Cell Insights May Predict Breast Cancer's Spread

Key biomarkers could point to women at higher risk, study suggests

By Carolyn Colwell
HealthDay Reporter

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FRIDAY, Nov. 16 (HealthDay News) -- U.S. researchers believe they're on the way to solving a major question about breast cancer: Which women have a type of lesion in their breast duct that will progress to invasive disease?

"It's an exciting step forward -- people have been trying to get traction on this big clinical problem for about 40 years, and this is a big crack in the door," said lead researcher Thea Tlsty, a professor of pathology at the University of California, San Francisco.

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Ductal carcinoma in situ (DCIS), as this type of lesion is officially known, is diagnosed in about 47,000 American women every year, according to the U.S. National Cancer Institute. To prevent its recurrence as invasive breast cancer, DCIS generally is treated by lumpectomy alone (approximately 25 percent of cases) or lumpectomy with adjunctive treatments such as radiation, chemotherapy, and/or hormones (approximately 40 percent).

In about 25 percent of cases, complete mastectomies are performed. Less than an estimated 5 percent of women choose "watchful waiting" in lieu of a surgical intervention, Tlsty said.

But doctors are still confronted with a guessing game when it comes to predicting those patients at highest risk for recurrence, Tlsty said. "Only about 12 to 15 percent of women diagnosed with DCIS are going to have a future invasive cancer, and all the others won't. Up until now, the problem was that we couldn't distinguish the 12 to 15 percent from those who were not [at risk]," explained Tlsty.

Consequently, some women unknowingly are overtreated by having a mastectomy, and others are undertreated if they chose a course of watchful waiting rather than surgical intervention, Tlsty added.

In their pilot study, published in the November issue of Cancer Cell, the UCSF team looked at how a collection of biomarkers, including molecules called p16 and ki67, interact to predict invasive tumors, she explained.

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