Predicting Response of Breast Cancer Therapy

A microarray can be used to predict the result of therapy for breast cancer according to the individual patient and prevent certain patients from having to undergo painful or unsuccessful therapies, according to researchers at the Karolinska Institute (Stockholm, Sweden).

The researchers analyzed tumor 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. By identifying patients whose tumors express these genes, they found they could predict which patients would not benefit from adjuvant therapy and thereby avoid giving patients therapies that might cause more harm than good.

The researchers analyzed 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 five years. The remaining 121 patients were defined as the "good prognosis” group. Gene expression was also used to separate patients who did well and did not have adjuvant therapy from those whose tumors failed to respond. An analysis of the genes expressed in the tumors 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. They found that using the expression patterns of the 64 identified genes gave better prediction rates than histologic grading, tumor stage, and age.

The findings were reported in the October 3, 2005, issue of Breast Cancer Research (http://breast-cancer-research.com), published online by BioMed Central.





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