GENOMIC ANALYSIS OF MEDULLOBLASTOMAS

描述（由申请人提供）：最近，DNA寡核苷酸微阵列基因表达分析已被用于定义髓母细胞瘤的分子谱，髓母细胞瘤是儿童期最常见的恶性脑肿瘤（Pomeroy等人，2002年）。髓母细胞瘤被发现是从其他中枢神经系统胚胎性肿瘤的分子不同，其组织学亚型有独特的和功能显着的基因表达模式。基因表达谱对治疗反应具有高度预测性，在回顾性分析中预测生存率的准确性远远高于当前的临床分期标准或单一标志物基因结果预测因子。这些结果现在必须进行前瞻性验证之前，分子标记物可以用于危险分层在未来的临床试验。该提案的实验是儿童肿瘤学组（COG）III期髓母细胞瘤治疗试验的相关生物学研究，旨在优化和验证预后分子标志物。在具体目标1中，将优化、验证和开发一种多分子结果预测器，该预测器基于未来5年内在COG髓母细胞瘤试验中接受治疗的500名儿童的肿瘤基因表达谱（Affytek人类基因组U133阵列），用于未来临床试验背景下的“真实的时间”分析。在特定目标2中，基因表达数据库将用于开发分子分类学，识别由促进肿瘤发生的分子信号通路的表达谱定义的髓母细胞瘤亚类。通过将表达谱分析与从基于DNA BAC克隆（光谱基因组学）微阵列的比较基因组杂交获得的全基因组突变分析相结合，将基因表达与特定目标3中的致癌基因组突变相关联。为了实现这些目标，我们将建立一个全面的髓母细胞瘤基因表达和突变数据库，该数据库与一个大型且特征良好的儿童队列的临床结果相关。这些数据将在NCI/NINDS神经胶质瘤分子诊断倡议的网站上托管，该倡议由NCI/NINDS神经肿瘤分支的霍华德费恩和NIH生物信息学小组开发，以便世界各地的研究人员可以免费访问该项目产生的分子和临床数据库。

DESCRIPTION (provided by applicant): Recently, DNA oligonucleotide microarray gene expression analysis has been used to define molecular profiles of medulloblastomas, the most common malignant brain tumors of childhood (Pomeroy et al., 2002). Medulloblastomas were found to be molecularly distinct from other CNS embryonal tumors, and their histological subtypes had unique and functionally significant gene expression patterns. Gene expression profiles were highly predictive of response to therapy, predicting survival in a retrospective analysis with much greater accuracy than current clinical staging criteria or single marker gene outcome predictors. These results must now be prospectively validated before molecular markers can be used for risk stratification in future clinical trials. The experiments of this proposal are correlative biological studies of Phase III medulloblastoma therapy trials of the Children's Oncology Group (COG), designed to optimize and validate prognostic molecular markers. In Specific Aim 1, a multi-molecular outcome predictor, based on gene expression profiles (Affymetrix Human Genome U133 arrays) of tumors from 500 children treated in COG medulloblastoma trials over the next 5 years, will be optimized, validated and developed for "real time" analysis in the context of future clinical trials. In Specific Aim 2, the gene expression database will be used to develop a molecular taxonomy, identifying subclasses of medulloblastomas defined by the expression profiles of molecular signaling pathways that promote tumorigenesis. Gene expression will be linked to oncogenic genomic mutations in Specific Aim 3, by combining expression profiling with genome-wide mutation analysis obtained from DNA BAC clone (Spectral Genomics) microarray-based comparative genomic hybridization. In achieving these Aims, we will create a comprehensive medulloblastoma gene expression and mutation database that is linked to clinical outcome of a large and well-characterized cohort of children. The data will hosted on the website of the NCI/NINDS Glioma Molecular Diagnostic Initiative that is being developed by Howard Fine of the NCI/NINDS Neuro-Oncology Branch and the NIH Bioinformatics group, so that investigators throughout the world can have free access to the molecular and clinical database generated by this project.