The objectives of the proposed research are to provide novel methods for the analysis of the complex interactions between gene products at the level of gene expression. A great deal of research demonstrates that the outcome of exposure of a cell to two different signals is not predictable from the response to each signal on its own. This general principle holds true for the cooperative effects of exogenous signaling molecules as well as the effects of gene expression and mutation. Detailed analysis of the mechanisms by which the consequences of such interactions are created requires novel approaches to the dissection of gene regulatory networks. As the most detailed analysis of interactions between different regulatory pathways has been carried out in regard to the consequences of expression of cooperating oncogenes, this area is especially promising for the application of newly developed analytical tools. The proposed methodology includes the following components: (1) Multivariate search for a set of differentially expressed genes allowing for multidimensional characteristics of gene expression data, (2) Identification of a subset of candidate genes that participate in the cooperative response of a cell to multiple mutations, and (3) Reconstruction of a gene signaling network that underlies the cooperative effect of multiple mutations on a specific cell function, thereby providing the necessary information on causal relationships between cooperating genes. By combining methods of computational biology, multivariate statistics, and experimental studies it is possible to greatly enhance the ability to understand complex mechanisms of cell responses to multiple gene perturbations. While the main objective is to develop a general methodology that will be widely applicable in various experimental settings, biological experiments will be conducted to study the effects of two oncogenic mutations on such fundamental cell functions as survival and proliferation. This experimental program may have additional benefits such as pinpointing drug targets within a particular circuit supporting cell proliferation and/or survival.
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