Signaling Network Dynamics in Metastatic Prostate Cancer

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DESCRIPTION (provided by applicant): Uncertainties and controversies characterize the diagnosis and treatment of CaP. There is a desperate need to identify those forms of CaP that are life threatening. These challenges cannot be fully confronted until there is a better understanding of how the signaling pathways in CaP cells differ from those in their normal counterparts. However, identifying these differences is complicated by the extraordinary plastic and robust nature of these biochemical networks. Furthermore, these complications have consequences in terms of therapeutic intervention. The recent correlation of several key signaling proteins with metastatic androgen-independent CaP offers the promise of diagnostic and prognostic breakthroughs for this disease. However, the requisite technological tools are lacking to directly and simultaneously detect the activity of these enzymes in their natural environment. The proposed multidisciplinary research program seeks to develop a highly integrated molecular/analytical strategy to assess the dynamics of the signaling network associated with CaP. Differences and similarities in the general response of these networks to pathway perturbation by pharmacological agents as a function of cell type will be noted. Specific aims include (1) the construction of a semi-automated instrument that rapidly initiates and assesses enzymatic activity in single cells, (2) the creation of selective reporters of CaP-relevant signaling pathway nodes, (3) the transformation of these reporters into cell permeable analogs and the integration of their molecular activity with the instrumentation constructed in Aim 1, and (4) a demonstration that these engineered reporters can assess dynamic signaling behavior in living cells. We will also evaluate the sensitivity of these reporters to upstream activators, as well as inhibitors that target the CaP signaling network across a series of normal and CaP cell lines. PUBLIC HEALTH RELEVANCE: Current methods for the detection, diagnosis, and prognosis of metastatic prostate cancer (CaP) are subject to misinterpretation and do not directly address key biochemical processes responsible for the transformed phenotype. The proposed multidisciplinary collaborative research program will develop new technology to assess the dynamics of the signaling network linked to CaP.