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Cellular and Signaling Network Cross-Talk in Ovarian Cancer

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Ovarian cancer has a mortality rate of greater than 50%, primarily due to the late stage at which it is diagnosed. This late diagnosis complicates treatment - patients accumulate different mutations in their tumors and tumor cells receive a variety of stimuli from other cell types during disease progression, making it impossible to define a blanket treatment for everyone. We are working to address this complex scenario through several complementary approaches. First, we are characterizing a panel of ovarian cancer cell lines to capture this diversity and determine how cells respond to current drugs. By delineating molecular signatures that correspond to drug sensitivities we hope to better match patients to drugs and improve prognosis. Secondly, we are examining cross-talk between signaling pathways in the tumor cell to determine signals that are responsible for controlling proliferation, providing new drug targets for ovarian cancer. Finally, we are developing in vitro culture systems to study interactions between ovarian cancer tumor cells and other cells in the tumor microenvironment in order to identify new approaches to control tumor growth. Funding for this project is provided by a grant from the American Cancer Society Institutional Research Grant and the UW-Madison Graduate School.

Cellular Decision-Making Processes in Wound Healing and Angiogenesis
In both in vivo and in vitro environments, cells are exposed to numerous extracellular stimuli that regulate their function, such as extracellular matrix proteins, growth factors, and mechanical forces. The nature of these cues and their subsequent interpretation by cells is complex; sometimes these cues work in concert to instruct cells to perform a certain function, and other times these cues are conflicting. We aim to better understand how cells “decide” what cues to follow in this complex environment, particularly in the context of dermal wound healing and angiogenesis. This work will also be combined with computational modeling (collaboration with Prof. Pam Kreeger) to predict cell behavior in untested environments. Such efforts to better understand and predict cellular decision-making processes is important in not only informing the construction of environments that allow greater control over cell behavior, but also in understanding native physiological phenomena.
Estrogen and Phytoestrogen Interactions in Breast Cancer
File:Estrogen signaling.tif Estrogen receptor (ER) expression is one of the best determinants for therapeutic choice in breast cancer. However, the roles of the two ERs (ERα and ERβ) in estrogen signaling remain unclear. Additionally, there are conflicting studies about the impacts of plant-based estrogens, called phytoestrogens, on breast cancer progression. To address these questions, we will experimentally alter the levels of ERα and ERβ and follow cellular signals and responses to treatment with estrogens and/or phytoestrogens. Our models will be used to identify critical signaling mechanisms regulating estrogenic effects on proliferation in breast cancer, providing novel drug targets. Funding for this project is provided by NSF CAREER award (#0951613) and a grant of a Veritas Microplate Luminometer from Turner Biosystems

Funding for our research is provided by

NSF CAREER award (#0951613) and a grant of a Veritas Microplate Luminometer from Turner Biosystems