Functional genomics of cancer

癌症的功能基因组学

• 批准号: 7147959
• 负责人: PAUL S. MELTZER
• 金额: --
• 依托单位: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7147959
• 关键词: biotechnology; breast neoplasms; chromosome aberrations; estrogen receptors; fluorescent dye /probe; functional /structural genomics; gene expression profiling; gene mutation; genetic models; high throughput technology; human genetic material tag; human subject; melanoma; metastasis; microarray technology; neoplasm /cancer genetics; neoplastic cell; pediatric neoplasm /cancer; robotics; sarcoma; statistics /biometry

One of the major problems in cancer biology is to define the aberrant pattern of gene expression in tumor cells and to relate this pattern to specific genomic alterations which occur during tumorigenesis. To address this issue, a powerful technology, DNA microarray hybridization is being applied to analyze the consequences of chromosome anomalies at the level of gene expression. Using a robotic device, it is possible to print thousands of DNA probes representing the complete genome on a single microscope slide. Fluorescent probes prepared from any cell or tissue source of interest are then hybridized to these arrays providing a large scale view of gene expression. In parallel, DNA can be analyzed in the same fasion, providing a genome wide high resolution view of copy number change. The ultimate goal of this project is integrated genome wide analysis at multiple levels of genome strucuture and function. In this fashion, it is proving possible to profile individual diseases, and to determine the consequences of a given genetic alteration on gene expression and to identify lists of candidate genes involved in disease initiation and progression. In addition to studies of cancer samples, this technology is now being applied in model systems carrying alterations in tumor specific genes affected by translocation, activation mutation, amplification or deletion, and in models which have distinct biological properties such as metastasis or responsiveness to hormones. Information obtained from model systems is then integrated with gene expression profiles derived from the statistical analysis of expression data from tissue specimens. Our recent efforts have applied this technology to pediatric cancers, adult sarcomas, melanoma and breast cancers. We have been able to establish the potential of microarrays for the accurate diagnosis of pediatric cancers and for distinguishing estrogen receptor positive breast cancers from receptor negative tumors. Using data from laboratory models we have uncovered patterns of gene expressionrelated to important clinical properties of cancers such as estrogen sensitivity in breast cancer and metastasis in melanoma and osteosarcoma. Numerous candidate genes of potential biological importance have been identified for further investigation. To approach the problem of analyzing multiple genes we are using RNA interference technology coupled with high content screening using scanning microscopy to assess the phenotypic impact of altering the level of expression of candidate genes which are overexpressed. Candidate genes which are lost are evaluated by DNA sequencing. In this fashion, we are using the human genome sequence and the tools of genome technology to gain deeper understanding of how perturbations of genome function lead to the development of cancer.

癌症生物学的主要问题之一是确定肿瘤细胞中基因表达的异常模式，并将这种模式与肿瘤发生过程中发生的特定基因组改变联系起来。为了解决这个问题，一种强大的技术，DNA微阵列杂交被应用于分析染色体异常在基因表达水平上的后果。使用机器人设备，可以在一张显微镜载玻片上打印数千个代表完整基因组的DNA探针。从感兴趣的任何细胞或组织源制备的荧光探针然后杂交到这些阵列，提供基因表达的大规模视图。与此同时，DNA也可以以同样的方式进行分析，提供全基因组范围内拷贝数变化的高分辨率视图。该项目的最终目标是在基因组结构和功能的多个水平上进行全基因组综合分析。通过这种方式，证明有可能对个别疾病进行分析，确定特定基因改变对基因表达的影响，并确定与疾病发生和进展有关的候选基因清单。除了对癌症样本的研究外，这项技术现在正被应用于携带受易位、激活突变、扩增或缺失影响的肿瘤特异性基因改变的模型系统，以及具有不同生物学特性（如转移或对激素的反应）的模型。然后将从模型系统获得的信息与来自组织标本表达数据的统计分析得出的基因表达谱相结合。我们最近的努力已经将这项技术应用于儿童癌症、成人肉瘤、黑色素瘤和乳腺癌。我们已经能够确定微阵列的潜力，以准确诊断儿童癌症和区分雌激素受体阳性乳腺癌与受体阴性肿瘤。利用实验室模型的数据，我们发现了与癌症重要临床特征相关的基因表达模式，如乳腺癌的雌激素敏感性和黑色素瘤和骨肉瘤的转移。许多具有潜在生物学重要性的候选基因已被确定供进一步研究。为了解决分析多基因的问题，我们使用RNA干扰技术结合扫描显微镜的高含量筛选来评估改变过表达候选基因的表达水平对表型的影响。丢失的候选基因通过DNA测序进行评估。以这种方式，我们正在使用人类基因组序列和基因组技术工具来更深入地了解基因组功能的扰动如何导致癌症的发展。

项目成果

Predicting continuous values of prognostic markers in breast cancer from microarray gene expression profiles.

从微阵列基因表达谱预测乳腺癌预后标志物的连续值。

• 发表时间: 2004
• 期刊: Molecular cancer therapeutics
• 影响因子: 5.7
• 作者: Gruvberger-Saal,SofiaK;Eden,Patrik;Ringner,Markus;Baldetorp,Bo;Chebil,Gunilla;Borg,Ake;Ferno,Marten;Peterson,Carsten;Meltzer,PaulS
• 通讯作者: Meltzer,PaulS

Differential responses of stress genes to low dose-rate gamma irradiation.

• 发表时间: 2003-04
• 期刊: Molecular cancer research : MCR
• 作者: S. Amundson;Richard A. Lee;C. A. Koch-Paiz;M. Bittner;P. Meltzer;J. Trent;A. Fornace

Gene expression profiles in a panel of childhood leukemia cell lines mirror critical features of the disease.

• 发表时间: 2003-07
• 期刊: Molecular cancer therapeutics
• 影响因子: 5.7
• 作者: U. Kees;J. Ford;Marcia Watson;A. Murch;M. Ringnér;R. Walker;P. Meltzer

Expression profiling to predict outcome in breast cancer: the influence of sample selection.

表达分析以预测乳腺癌的预后：样本选择的影响。

• DOI: 10.1186/bcr548
• 发表时间: 2003
• 期刊: BREAST CANCER RESEARCH
• 影响因子: 7.4
• 作者: Gruvberger, SK;Ringnér, M;Edén, P;Borg, Å;Fernö, M;Peterson, C;Meltzer, PS
• 通讯作者: Meltzer, PS

The gene expression response of breast cancer to growth regulators: patterns and correlation with tumor expression profiles.

• 发表时间: 2003-11
• 期刊: Cancer research
• 影响因子: 11.2
• 作者: H. Cunliffe;M. Ringnér;S. Bilke;R. Walker;Jennifer Cheung;Yidong Chen;P. Meltzer