Using genetic predictors of CA125 to improve personalized ovarian cancer screening
Most ovarian cancer cases are currently diagnosed at late stage when less than half of the women will live five years after their diagnosis. In contrast, ovarian cancer cases diagnosed at an early stage have more than 90% living after five years from diagnosis. Thus, early detection of ovarian cancer, which would allow earlier interventions, could lead to a significant improvement in ovarian cancer survival. However, despite extensive efforts to identify early detection biomarkers, the blood biomarker CA125 remains the best candidate for ovarian cancer screening biomarker even though it identifies women with late-stage disease but not early stage. CA125 diagnostic tests look for a specific level of CA125 that is considered abnormally high, but CA125 levels vary from person to person, meaning there is not a generalizable ‘normal’.
For her Scientific Scholar project, Dr. Sasamoto will identify the genetic factors that determine an individual’s normal CA125 levels. Based on these genetic factors, she will then develop an algorithm to determine a specific, personalized CA125 cutoff point for any given patient. This research could not only improve the CA125 test to detect ovarian cancer at much earlier stages, but can also extend its use from high-risk to average-risk individuals. It will open the door to developing a personalized and accurate early detection method that can lead to improved survival of ovarian cancer.