Stanford Cancer Genome Characterization Center

描述(由申请人提供)： 斯坦福癌症基因组表征中心(CGCC)将利用在高通量基因组分析方面已有的优势和独特的技术专长，对人类癌症的DNA甲基化和DNA拷贝数变化进行系统的全基因组分析。斯坦福CGCC将加入一个癌症基因组中心联盟，其广泛目标是对人类癌症的遗传、表观遗传和基因表达变化进行详细的基因组分析，并将这些变化与临床、病理和结果数据相关联，以深入了解癌症生物学，改进癌症分类和诊断，并确定新的分子靶点和治疗策略。斯坦福CGCC是一个多学科小组，在高通量基因组分析、生物信息学、遗传学、癌症生物学和临床癌症护理方面拥有专业知识。利用癌症基因组图谱计划人类癌症生物图谱核心资源提供的高质量正常和恶性肿瘤组织的DNA，斯坦福CGCC建议：1)利用一种新的基于微阵列的技术，表征正常和恶性肿瘤组织中CpG岛和其他CpG丰富区域的全面DNA甲基化变化；以及2)识别正常和恶性肿瘤组织中全基因组DNA拷贝数的变化。生成的数据和开发的工具将不受限制地迅速提供给CGCC小组和科学界。这些数据的临床和生物学意义将通过将拷贝数和甲基化变化与CGCC联盟提供的基因表达和临床结果数据相关联来确定。

DESCRIPTION (provided by applicant): The Stanford Cancer Genome Characterization Center (CGCC) will capitalize on established strengths in high-throughput genome analysis and unique technological expertise and will carry out systematic, genome-wide analysis on DNA methylation and DNA copy number changes in human cancers. The Stanford CGCC will join a consortium of Cancer Genome Centers with the broad goals of carrying out detailed genome analysis of the genetic, epigenetic and gene expression changes in human cancers and correlating these changes with clinical, pathological and outcome data to gain insights into cancer biology, improve cancer classification and diagnosis, and identify new molecular targets and strategies for treatment. The Stanford CGCC is a multidisciplinary group with expertise in high-throughput genome analysis, bioinformatics, genetics, cancer biology and clinical cancer care. Using high quality DNAs obtained from matched normal and malignant tissues provided by the Human Cancer Biospecimen Core Resource of The Cancer Genome Atlas Project, the Stanford CGCC proposes to: 1) characterize comprehensive DNA methylation changes at CpG Islands and other CpG-rich regions of the human genome in normal and malignant tissues by using a new microarray based technology, and 2) identify genome-wide changes in DNA copy number in normal and malignant tissues. Data generated and tools developed will be made available rapidly without restriction to the CGCC groups and scientific community. Clinical and biological significance of the data will be identified by correlating copy number and methylation changes with gene expression and clinical outcome data available through the CGCC consortium.