Mass spec diagnostic developed for ovarian cancer

Mass spectrometry is helping Melbourne researchers develop a diagnostic test for the early detection of ovarian cancer.

Currently, the insidious disease tends to be detected in the later stages when prognosis is poor. But by developing a kind of protein marker "fingerprinting" system, researchers at the Peter MacCallum Cancer Institute hope to ultimately create a population screen similar to the existing pap smear tests for cervical cancer.

Head of mass spectrometry Dr Ken Mitchelhill said that if the cancer was detected in the later stages, the five-year survival rate was about 20 per cent.

But if it could be picked up in stage one, often before any symptoms began to manifest, survival was 95 per cent and above.

Ovarian cancer cells release specific proteins into blood, which can be used to identify patients with the disease.

Mitchelhill said current screening, which looked for levels of certain proteins in a woman's blood, were not very good because the test carried a positive predictive value of 20 per cent.

This meant that for every 100 women screened, 10 would test positive to ovarian cancer but only two would truly have the disease, often leading to unnecessary surgery.

"In the past, people have tried to find individual proteins indicative of ovarian cancer," Mitchelhill said.

"The idea here is not to worry about the identification of molecules, but to generate a sophisticated pattern or fingerprint that can be used to detect the cancer in the earliest stages."

To do so, the Peter Mac group is using an API4000 mass spectrometer, understood to be the only one of its kind in the southern hemisphere.

Using the institute's established tissue bank, the researchers will run serum samples from 50 confirmed ovarian cancer patients and 50 controls who may have presented for surgery but were found not to have cancer.

Mitchelhill said between 50,000 to 100,000 proteins could be detected and their levels measured using the mass spectrometer, with the data from the patient groups analysed using neural network computing.

He said the software was capable of "sophisticated artificial learning", enabling it to distinguish between the cancer and non-cancer groups and to recognise patterns that could be used to detect the disease early.

The first study is set to begin in the next few months, followed by a second project as part of the Australian Ovarian Cancer Study that will involve 5000 patients and 5000 controls.

Mitchelhill said the Peter Mac would also take part in a National Institutes of Health high-risk ovarian cancer study expected to begin in the next 12 months.

He said he hoped a diagnostic test would be ready for a pilot patient trial within three years.

"The first stage of that would be in high-risk women with a family history or who have a gene mutation known to be linked to ovarian cancer," he said. "Then we would hope that we could develop the test to be sufficiently efficient that it could be applied as a population screen."

The Melbourne study builds on work published in The Lancet in February, in which a United States group used mass spectrometry to develop a screen that carried a 94 per cent positive predictive value.

Mitchelhill said the instrumentation his group will use was slightly different and predicted the local researchers could match or even better the results produced in the US.

Further reading:

THE LANCET, Vol 359, February 16, 2002: Use of proteomic patterns in serum to identify ovarian cancer, Emanuel F Petricoin III, Ali M Ardekani, Ben A Hitt, Peter J Levine, Vincent A Fusaro, Seth M Steinberg, Gordon B Mills, Charles Simone, David A Fishman, Elise C Kohn, Lance A Liotta