Grand Rounds: Breast Cancer Genomics

November 20, 2007

Bellevue AmphitheaterCommentary by Jonathan Willner MD, PGY-2

This week’s Medicine Grand Rounds speaker was Lisa Carey, MD, Associate Professor in Hematology/Oncology at the University of North Carolina and Medical Director of the UNC Breast Center.  Much of Dr. Carey’s research focuses on how an understanding of breast cancer genomics may tailor clinical therapy.

While the incidence of breast cancer has plateaued over the past few years, there has been a decline in the number of breast cancer deaths. The reason is thought to be two-fold: improved screening and more effective medical therapy.  As treatment has improved, so too has the variability in choice and duration of therapy. However our ability to personalize adjuvant therapy so that women are receiving only the drugs they need is limited; most women are either over or under-treated.

The traditional model of cancer development holds that malignancy develops as a linear progression of genetic “hits:” successive loss of genetic integrity over time allowing for unchecked proliferation and spread of malignant cells. The biologic model, by contrast, argues that inborn traits and biologic variability sum to create a cancer subtype, which is later evidenced by the phenotypic variability we see in disease progression and treatment response.  The biologic model has been largely informed by genomics, the study of large-scale genetic mapping, as its tool for defining breast cancer subtypes. Analysis of approximately 8000 genes via microarray has elucidated a gene sets that reliably identify several breast cancer subtypes. These subtypes are definable early in the course of disease, and are present both after chemotherapy and in metastatic disease.  Dr. Carey’s work has focused on the ‘basal-like’ subtype in particular, so named because of its high density of genes coding for EGFR, basal cytokeratins, and other basal proteins. The basal-like subtype also has typically low HER2 and ER/PR expression, and is very proliferative.

Breast cancer subtyping being increasing used to predict the clinicopathologic characteristics of a patient’s disease. Population-based studies, such as the Carolina Breast Cancer Study, have found a preponderance of the basal-like subtype among pre-menopausal, African-American women. Patients that carry germline BRCA1 mutations also tend to develop the basal-like subtype. Somewhat surprisingly, traditional breast cancer risk factors (degree of parity or OCP use, for example) fail to predict ER-negative subtypes, and some factors may actually be protective in some subtypes.. Such variability has led researchers to try to identify particular gene profiles that can be used to predict outcome across all subtypes.  From these studies, the basal-like subtype has emerged as the subtype most powerfully predictive of clinical progression and outcome.

Breast cancer relapse is known to be heterogenous. While ER-positive breast cancer tends to maintain a low-but-constant relapse rate, the basal-like subtype typically evinces a high early rate followed by a rapid decline in number of relapses. This may suggest why these two subtypes have different responses to chemotherapy: chemotherapy tends to decrease early relapses and is more effective in ER-negative subtypes like the basal-like subtype; ERER-positive breast cancer has a constant risk of  relapse over many years and is less impacted by chemotherapy.

Lastly, though genomic subtyping has shown promise as a model for predicting clinical outcome, it has yet to prove itself as a tool for choice of medical therapy. A number of agents have shown promise in the treatment of basal-like breast cancer, but it has not yet been proven that chemotherapy regimen  can be tailored on the basis of genetic subtyping. We do not yet have known targeted drugs for this subtype, which is the subject of active study.   Future efforts will work to clarify risk factors by breast cancer subtype, which may inform either directed lifestyle or chemopreventive strategies, improving chemotherapy, and identifying targeted drugs to effectively treat with a minimum of toxicity.

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