Scientists at the Georgia Institute of Technology have attained very promising results on their initial investigations of a new test for ovarian cancer. Using a new technique involving mass spectrometry of a single drop of blood serum, the test correctly identified women with ovarian cancer in 100 percent of the patients tested. The results can be found online in the journal Cancer Epidemiology, Biomarkers, & Prevention Research.
"Because ovarian cancer is a disease of relatively low prevalence, it's essential that tests for it be extremely accurate. We believe we may have developed such a test," said John McDonald, chief research scientist at the Ovarian Cancer Institute (Atlanta) and professor of biology at Georgia Tech.
The measurement step in the test, developed by the research group of Facundo Fernandez, associate professor in the School of Chemistry and Biochemistry at Tech, uses a single drop of blood serum, which is vaporized by hot helium plasma. As the molecules from the serum become electrically charged, a mass spectrometer is used to measure their relative abundance. The test looks at the small molecules involved in metabolism that are in the serum, known as metabolites. Machine learning techniques developed by Alex Gray, assistant professor in the College of Computing and the Center for the Study of Systems Biology, were then used to sort the sets of metabolites that were found in cancerous plasma from the ones found in healthy samples. Then, McDonald's lab mapped the results between the metabolites found in both sets of tissue to discover the biological meaning of these metabolic changes.
The assay did extremely well in initial tests involving 94 subjects. In addition to being able to generate results using only a drop of blood serum, the test proved to be 100 percent accurate in distinguishing sera from women with ovarian cancer from normal controls. In addition it registered neither a single false positive nor
|Contact: David Terraso|
Georgia Institute of Technology