Putting the Genome to Work in Breast Cancer
Published Online: Thursday, October 18, 2012
Elaine R. Mardis, PhD, discusses genomic insights into resistance mechanisms in endocrine therapy.
It is a vision of the future that Elaine R. Mardis, PhD, a speaker at the 11th International Congress on the Future of Breast Cancer, not only anticipates but also helps to create.
Mardis is co-director of the Genome Institute, director of Technology Development, and professor of Genetics and Molecular Microbiology at Washington University School of Medicine in St. Louis, Missouri. The institute is among three large-scale sequencing centers that the National Institutes of Health has enlisted nationwide to join in developing The Cancer Genome Atlas.
One of the institute’s endeavors is to help build a database of human reference genome sequences, a more complete library of information than the initial Human Genome Project generated, which can be used to develop targeted therapies and as a comparison point for an individual patient’s genomic signature.
While that work continues, new sequencing technologies now in development are enabling researchers “to anticipate assembling that person’s genome as opposed to aligning it back to the human reference,” thus expanding their ability to understand what is happening with the patient’s chromosomes, said Mardis.
“It’s a brave new world out there right now, and I’m personally very excited about it because I love the technology aspects—it’s really powerful to see what the technology is going to be able to do,” she said.
In this interview, Mardis discussed clinical applications of genomic research on the near horizon.
OncologyLive: Your recent paper in Nature, “Whole-Genome Analysis Informs Breast Cancer Response to Aromatase Inhibition” [2012;486(7403):353-360],is one of the first genomic studies to demonstrate how this research can be applied in the clinical setting. You found 18 significantly mutated genes in the tumor samples. What is the clinical significance of this research?
Mardis: I was honored to recently have a publication in Nature with a large number of collaborators that studied sequencing samples from a clinical trial of aromatase inhibitors. Our overarching goal in this study was to begin to characterize the genomes of patients who were known, by virtue of the clinical trial parameters, to respond to the aromatase inhibitors compared with those who did not respond.
In essence, what we wanted to identify in these data were signatures from the genome that will help us predict which patients will or will not respond to aromatase inhibitors so that we can be more intelligent about our choices in deciding which patients to assign to this therapy versus other types of therapy (eg, surgery, chemoradiation, or other new targeted therapies).
We performed whole-genome sequencing of patients who were about equally stratified between those who did and did not respond based on a fundamental immunohistochemistry marker of Ki67, which provides a metric of tumor cell proliferation.
Some of the outcomes of this study, which focused on estrogen receptor-positive tumors, included new insights into genes that were not previously known to be commonly mutated in luminal-type cancers. In particular, we identified five new genes historically thought to be only involved in hematopoietic malignancies that were clearly highly mutated, and were contributing to the disease onset or were “drivers” of the disease. This was an important finding in terms of what we typically refer to as significantly mutated genes. These significantly mutated genes are genes that, by a variety of mathematical tests, are more commonly mutated than would be typically expected.
We also found that patients with TP53 mutation, high proliferation by Ki67, and luminal B-type tumors were the least likely patients to respond to aromatase inhibitors. By comparison, a new gene that was also identified in our study, MAP3K1, is commonly mutated in patients with luminal A-type tumors and a lower Ki67 proliferation index, and these were the patients who most commonly responded to the aromatase inhibitor therapy.
So, in essence, what we have from this study is the very beginning of a genomic signature that’s combined with conventional pathology markers, such as Ki67 and RNA subtyping, to identify the specific intrinsic subtype of the breast tumor, and to identify patients who are likely to respond before they’re assigned to aromatase inhibitor therapy.
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