Molecular fingerprints  pg. 5

Imaging mass spectrometry of a human brain tumor that had been grown in a mouse reveals a high concentration of a number of specific proteins in the fast-growing edge of the tumor, including thymosin beta-4 (d). This suggests that these proteins may be important in tumor spread.
Illustration by Richard Caprioli, Ph.D., and his colleagues and previously published in Nature Medicine.
© 2001 Nature Publishing Group.
Lance Liotta, Ph.D., and his colleagues at the National Cancer Institute already had developed a microscope technique for teasing apart normal cells from their cancerous neighbors with the help of a laser. The cancer cells were then split open, and their contents poured onto a “protein chip,” a glass slide lined with “bait” molecules to which the cellular proteins stuck.

Extraneous material was washed away, and the slides were put into a mass spectrometer. As a first step, the slide was zapped with a laser, giving the proteins an electrical charge and spinning them off into a vacuum chamber toward an oppositely charged electrode. Their molecular weight was determined by the time it took them to get there.

The mass spectrometer then spit out a spectrum showing the molecular weights of all of the proteins and protein fragments. Dozens of experiments revealed that different cancer cells had unique spectra, or patterns of proteins, and thus potentially could be identified by their “molecular fingerprints.”

Using these techniques, the researchers are analyzing biopsies of cancerous tissue removed from patients before and after treatment to see if they can predict, from the protein patterns, which patients are likely to respond to specific drugs. The hope is that doctors one day will be able to “tailor” treatments to individual patients, while avoiding—in advance -- therapies that won’t work.

The researchers also began testing the serum, the clear liquid part of the blood from cancer patients, to see if they could detect the characteristic protein patterns without actually removing any cancerous tissue.

In February 2002, they reported their first success. With the help of pattern-recognition computer software developed by scientists at Correlogic Systems in Bethesda, Md., the government researchers found unique patterns of five proteins in serum that could detect ovarian cancer with near-100 percent accuracy.

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