Expression-based identification of OHNC genomic changes

基于表达的 OHNC 基因组变化鉴定

• 批准号: 6901174
• 负责人: XIAOFENG ZHOU
• 金额: $ 15.42万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-03-01 至 2007-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6901174
• 关键词: chromosome aberrations; chromosome deletion; clinical research; comparative genomic hybridization; fluorescent in situ hybridization; gene expression; genetic mapping; head /neck neoplasm; loss of heterozygosity; mathematical model; microarray technology; model design /development; oral pharyngeal neoplasm; statistics /biometry

Oral/head and neck cancer (OHNC) is the 6th most common cancer worldwide. Approximately 38,000 new cases of oral cancer are diagnosed in the U.S. each year. Like most human cancers, oral/head and neck cancer is characterized by chromosomal alterations. The advent of DNA microarrays has produced a massive corpus of data on gene expression dynamics associated with various disease states, but comparatively little research has been done to identify chromosomal structural abnormalities that might underlie those expression changes. The present studies seek to develop an easily usable statistical framework for identifying chromosomal alterations based on widely available gene expression data. Specifically, these studies seek to: AIM 1) Map the boundaries of structural insertions or deletions within an abnormal chromosome AIM 2) Identify chromosomes showing spatially organized abnormalities in gene expression AIM 3) Discover chromosomal alterations in oral/head and neck cancer using clinical gene expression data. These studies will provide a comprehensive and clinically useful framework for mapping chromosomal abnormalities based on statistical techniques we have recently developed to identify chromosomal break points based on gene expression data. In addition to opening archival expression data to structural analysis, these techniques can provide a "value-added" layer of data analysis to nominate incoming gene expression data for more direct analyses of chromosomal abnormality through fluorescence in situ hybridization (FISH), loss of heterozygosity (LOH), or comparative genomic hybridization (CGH).

口腔/头颈部癌(OHNC)是全球第六大常见癌症。美国每年约有3.8万例新确诊的口腔癌病例。像大多数人类癌症一样，口腔/头颈部癌症的特点是染色体改变。DNA微阵列的出现产生了大量与各种疾病状态相关的基因表达动态数据，但对可能导致这些表达变化的染色体结构异常的研究相对较少。目前的研究试图开发一个易于使用的统计框架，以基于广泛可用的基因表达数据来识别染色体变化。具体地说，这些研究试图：1)定位异常染色体内结构插入或缺失的边界；2)识别在基因表达中表现出空间组织异常的染色体；3)利用临床基因表达数据发现口腔/头颈癌中的染色体变化。这些研究将基于我们最近开发的基于基因表达数据识别染色体断裂点的统计技术，为定位染色体异常提供一个全面和临床有用的框架。除了将存档的表达数据用于结构分析之外，这些技术还可以提供“增值”的数据分析层，以提名传入的基因表达数据，以便通过荧光原位杂交(FISH)、杂合性缺失(LOH)或比较基因组杂交(CGH)更直接地分析染色体异常。