High-grade serous ovarian cancer (HGSOC) is the most lethal gynecologic malignancy. Although initial therapy and cancer management has vastly improved, the majority of patients relapse within 5 years of diagnosis and die of their disease. The current biomarker for monitoring HGSOC recurrence is the glycoprotein CA125. While routinely used in the clinic, the performance of CA125 in comparison to clinical symptoms of recurrence has not shown significant advantages. In addition, 10-25% of HGSOC cases do not present with elevated levels of CA125. Hence, we propose that identification of additional biomarkers that can be used as a signature will improve analytical sensitivity and clinical selectivity for surveillance of HGSOC recurrence. CA125 and the majority of other FDA approved biomarkers (PSA for prostate cancer, CEA for colorectal cancer) belong to a sub-class of proteins that are decorated with carbohydrates (termed: glycoproteins), responsible for their secretion into the blood. Glycoproteins are hence an ideal sub-class to identify novel protein biomarkers for remote sensing of cancer in blood. We have established a high-throughput screening technology (referred to as N-glyco-capture proteomics) that specifically screens for this sub-class of proteins. We intend to apply this technology to identify tumour-derived proteins present in serum of mouse models that carry surgically embedded human tumour tissue (termed: patient-derived xenografts). Subsequently, identified candidate biomarkers will be validated in longitudinally collected serum of HGSOC patients. At the completion of this project we will identify new biomarkers that either alone or in combination (i.e. biomarker signature) can be used for improved diagnosis of HGSOC recurrence. Ultimately, identification of a highly sensitive biomarker signature can improve clinical management of HGSOC and possibly help to extend life expectancy of HGSOC patients.