Intrinsic subtype diagnosis accurately predicts breast cancer prognosis

NEW YORK (Reuters Health) - A gene expression-based risk model incorporating intrinsic subtypes of breast cancer accurately predicts prognosis and chemotherapy benefit, according to a report published online on February 9th by the Journal of Clinical Oncology.

Microarray and hierarchical clustering analysis have been used to define the intrinsic subtypes luminal A (LumA), luminal B (LumB), HER2-enriched, basal-like, and normal-like, Dr. Philip S. Bernard from the University of Utah, Salt Lake City, and colleagues explain.

The researchers studied the utility of these subtypes alone and as part of a risk-of-relapse predictor in breast cancer patients receiving no adjuvant systemic therapy and in breast cancer patients undergoing neoadjuvant chemotherapy.

The intrinsic subtypes showed significant effects on prognosis for relapse-free survival in untreated patients and when patients were stratified by estrogen-receptor status, the authors report.

Models that incorporated clinical variables with the intrinsic subtype were significantly better than either approach alone in predicting risk of relapse.

Among patients receiving neoadjuvant chemotherapy, intrinsic subtypes were the only variables that significantly predicted response to therapy, the researchers note.

"Diagnosis by intrinsic subtype adds significant prognostic and predictive information to standard parameters for patients with breast cancer," Dr. Bernard and colleagues conclude.

"The prognostic properties of the continuous risk score will be of value for the management of node-negative breast cancers," they add. "The subtypes and risk score can also be used to assess the likelihood of efficacy from neoadjuvant chemotherapy."

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