A Better Way To Classify Breast Cancers

Researchers at Duke University believe they have developed a new statistical approach that can better classifying breast cancers based on profiles of their gene expression. Using a technique called "DNA microarray," they were able to analyze the activity of genes in breast tumor samples.

Writing in the Proceedings of the National Academy of Sciences, Dr. Joseph Nevins and colleagues reported that they could determine the potential role of new research tools using DNA microarrays to better assess the true estrogen receptor status of a tumor.

Together with axillary lymph node status, these are two of the most important prognostic factors to help predict the risk of future recurrence in a woman with a new diagnosis of early stage breast cancer.

Tumors whose cells show the presence of estrogen receptors are more likely to spread aggressively, as they respond to growth-inducing estrogen and progesterone. Also, the ability to predict whether breast tumors either have spread to lymph nodes, or have the potential to do so, constitutes the single most important risk factor in the metastasis of the cancer, they noted.

While their findings are preliminary and the approach new, Nevins said their technique will eventually lead to new diagnostic tests that can predict the status of tumors with considerable precision, enabling improved diagnosis and treatment.

"This technique goes beyond the standard practice of a pathologist visually examining a tumor and deciding on treatment and outcomes based on that examination," Nevins said. "It affords the opportunity to diagnose tumors with much greater detail than is now possible."

A DNA microarray-also known as a "gene chip"-allows researchers to examine thousands of genes from a single tumor sample. In using the DNA microarray to measure gene activity, the scientists extract messenger RNA (mRNA) from each of the tumors, enabling them to "read out" which genes are actively expressed in which tumor.

The researchers analyzed the gene expression profiles of 49 tumor samples previously tested to be either positive or negative for estrogen receptors. The subsequent DNA microarray analyses were able to confirm the estrogen receptor status of the tumors with remarkable precision, Nevins said.

"The determination of estrogen receptor status is an important aspect of breast cancer diagnosis because of its role in promoting tumor growth," Nevins explained.

"Although an analysis for estrogen receptor can be done now, the use of gene expression analysis provides much more detailed information about the nature of estrogen receptor status in these tumors," he added.

Their study also reported the results of gene profiling of breast tumors to predict their lymph node involvement. In their profiling, the scientists compared tumors that had spread to lymph nodes at the time of diagnosis to those that had not. Their new technique was able to classify tumor lymph node status, although with less accuracy than that of the estrogen receptor analysis.

According to Nevins, DNA microarray analysis can be compared to examining the individual pixels of a digital photo rather than only being able to view the overall scene. Instead of examining a tumor under a microscope, physicians will soon have the technology to examine the individual genes of a tumor, he said.

SOURCES:
Proceedings of the National Academy of Sciences, September 25, 2001; 98:11462-11467
Duke University Medical Center (www.mc.duke.edu)

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