Ovarian cancer is the second most common gynecologic malignancy, and this malignancy is the leading cause of death from gynecological cancers. At the time of presentation, most ovarian cancers are no longer dependent on single genetic determinants for growth and/or survival, and targeted therapies used as single agents typically do not work in this disease. Knowledge of signaling pathways within normal and malignant cells has led to identification of pathways and their associated targets that are aberrantly expressed or mutated in tumor cells, and actively contribute to the development and spread of cancer. Therapies directed against these cancer cell-specific activated targets have the potential to significantly improve long-term control of disease. By defining and functionally probing robust networks of signaling proteins that are essential to malignant cells, we are able to identify which network components can be targeted in parallel to fully block oncogenic pathway, essentially shutting down ‘rescue routes’. RNAi screening with a targeted library was used to identify a set of gene candidates that influence the response of epithelial ovarian cancer (EOC) cells to the Src-targeting agent dasatinib, a promising agent for treatment of EOC. Mapping the pattern of hits back to the network revealed suggestive clusters of very closely interacting proteins clustering with well validated modulators of cancer cell survival. We are analyzing the mode of action of a subset of candidates clustering with the well-validated cancer-related signaling hub. These studies offer an opportunity to employ a functional approach to identify critical drug response-modifying genes that can be therapeutically targeted as biomarkers and drug targets to improve ovarian cancer treatment outcomes with emerging targeted agents.