Washington Imagine a blood test that could detect the earliest signs of ovarian cancer to help far more women survive. Or one that could prevent thousands of aging men from undergoing unnecessary biopsies for prostate cancer.
Those tests are moving toward reality, thanks to new technology that can spot early signals in drops of blood.
The National Cancer Institute has begun a major study to prove whether the blood test detects early relapse in ovarian cancer patients. Relapse occurs dismally often, and if the test works as well as earlier research suggests, it could win Food and Drug Administration approval for that use within a few years.
It would take longer to prove to FDA's standards whether the test also can spot ovarian cancer the first time it strikes.
Two national testing laboratories aren't waiting. Later this year, Quest Diagnostics and LabCorp hope to begin offering the blood test, by prescription, for women at high risk of ovarian cancer because of genetic or family history.
How does the testing work? It's called proteomics, the study of all proteins in living cells.
Proteins are molecules that do the body's work by directing cells' actions. Scientists have long used single aberrant proteins as a signal, or biomarker, for different diseases -- such as PSA, or prostate specific antigen, used to screen men for prostate cancer.
But one protein gone bad seldom is definitive. Indeed, most men with elevated PSA levels don't have cancer but a benign enlarged prostate. Too often, it takes a surgical biopsy to tell.
The new method: Proteins usually work through networks of circuit boardlike interactions that leave behind microscopic patterns. In a unique collaboration, scientists at the cancer institute and FDA discovered how to measure those patterns with special technology that picks out protein fragments floating in blood, patterns that can show when normal cells have turned cancerous.
"There is a wealth of information in the blood that we didn't know about before," says NCI's Dr. Lance Liotta, who co-directs the program. "We're finding an ocean of biomarkers."