Abstract
Protein biomarkers for epithelial ovarian cancer are critical for the early detection of the cancer to improve patient prognosis and for the clinical management of the disease to monitor treatment response and to detect recurrences. Unfortunately, the discovery of protein biomarkers is hampered by the limited availability of reliable and sensitive assays needed for the reproducible quantification of proteins in complex biological matrices such as blood plasma. In recent years, targeted mass spectrometry, exemplified by selected reaction monitoring (SRM) has emerged as a method, capable of overcoming this limitation. Here, we present a comprehensive SRM-based strategy for developing plasma-based protein biomarkers for epithelial ovarian cancer and illustrate how the SRM platform, when combined with rigorous experimental design and statistical analysis, can result in detection of predictive analytes.Our biomarker development strategy first involved a discovery-driven proteomic effort to derive potential N-glycoprotein biomarker candidates for plasma-based detection of human ovarian cancer from a genetically engineered mouse model of endometrioid ovarian cancer, which accurately recapitulates the human disease. Next, 65 candidate markers selected from proteins of different abundance in the discovery dataset were reproducibly quantified with SRM assays across a large cohort of over 200 plasma samples from ovarian cancer patients and healthy controls. Finally, these measurements were used to derive a 5-protein signature for distinguishing individuals with epithelial ovarian cancer from healthy controls. The sensitivity of the candidate biomarker signature in combination with CA125 ELISA-based measurements currently used in clinic, exceeded that of CA125 ELISA-based measurements alone. The SRM-based strategy in this study is broadly applicable. It can be used in any study that requires accurate and reproducible quantification of selected proteins in a high-throughput and multiplexed fashion.
Highlights
Clinical management of aggressive tumors requires sensitive and specific protein biomarkers that can be monitored in a non-invasive way [1]
While this model accurately recapitulates the clinical disease, a potential caveat is that most epithelial ovarian cancer (EOC) are serous histology and biomarker candidates derived from it could be specific for endometrioid OC
To identify biomarker candidates secreted or shed by tumors into circulation, we focused on glycoproteins, which are representative of the vast majority of currently approved biomarkers [24]
Summary
Clinical management of aggressive tumors requires sensitive and specific protein biomarkers that can be monitored in a non-invasive way [1]. The complex and large dynamic range of protein concentrations in plasma pose a technical challenge for the accurate, sensitive and reproducible quantification of biomarker candidates across hundreds of samples [4]. Targeted mass spectrometry (MS) based on Selected Reaction Monitoring (SRM) is a highly sensitive MS approach for accurate and reproducible protein quantification and for fast and costeffective development of assays. It has been proposed several years ago as an alternative method to immune reagent based measurements for developing biomarkers [2, 3]. The investment of substantial resources for SRM-based quantification across large subject cohorts requires a careful selection of protein targets. Since the measurements will likely span a considerable time on the mass spectrometer, controls such as heavy labeled internal standards should be included to account for variability in instrument performance
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