAS患者中差异表达的基因和基因集。2)使用TCGA和TCIA数据集，描述基因表达与TAS显著相关的脑区域。特别关注SLC7A11的表达，它编码系统的XC-谷氨酸转运体，通过谷氨酸的失调导致TAS的一个成熟的机制。将对这些数据集进行评估，以确定其他新基因和基因集的差异表达。新开发的基因表达统计图像映射工具将用于分析SLC7A11和其他关键基因在大脑哪些区域的表达与TAS显著相关，假设SLC7A11的表达与TAS在时间上的相关性高于额叶。与TAS相关的基因，因为与肿瘤的位置有关，但没有特定的致痫机制，将不会显示出有意义的区域。同时结合基因表达和成像信息是表征TAS的一种新颖而有力的方法。根据NINDS癫痫研究基准，这项工作的完成将导致1)对最有可能对抗谷氨酸能治疗有反应的肿瘤的识别；2)与癫痫相关的基因和途径的识别；3)促进对TAS致痫过程的理解。

 DESCRIPTION (provided by applicant): Tumor associated seizures (TAS) are present in approximately half of the patients with brain tumors and cause a marked decrease in the quality of life in these patients. Understanding the underlying mechanisms of TAS, crucial in developing new therapies, is hindered by its multifactorial nature, as both imaging and genomic characteristics play key roles. Examining the contribution of neuroimaging and gene expression in TAS in concert will more readily lead to discovery of biologically relevant mechanisms of TAS than by assessment of either modality in isolation. The central hypothesis of this study is that tumor gene expression is associated with TAS in a brain region-specific manner. This study will utilize the genomic and MRI data from carefully curated public repositories: The Cancer Genome Atlas (TCGA), Repository for Molecular BRAin Neoplasia DaTa (REMBRANDT, for validation), and The Cancer Imaging Archive (TCIA). The specific aims are: 1) Using TCGA dataset, identify genes and gene sets that are differentially expressed in patients with versus without TAS. 2) Using TCGA and TCIA datasets, characterize brain regions where gene expression has significant correlation with TAS. Particular focus will be on the expression of SLC7A11 which encodes the system xc- glutamate transporter, which causes a well-established mechanism of TAS through dysregulation of glutamate. The datasets will be assessed for differential expression of other novel genes and gene sets. Newly developed gene expression statistical image mapping tools will be utilized to analyze in what brain region the expression of SLC7A11 and other key genes are significantly associated with TAS, with the hypothesis that SLC7A11 expression have a higher correlation with TAS in the temporal, as compared to the frontal, lobes. Genes that are correlated to TAS because of association with tumor location, but without specific epileptogenic mechanisms, will demonstrate no regions of significance. Incorporating both gene expression and imaging information simultaneously is a novel and powerful method of characterizing TAS. In accordance with the NINDS Benchmarks for Epilepsy Research, completion of this will result in 1) improved identification of tumors that are most likey to respond to anti-glutaminergic treatments, 2) identification of genes and pathways associated with epilepsy; 3) advancement in the understanding of the epileptogenic process of TAS.