This project will develop a new framework for discovery of genes involved in the breast carcinogenesis process. Among families that have a predisposition to breast cancer, approximately 25% have inherited mutations in either breast cancer (BRCA) genes BRCA1 or BRCA2, but the predisposing mutated genes in the majority of the families are unknown. BRCA1 and BRCA2 gene products both regulate cell division pathways that involve DNA repair and centrosome duplication, and their expression is correlated in microarray analyses in many cell types. We hypothesize that other unidentified BRCA genes may be involved in the same pathways that BRCA1 and BRCA2 regulate, and thus may be discovered by identifying genes whose expression also is correlated with that of BRCA1 and BRCA2. We will interrogate public-domain gene expression databases using newly developed computational tools that include combinatorial and algebraic clustering methods to identify genes whose expression correlates with these tumor suppressors. RNA interference will be used to disrupt the expression of the candidate BRCA gene products in two cell-based assays that are dependent on BRCA1 and BRCA2 expression. The first assay models the regulation of homology-directed recombination repair of double-strand DNA breaks, and the second assay tests the control of duplication of the centrosome. We will also perform a third test to determine whether the informatics-identified candidate BRCA gene product can form a protein complex with BRCA1 since several of the already identified co-expressed genes do form a complex with BRCA1. Candidate BRCA genes that are positive in the functional cell based assays will then be tested for changes in expression of their gene products in clinical samples, using an antibody-based, high-throughput tissue microarray system. In summary, this proposal outlines a novel experimental framework that will develop new bioinformatic tools for identifying candidate genes whose regulation suggests the potential for involvement in breast carcinogenesis, testing whether depletion of the proteins encoded by these candidate genes results in phenotypes in the laboratory that are consistent with breast cancer, and determining whether the expression of these candidate genes in clinical samples indicates their potential as biomarkers for breast carcinogenesis. This project defines a framework that may also be applicable to the identification of groups of genes involved in common pathways in other disease processes.