Imaging regional gene expression variability in brain tumor associated seizures

 描述（由申请方提供）：肿瘤相关性癫痫发作（TAS）存在于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。了解TAS的潜在机制，在开发新的治疗方法中至关重要，但由于其多因素的性质，成像和基因组特征都起着关键作用，因此受到阻碍。检查TAS中神经影像学和基因表达的贡献将更容易发现TAS的生物学相关机制，而不是孤立地评估任何一种方式。本研究的中心假设是肿瘤基因表达与TAS以脑区域特异性方式相关。这项研究将利用来自精心策划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DaTa存储库（伦勃朗，用于验证）和癌症成像档案（TCIA）。具体目的是：1）使用TCGA数据集，识别TAS患者与非TAS患者中差异表达的基因和基因集。2)使用TCGA和TCIA数据集，表征基因表达与TAS显著相关的大脑区域。将特别关注编码系统xc-谷氨酸转运蛋白的SLC 7A 11的表达，其通过谷氨酸的失调引起TAS的充分确立的机制。将评估数据集的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在什么脑区域中SLC 7A 11和其他关键基因的表达与TAS显著相关，假设与额叶相比，在颞叶中SLC 7A 11表达与TAS具有更高的相关性。由于与肿瘤位置相关而与TAS相关的基因，但没有特定的致癫痫机制，将不会显示有意义的区域。同时描述基因表达和成像信息是表征TAS的一种新颖而强大的方法。根据NINDS癫痫研究基准，完成该研究将导致1）更好地识别最可能对抗多巴胺能治疗有反应的肿瘤，2）识别与癫痫相关的基因和途径; 3）促进对TAS致癫痫过程的理解。

 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.