A proteomics technique for diagnosing early-stage ovarian cancer developed 2 years ago by researchers at the U.S. Food and Drug Administration and the National Cancer Institute relied solely on the pattern generated by mass spectrometry analysis to distinguish between serum samples from healthy women and those with ovarian cancer.
In early studies, the technique enabled researchers to diagnose patients without having to know what proteins differ between the sample types. Now, however, the team reported in March at the annual meeting of the American Association for Cancer Research in Orlando that they have modified their approach and have started identifying the proteins that underlie the mass spectrometry pattern.
As blood flows through capillaries, tissues, and vessels, it picks up small proteins and protein fragments. Most of these nonblood peptides should be cleared by the kidney within a few minutes. However, based on mathematical modeling, Arpita Mehta, a student at Tufts University School of Medicine and a Howard Hughes Medical Institute research fellow in Boston, deduced that most of the peptides stick to large carrier proteins, like albumin, rather than floating free in the serum.
Therefore, to learn what proteins account for the peaks in the mass spectrometry analysis, Mehta isolated the albumin serum fraction from 127 unaffected women and 115 women with ovarian cancer, including 31 with stage I disease. She used these samples to identify a diagnostic proteomic pattern, much like the one NCIs Lance Liotta, M.D., Ph.D., and FDAs Emanuel Petricoin, Ph.D., had previously identified in whole serum. By focusing on the albumin carrier and its binders, the scientists improved their ability to detect stage I ovarian cancer. But rather than stopping with that diagnostic pattern, as the group has previously done, Mehta sequenced candidate biomarkers from discriminating ion peaks in the mass spectrometry sample. Each peak consists of numerous proteins, providing her with a substantial amount of material.
With the new method, Mehta, who did this research while working with the NCIFDA Clinical Proteomics Program, and colleagues have identified more than 800 proteins that are bound to the albumin carrier protein in the blood. Nearly three-quarters of these have not been found in blood before. They fall into numerous functional categories, including transcription factors, motor proteins, cell adhesion molecules, and proteins involved in apoptosis. Half of the proteins are of unknown function. The scientists have thus far sequenced 223 of the proteins that were differentially expressed in patients with stage I ovarian cancer relative to both stage III disease and high-risk controls.
When asked why the team has moved from pattern-based diagnostics to identifying proteins, Liotta said that it was simply the natural progression of the project. "This is like CA125; it was just a band on a gel" when people started using it as a marker for ovarian cancer. "In a year or so, we will be looking at labeled, known peaks in the pattern rather than just unknown ion peaks," he said.
Related News Article in JNCI
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