Magazine article Science News

Ominous Signals: Genes May Identify the Worst Breast Cancers. (This Week)

Magazine article Science News

Ominous Signals: Genes May Identify the Worst Breast Cancers. (This Week)

Article excerpt

Some women with breast cancer respond well to treatment while others succumb to the disease, even when the cancer in both cases appears to have been caught early and was treated similarly. A growing pool of evidence suggests that the genetic nuances of tumor cells account for the contrasting outcomes.

To turn those genetic traits to medical advantage, several research groups have begun scanning DNA in breast-tumor cells to determine which of thousands of genes are most or least active in aggressive cancers. A U.S.-Dutch team doing such gene profiling reports in the Jan. 31 Nature that certain patterns of activity crop up more frequently in the most deadly breast cancers--those that spread beyond the breast--than in cancers that remain in remission after initial treatment.

At present, physicians derive a breast cancer prognosis from the tumor's size, the extent of its spread, the degree to which the tumor cells differ from normal cells, molecular characteristics of the tumor cells, and the patient's age. Tumor removal and radiation therapy cure most women whose cancer is confined to the breast. Nonetheless, one-fourth of such women subsequently have cancer crop up elsewhere, says Stephen P. Ethier, a molecular biologist at the University of Michigan School of Medicine in Ann Arbor.

To obtain genetic clues to this risk, the researchers analyzed samples of 78 breast tumors that had been surgically removed from women. All the patients had breast cancer that was confined to the breast at the time of diagnosis. Of these, 34 women had cancer arise outside the breast within 5 years.

Using microarray analysis--a lab technology that reveals activity in individual genes--the researchers scanned roughly 25,000 genes in the tumor cells. Of the genes, 4,968 showed up as either especially busy or sluggish in at least three tumors.

Next, the researchers used a computer to look for patterns of gene overactivity or underactivity associated with aggressive tumors. …

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