Project Summary/Abstract Ovarian cancer (OVC) is the deadliest gynecologic cancer and the fifth leading cause of cancer-related death among US women. A critical limitation in fighting OVC is the inability to detect OVC early (stages I & II). Detection at early stages improves five-year survival to ~95% compared to ~57% overall. The five-year survival further drops to ~36% for black women. Currently, no reliable diagnostic markers are available that identify OVC early and accurately. We utilize female chickens (hens) as a model to identify early and accurate diagnostic biomarkers for OVC. Chickens (unlike mice) develop OVC spontaneously, just like humans. Moreover, disease progression and disease staging parallels human OVC. Further, total number of ovulation events (a risk factor, if high) and age of onset (menopause) are also similar across both species. The overarching long-term goal of this research is to design and validate a diagnostic test similar to a mammogram or a pap smear that can be routinely performed to identify OVC before it can be clinically identified. Based on our preliminary data, this proposal seeks to identify and validate the potential role of lipid metabolites as potential diagnostic biomarkers of OVC. In this proposal, we will utilize specific-pathogen free hens as an animal model. These hens develop OVC spontaneously (similar to humans) with ~10-30% penetrance by 3.5 years of age. Based on our pilot studies, we will perform non-biased metabolomic analysis on longitudinally harvested plasma samples using the Sciex 6500+ quadropule ion trap (QTrap) in conjunction with the C18 liquid chromatography-tandem mass spectrometry (LC-MS/MS) Multiple Reaction Monitoring (MRM) method for detecting ~550+ annotated metabolites. Further, we will perform pre-clinical metabolomic validation on plasma samples obtained directly from untreated patients, patients with benign disease presentation, and age-matched controls. Such comprehensive metabolite profiling especially for lipid metabolites as early and accurate diagnostic biomarkers in human ovarian cancer lays the groundwork for large-scale validation in patients, helping fulfill a critical need in the ovarian cancer precision prevention landscape.