Speaker: David Muddiman, North Carolina State University
Topic: Innovative Chemistries and Technologies to Read the Complex Language of Biology (following vendor show)
Date: Monday, September 12, 2016
Time: 6:00 pm Vendor Show and Dinner
7:15 pm: Presentation from David Muddiman
Location: Shimadzu Scientific Instrument, Inc. Training Center 7100 Riverwood Drive, Columbia, MD 21046 (Directions)
Dinner: Please RSVP to Katherine Fiedler (Katherine.L.Fiedler@fda.hhs.gov) before September 12 if you will be attending the dinner or are a presenting as a vendor.
Abstract: Mass spectrometry offers the most robust platform to discover and characterize new diagnostic, prognostic, and therapeutic biomarkers for ovarian cancer across all molecular classes. Moreover, a systems biology approach will allow the underlying biology and origin of ovarian cancer to be understood. This presentation will discuss the challenges specific to the study of epithelial ovarian cancer (EOC) in humans and how these challenges have directed our thinking in terms of the development of model organisms and mass spectrometry-based bioanalytical strategies. First, to augment the human model, we developed the domestic hen model of spontaneous EOC, which allowed us to longitudinally sample the rapid onset and progression of the disease in a controlled environment. Second, we developed bioanalytical tools to characterize structurally challenging analytes that are critical to a systems-level analysis. To increase the electrospray response of N-linked glycans, we synthesized novel hydrophobic tagging reagents which have the added benefit of being able to incorporate a stable-isotope label for relative quantification experiments (INLIGHTTM). Furthermore, we developed a novel ionization technique for tissue imaging of lipids and metabolites. This unique model organism has and continues to provide new insights into the biology of ovarian cancer; combined with other –OMICS data obtained through these novel bioanalytical approaches, we will understand the origin of ovarian cancer and ultimately translate that knowledge to humans.