Prosigna Breast Cancer Prognostic Gene Signature Assay

Overtreatment in health care wastes money and can sometimes cause more harm than good. NanoString’s Prosigna Breast Cancer Prognostic Gene Signature Assay, introduced in February 2013, brings more detailed prognostics right to the clinic, with the goal of sparing breast cancer patients from overly aggressive treatments.
NanoString’s Prosigna assay determines a patient’s risk of breast cancer recurrence by examining the gene expression profile of the patient’s tumor cells. Aleix Prat, a physician and researcher at Vall d´Hebron Institute of Oncology in Barcelona, uses the score to identify patients who might do fine without chemotherapy or radiation if they’ve responded well to endocrine therapy.
The assay is also useful in research because it can identify the true biological subtype of the tumor—the only test that can, Prat says. In addition, “it captures more biological information than the set of three to four pathology-based biomarkers currently used in the clinic.”
Brad Gray, the CEO of Seattle-based NanoString, says that other genomic tests can make similar assessments, but NanoString’s technology is simple enough to be used in the clinic, rather than sent to specialized labs. One kit sells for $2,000, but the instrument that performs the actual analysis, called the nCounter, runs about $250,000, at least in Europe. The company plans to introduce the assay in the United States in 2014, but isn’t yet saying what they’ll charge US customers. “There are a lot of opportunities to continue to expand the utility of the assay,” says Gray. “We think this is the first of a menu of diagnostic tests we hope to build on this system.”

MARDIS: This assay has been shown to outperform the clinical testing service from Oncotype DX because more women are characterized as having a high or low risk of recurrence, both of which are clinically informative, versus “medium” risk of recurrence, which is clinically indeterminate.

SCHADT: This test leverages the NanoString technology that can be run in any local lab, thus providing a path for this type of diagnostic to be run as part of existing laboratory workflows.
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