Metabolic Profiles Distinguish Early-Stage Ovarian Cancer
Samples are shown ready for testing in an ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) instrument in the laboratory of Facundo Fernández at Georgia Tech. The UPLC-MS technique was used to help identify 16 metabolites associated with early-stage ovarian cancer.
Photo: Rob Felt
Studying blood serum compounds has led scientists to a set of biomarkers that may enable development of a highly accurate screening test for early-stage ovarian cancer.
Using advanced liquid chromatography and mass spectrometry techniques coupled with machine-learning computer algorithms, researchers have identified 16 metabolite compounds that provided unprecedented accuracy in distinguishing 46 women with early-stage ovarian cancer from a control group of 49 women who did not have the disease.
While the set of biomarkers is the most accurate reported thus far for early-stage ovarian cancer, more extensive testing is needed to determine if the diagnostic accuracy will be maintained across a larger group of women.
“This work provides a proof of concept that using an integrated approach combining analytical chemistry and learning algorithms may be a way to identify optimal diagnostic features,” said John McDonald, a professor in Georgia Tech’s School of Biology and director of its Integrated Cancer Research Center. “We think our results show great promise and we plan to further validate our findings across much larger samples.”
Ovarian cancer has been difficult to treat because it typically is not diagnosed until after it has spread to other areas of the body. Researchers have been seeking a routine screening test that could diagnose the disease while it is confined to the ovaries.
Working with cancer treatment centers in the U.S. and Canada, the researchers obtained blood samples from women with stage one and stage two ovarian cancers. They separated out the serum, which contains proteins and metabolites — molecules produced by enzymatic reactions in the body.
The serum samples were analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS), two instruments joined together to better separate samples into their individual components. The researchers decided to look only at the metabolites.
“People have been looking at proteins for diagnosis of ovarian cancer for a couple of decades, and the results have not been very impressive,” said Facundo Fernández, the professor in Georgia Tech’s School of Chemistry and Biochemistry who led the analytical chemistry part of the research. “We decided to look in a different place for molecules that could potentially provide diagnostic capabilities.”
The research was reported in the journal Scientific Reports.
— John Toon