Functional genomics of cancer

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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.