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Geeta Mehta, PhDAssociate ProfessorMaterials Science & Engineering, Biomedical EngineeringUniversity of Michigan
Abstract:Ovarian cancer is a highly lethal gynecologic cancer, responsible for 140,000 deaths globally each year. One of the reasons for the poor outcomes is the heterogeneous and complex nature of the primary and metastatic tumor microenvironments. The progression of ovarian cancer is influenced by various environmental factors, including non-cancerous cells, mechanical stimuli, and extracellular matrix. Therefore, personalized 3D models that mimic the in vivo tumor microenvironments are essential for investigating and interpreting ovarian cancers. Our laboratory has developed multiple personalized heterogeneous tumor models to study cellular- and extracellular matrix-heterogeneity and to evaluate potent compounds to treat ovarian cancer. In this seminar, I will discuss our latest findings and progress on personalized heterogeneous models of ovarian cancer. I will present two of our model platforms, one investigating the role of fluidic shear stress in cancer progression and the other predicting therapy responses using patient-derived cells. Our ultimate goal is to develop effective and targeted treatments for all ovarian cancers, regardless of histotypes, to improve overall survival and cure rates. Additionally, our models can be used for fundamental cancer biology and translational studies. Importantly, these approaches can be extended to other carcinomas, facilitating the discovery of new therapeutics that effectively target the unique aspects of each patient’s heterogeneous disease.
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