Early Detection and Prevention of Ovarian Cancer by Multi-modality Metabolomics and Proteomics - Epithelial ovarian cancer is the most lethal gynecologic malignancy, partially due to its significant delay in diagnosis, where 80% of patients are diagnosed at an advanced stage. There is an unmet need to achieve early screening and diagnosis for epithelial ovarian cancers. Endometriosis, defined by endometrial tissue growing outside of the uterine cavity, is a known risk factor for all types of epithelial ovarian cancers; patient studies observed a four-fold increased risk for overall epithelial ovarian cancer diagnosis. The overarching goal of this proposal is to decipher the molecular interplay between endometriosis and ovarian cancer, with the goal of developing preventative and early diagnostic strategies for invasive ovarian cancers using a multimodality approach: a) Nuclear Magnetic Resonance metabolomics, b) Mass spectrometry imaging and c) LC-MS proteomics. Metabolomics and proteomics will give us the global molecular and metabolic landscape of both disease systems, while mass spec imaging highlights the spatial location within the tissue. This multimodality approach is innovative as it has the opportunity to determine the molecular interplay between endometriosis and ovarian cancer. Once the molecular interplay has been determined, it can be used as a template to incorporate drug discovery strategies for the prevention of ovarian cancers. This is the transitional research proposal with multiple sponsors for the K00 phase. Including the laboratories of Martin Matzuk, M.D., Ph.D. in the Department of Pathology and Immunology and Michael Lewis, Ph.D. member of the Dan L Duncan Comprehensive Cancer Center and academic director of the PDX core, both at Baylor College of Medicine. Aim 1, is to identify the metabolic and signaling targets for the treatment of type 1 ovarian cancers with two sub aims. One is to determine the molecular link between endometriosis and type 1 ovarian cancers and the other is to develop preventative strategies for ovarian cancer with novel therapeutics. Aim 2, is to identify biomarkers for early detection of type 2 ovarian cancers in vivo and in patients. The success of this proposal has the potential for building diagnostic advances in the early-stage detection of ovarian cancers, which will increase therapeutic efficacy and provide therapies to prevent malignant progression toward ovarian cancer. Included in this proposal is a fellowship training plan to be conducted in K00 phase. They include additional training in metabolomic data analysis, research skills in small animal handling, histological and proteomic techniques, public speaking, scientific writing, mentoring, and institutional networking all during the postdoctoral training.
