May 28, 2019
Ahead of the 2019 American Society of Clinical Oncology (ASCO) Annual Meeting, we are speaking with Harold J. Burstein, MD, PhD, of the Dana-Farber Cancer Institute and Harvard Medical School in Boston, about genomic profiling for estrogen receptor (ER)-positive breast cancer. Dr. Burstein will be speaking at an Education Session titled, “Genomic Profiling in ER-Positive Breast Cancer, From MINDACT to TAILORx,” on Monday, June 3, at the meeting, which is being held May 31–June 4 in Chicag .
Cancer Network: What prognostic genomic profiling panels are now approved to inform adjuvant therapy decision making for women with ER-positive breast cancer?
Dr. Burstein: There are several commercially available genomic assays that are used to help guide treatment decisions for women with ER-positive breast cancer. The most commonly used test is the Oncotype DX 21-gene recurrence score from Genomic Health. There are other assays as well, including the MammaPrint 70-gene assay and an assay from Nanostream called the intrinsic subtype assay. All of these are multigene assays built around patterns of gene expression within ER-positive breast cancers, and in very broad terms they help to classify tumors. For example, tumors could be scored as lower risk, which means they typically have a better prognosis and usually do not warrant chemotherapy, or as higher risk, meaning typically a less favorable prognosis that warrants chemotherapy in the early-stage setting.
Cancer Network: How many genes are represented in these different panels, and is there much overlap in the genes in the different panels?
Dr. Burstein: Interestingly, each one of the assays uses both different genes and a different number of genes. The total number ranges from 70 in the MammaPrint assay down to other tests, which are less widely used but use somewhere on the order of 5 to 10 genes. As I said, the most commonly used one is the 21-gene recurrence score. What’s interesting is that most of these assays rely on different genes that they analyze and yet they have tremendous overlap in terms of identifying tumors at either lower vs higher risk. The way I explain that to patients is that you can come up with a lot of decision rules to look at different features of something and classify it. So, for instance, if you were to say, “I want a decision rule to distinguish a horse from a cow,” you could say, “Well, if it has horns it’s a cow, if it has an utter it is a cow. And if it has a mane, it’s a horse, longer snout, longer bushier tail, it’s a horse.” The point is you can use all these different ways of analyzing different aspects of the same animal to come up with a very similar characterization and the same is true for classifying ER-positive breast cancer, you can use a lot of different genes to read out different aspects of the tumor that more or less broadly align with this lower, more favorable risk, which we often call luminal A, and the higher grade, higher score, greater risk, which we often call luminal B tumors.
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