Despite advances in surgery and chemotherapy, ovarian cancer is still the most lethal form of gynecologic cancer and the fourth leading cause of cancer death among women in the United States; claiming 16,210 lives in 2005.
Survival rates for ovarian cancer have remained stubbornly low because symptoms are often vague and mimic other conditions, and the lack of a cost-effective, reliable test to diagnose this "silent killer" early, when it is most curable. A test is urgently needed that would rival the positive impact on survival that the Pap smear and mammography have had on cancers of the cervix and breast, respectively.
The statistics tell the story. Currently, three of every four women have advanced stage ovarian cancer when they are diagnosed, and only 25 percent of these women survive for five years. In contrast, the one woman in four diagnosed with early stage disease has a five-year survival rate exceeding 90 percent.
Scientists at these institutions have used sophisticated computer-modeling programs to interpret data from nuclear magnetic resonance (NMR) analyses of blood samples and produce cellular profiles that show the identities, structures and proportions of metabolites (metabonomics).
This NMR-based metabonomics approach has identified characteristics, known as biomarkers, in blood samples that can leave a "biomolecular signature" that distinguishes women with early stage ovarian cancer from healthy women. Scientists believe that these biomarkers could be developed into a screening test for ovarian cancer.
However, before this simple blood test can be developed, researchers will use the same approach to hone in on the specific metabolite (or metabolites) responsible for differences between healthy women and cancer patients, and make early diagnosis of ovarian cancer possible. These metabolites also could be targets for therapy.
Scientists believe that this NMR-based metabonomics approach will not only benefit thousands of women each year, but have practical implications in other types of cancer as well.