Affiliations: [a] Biological Sciences Division, Pacific Northwest National Laboratory, Washington, USA | [b] Departments of Ob/Gyn & Reproductive Sciences, Pathology, and Pharmacology, Yale University School of Medicine, New Haven, Connecticut, USA | [x] Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, 540 East Canfield Avenue, Detroit, MI, USA | [y] University of Pittsburgh Cancer Institute, Hillman Cancer Center, Pittsburgh, PA, USA
Correspondence:
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Address of correspondence: Karin D. Rodland, 902 Battelle Blvd, PO Box 999 MSIN J4-16, Richland WA 99352, USA. E-mail: karin.rodland@pnl.gov.
Abstract: The stark difference in clinical outcome for patients with ovarian cancer diagnosed at early stages (95% survival at 5 years) versus late stages (27.6% survival at 5 years) has driven a decades-long quest for effective biomarkers that will enable earlier detection of ovarian cancer. Yet despite intense efforts, including the application of modern high throughput technologies including transcriptomics and proteomics, there has been little improvement in performance compared to the gold standard of quantifying serum CA125 immunoreactivity paired with transvaginal ultrasound. This review describes the strategies that have been used for identification of ovarian cancer biomarkers, including the recent introduction of novel bioinformatic approaches. Results obtained using high throughput-based vs. biologically rational approaches for the discovery of diagnostic early detection biomarkers are compared and analyzed for functional enrichment.
Keywords: Ovarian cancer, diagnostics, biomarkers, early detection, systems biology
