) Both normal and malignant cellular behavior is dictated in large part by the repertoire of genes being expressed at any particular moment. We hypothesize that by monitoring a sufficiently large number of genes, tumors can be better defined and their behaviors better predicted. This proposal aims to develop and apply efficient molecular technologies to rapidly analyze clinical tumor specimens for differences in gene expression. Representational Difference Analysis (RDA) will be optimized as a high throughput means to identify differentially expressed genes from primary tumor tissue. A set of RDA products that represent differentially expressed genes from tumors with different behaviors (i.e., metastatic versus localized Ewing's sarcoma) will be arrayed. Concurrently, methods to amplify mRNA from solid tumors that will minimize skewing, will be developed in a murine model system. Finally, amplified mRNAs generated from banked tumor specimens from patients with known clinical histories, will be used to probe RDA micro-arrays to assess expression of many genes simultaneously. These investigations will directly test whether similar clinical tumor behaviors result from similar patterns of gene expression. Moreover, methods developed in this proposal should be applicable to a wide spectrum of malignancies to better characterize and predict tumor behavior.
