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FeaturesNovember 29, 2001

BETHESDA, Md. -- In a crowded Food and Drug Administration laboratory, a scientist fires a miniature laser at cells from a cancer patient, a purple blast that captures normal, precancerous and tumor cells. This microscopic freeze-frame is key to a new experiment: tracking the chain reactions of proteins that fuel cancer before, during and after each patient is treated...

By Lauran Neegaard, The Associated Press

BETHESDA, Md. -- In a crowded Food and Drug Administration laboratory, a scientist fires a miniature laser at cells from a cancer patient, a purple blast that captures normal, precancerous and tumor cells.

This microscopic freeze-frame is key to a new experiment: tracking the chain reactions of proteins that fuel cancer before, during and after each patient is treated.

The hope is that doctors one day could tell in an instant the best chemotherapy for each patient, when one treatment is about to fail and it's time to switch, or when a relapse is near -- merely by looking at the "protein fingerprint" inside patients' cells.

By tracking how patterns of proteins change, "you get almost the story of cancer in this patient," explains FDA microbiologist Emanuel Petricoin, who co-directs the joint FDA-National Cancer Institute research program.

It's called proteomics, the study of all proteins in living cells. Biotechnology companies are using it in a quest to discover disease-causing proteins and create drugs that disable them.

But the FDA-NCI collaboration marks the first time proteomics is being used in clinical trials -- a step toward using proteins to guide real-world treatment and diagnosis, not just hunt new drugs.

Today, the only way to know if cancer treatment is working is to "wait and see in six months, and hope," says NCI's Dr. Lance Liotta. If proteomics works, "we're not doing that ever again."

It's a highly unusual program for the FDA, known for regulating therapies, not creating them.

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Together, Petricoin and Liotta have discovered more than 140 proteins that change as cancers of the breast, ovary, prostate and esophagus grow, making them new targets for treatment and earlier diagnosis.

More important, Liotta says the cancer institute needed FDA's untapped expertise in how drugs work, and why so many fail, to spur proteomics in ways industry may not push, such as customizing therapy so that patients get the most effective therapy at the lowest, safest dose possible.

Genes contain the instructions that create proteins, molecules that do the body's work by directing cells' action. A mutated gene can create an abnormal protein, setting off a chain reaction that ends in disease.

Many drugs target single abnormal proteins. But proteins form networks, almost like a circuit board, that direct different cells. Those patterns can fluctuate minute-to-minute, depending on what medications or other compounds affect the proteins. And with cancer, a drug targeting just one protein may help some patients -- but other times tumors just reroute themselves along the protein network to evade treatment.

"Because everything is hooked up in circuits, it gives cancer cells the advantage, a fantastic advantage," Liotta says.

Enter the FDA-NCI proteomics program.

Several hundred patients, mostly ovarian cancer patients, enrolled in various treatment studies at the National Institutes of Health's hospital will undergo additional biopsies before, during and after their therapy.

First, Liotta's laboratory created a special laser microscope to extract cells -- normal, premalignant and invasive cancer -- from that biopsied tissue. Unlike traditional methods that yield a mishmash of proteins, this "laser capture microdissection" isolates pure cells and, in seconds, transfers them to a special film that preserves the patterns proteins make as normal cells turn cancerous.

Then, using measures of molecular weight, Petricoin developed a way to tell, in minutes, what proteins are present in that snapshot, and in what strengths. The result looks like a bar code, a pattern that is the unique fingerprint for each patient's cancer.

Now the challenge: Track how each patient's protein patterns change as a result of different therapies. Those changes should make clear if the patient is responding or needs to switch therapies.

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