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New test can predict spread of breast cancer

May help to reduce over- and under-treatment of the disease
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Scientists at MIT, the Albert Einstein College of Medicine and Weill Cornell Medical School have developed a test that could help doctors precisely identify which breast cancer patients should receive aggressive therapy, thereby sparing many women at low risk for metastatic disease from undergoing unnecessary and potentially dangerous treatment.

The researchers, including MIT biology professor Frank Gertler, developed the test based on an earlier finding that the co-mingling of three cell types can predict whether localized breast cancer will metastasize, or spread throughout the body. The findings are published March 24 in the online version of Clinical Cancer Research.

Above: MIT biology professor Frank Gertler discusses the Mena protein, and a test developed with two colleagues that could help doctors precisely identify which breast cancer patients should receive aggressive therapy.

"This is the first marker that could reliably predict metastatic outcome in a case-controlled study," says study co-author John S. Condeelis, professor and co-chair of anatomy and structural biology at Yeshiva University's Albert Einstein College of Medicine. "It could dramatically change the way we approach the care of women with breast cancer."

Breast cancer is the most common cancer among women in the United States. Last year, approximately 182,000 women were diagnosed with breast cancer and more than 40,000 died from the disease.

Surgery is the first line of defense for most patients with breast cancer. For patients with higher-grade tumors, additional treatment with chemotherapy or radiation is typically recommended to decrease the risk that the disease will spread. However, studies show that only 40 percent of these patients actually develop metastatic disease.

"What this means is that most of these patients are unnecessarily exposed to chemotherapy or radiation, which can have significant side effects or even worsen the disease," says Condeelis.

The blood test could become available once the method is validated in a study of a large population of breast cancer patients, which will take about two years, according to the researchers.

Recently, Condeelis found that breast cancer spreads only when a specific trio of cells are present together in the same microanatomic site: an endothelial cell (a type of cell that lines the blood vessels), a perivascular macrophage (a type of immune cell found near blood vessels), and a tumor cell that produces the protein Mena.

In a paper published in Developmental Cell in December, Condeelis and Gertler, who is a member of the David H. Koch Institute for Integrative Cancer Research at MIT, showed that Mena dramatically enhances a cancer cell's invasiveness.

"It's an important mechanism by which the cell gains the ability to become invasive and metastatic," says Gertler.

In the new Clinical Cancer Research study, the researchers defined a site with these three cell types as a tumor microenvironment of metastasis, or TMEM. Weill Cornell pathologists, aided by Einstein and MIT scientists, developed a tissue test to detect the presence and density of TMEMs. The test consists of a triple immunostain containing antibodies to the three cell types. A high number of TMEMs in a tissue sample means that the tumor is likely to metastasize or has already done so.

The immunostain was tested on breast tissue biopsy samples taken from 30 patients with advanced metastatic breast cancer and 30 patients with localized breast cancer, all of whom had been followed for at least five years. The resulting immunostains were evaluated by two pathologists who were not aware of the patients' clinical outcomes.

Their analysis confirmed that TMEM density was significantly higher in patients who had developed metastatic breast cancer than in those who had localized disease. For every 10-unit increase in TMEM density, the risk for metastatic disease doubled. The density of any of three TMEM components alone was not sufficient to predict clinical outcome.

Other authors of the paper include Brian D. Robinson, Gabriel L. Sica, Yi-Fang Liu and Joan G. Jones of Weill Cornell Medical College; and Thomas E. Rohan, professor of epidemiology and population health at Albert Einstein College of Medicine.

This story was adapted from a press release issued by Albert Einstein College of Medicine.

A version of this article appeared in MIT Tech Talk on April 1, 2009 (download PDF).

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