Given the stakes, a cautious approach makes sense. In fact, Correlogic, which has advanced its technology much more aggressively than the Eastern Virginia group, suffered a critical setback last winter. In September 2003, Correlogic announced at the annual meeting of the Ovarian Cancer National Alliance, a patient advocacy group, that OvaCheck would be on the market early in 2004. But in February, marketing plans went on hold when the FDA notified Correlogic and its two partners that the test might need regulatory approval-something not usually required of diagnostic tests marketed by clinical laboratories. Now the company and the FDA are working out a plan for moving forward.
The biggest mistake was to announce that you have a blood test,” says Eastern Virginia’s Semmes, who notes that Correlogic hadn’t even finalized its diagnostic pattern, at least in published form, at the time it made the announcement. “That claim, I think, hurt the field tremendously.” Even Petricoin and Liotta have distanced themselves from the test they helped originate.
The field must also cope with a scientific backlash against the whole idea of protein pattern diagnostics. Eleftherios Diamandis, a cancer expert at the University of Toronto in Ontario, calls the original Lancet ovarian-cancer paper “complete junk.” Diamandis contends that the patterns don’t actually represent proteins produced by cancer cells. “The technology will fail, because the molecules they monitor are not the correct ones,” says Diamandis. “I don’t think mass spectrometry, the way they perform it, is sensitive enough.” Instead, he urges, identify the proteins behind the peaks first, to make sure they’re really cancer proteins, and then develop standard tests to detect them. “Then we can put them all together, and we can make a reasonably good clinical diagnosis,” Diamandis says.
Petricoin firmly believes that the instruments are following proteins from cancer but concedes that proof can come only from rigorous trials. “The only way to prove it’s real or not is by validation, like any biomarker,” he says. The effort is worth it, he adds, because generating patterns is relatively simple, while identifying proteins and translating that knowledge into a useful lab test could take years, even before clinical trials. “The debate about whether or not it’s critical to identify the particular proteins or other molecules that make up a pattern, that’s [arguing] how many angels dance on the head of a pin,” agrees Levine. “If what you can do in the near term is develop diagnostics that will save lives, to me that’s the beginning of the end of the discussion.”