Epithelial ovarian cancer (EOC) is among the most common malignancies in women worldwide. In 2009, there were an estimated 21,000 new cases in North America, and it was the 5th leading cause of cancer-mortality in women. As for most cancers, disease stage at the time of diagnosis is a critical prognostic factor. Unfortunately, due to asymptomatic disease course and the lack of dependable early detection methods, most cases present at advanced stages (III and IV) with tumors spread beyond the ovaries. This is because we have no effective means of early detection and although clinical remission is often obtained with a combination of surgery and chemotherapy, the cancers recur and women ultimately die of disease. More sophisticated "tests" that would improve disease detection at an earlier stage are urgently needed. In the current study we will use a novel approach to identify proteins that are secreted by the cancer cells and detectable in the blood that can act as "biomarkers" for EOC detection. We will focus on N-glycoproteins, which have a complex carbohydrate (i.e. sugar) attached, and which are selected for secretion and cell-surface expression, thus enriching for a specific subset of proteins with high relevance for biomarker discovery. We will implant tissue specimens from patients undergoing surgery into mice, providing a reproducible model for biomarker discovery. This approach will enable us to have levels of control using serum from animals with no tumor engraftment (negative control), serum from engrafted animals (sample of interest) and surgically removed solid tumors (positive control - i.e. origin of the biomarker). Computational analysis will enable us to identify glycoproteins that are specifically human (and therefore cancer) derived. By the end of our study we will establish a panel of markers to detect residual disease with improved accuracy.