Representational analysis of DNA copy number/methylation

描述（由申请人提供）：基因组中甲基化状态和DNA拷贝数的变化在癌症的发生和进展中起着关键作用。这些变化的定位和量化对于发现新的肿瘤抑制基因和致癌基因具有重要意义，并为临床疾病管理提供癌症分类的巨大潜力。因此，该项目的总体目标是开发一种基于阵列的高通量商业技术，以全球扫描基因组的DNA拷贝数变化（目标是检测两倍差异）和甲基化状态。这将通过在BeadArrayTM平台上使用比较基因组杂交（CGH）和限制性标记基因组扫描（RLGS）技术的降低复杂性表示方法来实现。这种表示方法有几个直接的好处。首先，表示的放大将增强阵列上的信噪比。其次，生成表征的改进将提供一个更具可重复性和鲁棒性的过程，允许准确检测DNA拷贝数和甲基化变化，特别是从显示DNA降解的档案样本中。最后，通过将RLGS从基于二维凝胶的方法（大约1000-2000个基因座）转换为基于beadarraytm的分析（大约1000- 50000个基因座），将实现更高的基因座分辨率和样品吞吐量。这将使对成百上千个肿瘤样本的大规模分析成为可能，并提高对肿瘤发生的认识。第二阶段将把这项技术应用于肿瘤样本和细胞系的分析。

DESCRIPTION (provided by applicant): Changes in methylation state and DNA copy number within the genome play a key role in cancer development and progression. Localization and quantification of these changes is important to the discovery of new tumor suppressor genes and oncogenes, and offers great potential in classifying cancer for clinical disease management. As such, the overall objective of this project is to develop a high-throughput array-based commercial technology to globally scan the genome for changes in DNA copy number (goal to detect two-fold differences) and methylation state. This will be accomplished via a reduced complexity representation approach using comparative genomic hybridization (CGH) and restriction landmark genome scanning (RLGS) technology on a BeadArrayTM platform. There are several immediate benefits offered by this representation approach. First of all, amplification of the representations will enhance signal to noise on the array. Secondly, improvements in generating representations will provide a more reproducible and robust process, allowing accurate detection of DNA copy number and methylation changes especially from archival samples exhibiting DNA degradation. Finally by converting RLGS from a 2-D gel-based approach (approximately 1000-2000 loci) to a BeadArrayTM-based analysis (approximately 1000-50,000 loci), a much higher locus resolution and sample throughput will be realized. This should enable the large-scale analysis of hundreds to thousands of tumor samples and lead to improved understanding of tumorogenesis. Phase II will apply this technology to the analysis of tumor samples and cell lines.