Ovarian cancer is the fifth leading cause of death among women in the United States and remains the most common cause of death from a gynecologic malignancy. Most ovarian cancers are diagnosed at an advanced stage in which 5-year survival rate is approximately 30%. Given that the 5-year survival rate is greater than 90% for women diagnosed at an early stage, early detection in women presenting with vague symptoms is crucial to improve outcome. Diagnosis of ovarian cancer is largely based on symptoms, imaging, and laboratory biomarkers. Overall, more than 200 potential biomarkers differentially expressed in ovarian cancer have been identified (Lokshin, 2012). However, no single marker has been found useful for the diagnosis of ovarian cancer. Increased sensitivity and specificity for the diagnosis of ovarian cancer are observed when multiple markers are used in combination. The Food and Drug Administration (FDA) recently cleared two algorithms to evaluate the risk of ovarian cancer for women who present with pelvic mass. In this review, we will summarize the most recent serum biomarkers and clinical applications of biomarkers for the early detection and treatment monitoring of ovarian cancers. We will also discuss the algorithms for predicting the risk of ovarian cancers.
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