Functional genomics of cancer

癌症生物学中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期间发生的特定基因组改变相关联。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的基因表达水平的后果。使用机器人设备，可以在单个显微镜载玻片上打印数千个代表完整基因组的DNA探针。然后将从任何感兴趣的细胞或组织来源制备的荧光探针与这些阵列杂交，提供基因表达的大尺度视图。同时，可以在相同的片段中分析DNA，提供拷贝数变化的全基因组高分辨率视图。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。以这种方式，它被证明是可能的个人疾病，并确定一个给定的基因改变对基因表达的后果，并确定参与疾病的起始和进展的候选基因的列表。除了对癌症样本的研究之外，该技术现在还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性）的模型。然后将从模型系统获得的信息与从组织样本的表达数据的统计分析得到的基因表达谱整合。我们最近的努力已经将这项技术应用于儿科癌症，成人肉瘤，黑色素瘤和乳腺癌。我们已经能够确定微阵列用于儿童癌症的准确诊断和用于区分雌激素受体阳性乳腺癌与受体阴性肿瘤的潜力。利用实验室模型的数据，我们发现了与癌症的重要临床特性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用于进一步研究。为了解决分析多个基因的问题，我们使用RNA干扰技术结合使用扫描显微镜的高含量筛选来评估改变过表达的候选基因的表达水平的表型影响。通过DNA测序评估丢失的候选基因。以这种方式，我们正在使用人类基因组序列和基因组技术的工具，以更深入地了解基因组功能的扰动如何导致癌症的发展。

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.