High Content Analysis to Identify Biomarkers for Chemopreventive Drug Activity

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DESCRIPTION (provided by applicant): Although selective estrogen receptor modulators (SERMs) have set the stage for successful chemoprevention of estrogen receptor (ER) positive mammary tumors, novel agents are urgently needed to prevent ER-negative breast cancer. The synthetic rexinoid analogue bexarotene (Targretin, LGD1069) prevents breast cancer in preclinical models and is now studied in clinical settings. The exact mechanism by which bexarotene prevents mammary tumors has not been identified; however, individual phenotypic changes elicited by this drug could be used as surrogate biomarkers, to model the effects of future successful chemopreventive agents. Several of the molecular pathways modulated by bexarotene converge to alter cell cycle and thus suppress cell proliferation. In addition to cell growth, bexarotene also regulates genes governing metabolism, including genes involved in triglyceride synthesis. Furthermore, as a ligand preferentially binding to RXR, bexarotene marks RXR as potential target for breast cancer preventive agents. Currently, comprehensive datasets integrating different phenotypes as variables, such as changes in cell cycle, receptor engagement and metabolic status of individual cells is virtually unavailable. Therefore, we propose to perform high-throughput multiplex, cell-based screens for biomarkers that readily define functional and phenotypic effects linked to agents with high activity and low toxicity. In our study a multiplex assay will be optimized to incorporate cell cycle analysis data based on DNA content and EdU incorporation, along with quantitation and intracellular localization of RXRa and neutral lipid labeling, in response to bexarotene in normal mammary epithelial cells. High-throughput fluorescence microscopy (HTM) will be used to simultaneously quantitate multiple parameters of nuclear DNA content, cell morphology, neutral lipid content and distribution, and nuclear receptor localization and activity at the single cell level, in a large population of cells. The long term goal of our studies is to define novel biomarkers and cytological phenotypes based on multiparametric cytological measurements on cells treated with agents proven to effectively prevent breast cancer. A set of these phenotypes, a cytological fingerprint can be applied to search for new compounds with better anti-proliferative effects and less toxicity. The outcomes of this study will elucidate potential targets for new chemopreventive agents as well as help the development of advanced diagnostic tools. Further development of this technology may speed up the identification and development of novel drug candidates for the prevention of cancer.