In a study published in the journal Breast Cancer Research, researchers analysed tumour tissue samples and identified a group of 64 genes that can be used to predict a patient's response in the five years after adjuvant therapy for breast cancer. Identifying patients whose breast tumours express these genes could potentially be used to predict which patients would not benefit from adjuvant therapy, and avoid patients being given therapies with the potential of causing more harm than good.

A team of researchers led by Jonas Bergh from the Karolinska Institutet in Stockholm, Sweden, analysed the gene expression profiles of 159 breast cancer patients using DNA microarray analysis. From these samples they identified the genetic signatures shown by 38 patients who had a poor prognosis - defined as relapse or death from any cause within 5 years. The remaining 121 patients were defined as the 'good prognosis' group. The researchers also used gene expression profiling to separate patients who did well with and without adjuvant therapy, and those whose tumours failed to respond to treatment.

An analysis of the genes expressed in the tumours of all 159 patients showed that 64 genes were used to separate the patients with good and poor prognoses. The researchers then tested the predictive value of the group of 64 genes compared with three currently used clinical markers. Using the expression patterns of the 64 genes identified by the researchers gave significantly better (P=0.007) prediction rates than histological grading, tumour stage and age - which are all accepted prognostic markers for breast cancer.

The present lack of criteria to help tailor breast cancer treatment to individual patients indicates a need to develop new techniques for better prediction of how patients will respond to adjuvant treatments. The researchers suggest that the technique of DNA microarray analysis could be developed to help breast cancer patients who do not benefit from adjuvant therapy, and avoid painful unnecessary treatments and wastage of healthcare resources.

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According to Ie-Ming Shih, M.D., Ph.D., associate professor of pathology and oncology, who co-directs the laboratory with Wang, other gene typing methods can identify abnormalities within wide areas of the genome, but the tool used for this study, called digital karyotyping, is far more precise. "It's like narrowing down our search from the entire State of Maryland to a certain building in Baltimore City," he says.

In three of the seven cell lines, the scientists homed in on chromosome 11 after finding high levels of amplification in a region known for cancer-related genes. Further analysis of this region revealed that the Rsf-1 gene was overexpressed far more than 12 other genes in the same area.

Rsf-1 typically opens and closes the scaffolding structure of DNA, which acts as the gatekeeper to protein manufacturing. The Hopkins scientists say that when Rsf-1 is amplified, it may disturb this process and create more space for protein production of certain genes that may promote tumor growth.

"It's important for us to learn more about how Rsf-1 creates aggressive cancers in order to develop drugs that target it," says Wang. "But right now, we'll need to test larger samples to determine if Rsf-1 accurately predicts clinical outcome."

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