BCRP 2012 Investigator Vignette

Title: Advancing Our Understanding of Basal-Like, Luminal A, and Luminal B Breast Cancers

Investigator: Christopher Li, MD, PhD; Fred Hutchinson Cancer Research Center

So the DoD Collaborative Innovators Award that we were recently funded for is a collaboration with Dr. Arul Chinnaiyan at the University of Michigan. And so that is the mechanism that pairs people who either receive an Era of Hope Scholar Award or an Innovator Award from the DoD program and provides funding for a new partnership between two people who have been funded through either of those mechanisms.

So I have had this ongoing interest in looking at different subtypes of breast cancer, and so since the time that my original DoD grant was funded, there has been greater molecular characterization of breast cancer subtypes. And one that is of particular interest is a so- called "triple negative" type of breast cancer which is a much more aggressive form of the disease, occurs more commonly among young women, and also among African-American and Hispanic women.

And so our plan for this study is to enroll over 1,000 women with triple negative breast cancer. So it'll be the largest single study of triple negative breast cancer to date. And we'll also have a control group as well as some other more common breast cancer subtypes will also be represented in this particular study. We'll be collecting tumor tissue samples from the women and so we will be sending those samples to Dr. Chinnaiyan's lab where he will do a variety of different sorts of molecular work on these samples. And using this, what Dr. Chinnaiyan refers to as Integrative Sequencing Strategy, we will be able to comprehensively characterize the mutational landscape of these three different types of breast cancer. Part of the work is based on extracting DNA from the tumor tissue itself, to look at that tumor genome, and to look at changes that are happening across the different types of breast cancer. So we will do that across the genome as well as focusing on the tumor exome, which is the part of the genome that's coded. And so that will be done and then that will lead us to be able to identify structural rearrangement of genes looking at copy number, alterations, as well as looking at point mutations and insertions and deletions or indels.

And then we will also do some extraction of RNA so that we can evaluate the transcriptome and how that also varies across the different breast cancer subtypes. And so again we'll be able to look at point mutations and indels as well as looking at gene expression, again across the three different breast cancer subtypes that we'll be looking at. And so when we think about the potential impact that we hope to have with this particular study, our first aim is to identify risk factors. And so if we can identify potentially modifiable risk factors, whether it might be alcohol use, or obesity, or smoking, or use of particular medications, that could afford us potential opportunities for prevention of these types of breast cancer.

The second way that we could have potential impact is if we can develop targeted screening programs for women that we can identify as being at high risk for these tumors. So some of these risk factors might not be modifiable, things like family history or pregnancy history, reproductive history, but they could add importantly to a risk prediction model and enable us to identify women who are at high risk for these cancers. And if we can do that, there's a potential to reduce both morbidity and mortality associated with them.

The third way that we could have impact is by characterizing etiologic pathways, the biological mechanisms that are underlying the different types of breast cancer that we're looking at. It could point to new treatment or prevention strategies if we can identify particular molecular targets that would be suitable, or potentially druggable, for new treatments; that could be another way of realizing impact.

And then another component of the study is to look at predictors of recurrence among these patients who we know that many of these women...have a higher risk of having their breast cancer recur. But not all of them will have a breast cancer recurrence. So if we can identity both the epidemiologic and clinical factors as well as the molecular characteristics of their tumor that are predictive of recurrence, that could lead them to make different choices with respect to how aggressive a treatment they pick or how frequently they're following up with mammography or whatever other sort of follow-up they might require.

For our project there are certainly innovative aspects to this study in terms of its large sample size, its characterization of these cancers with a depth using Dr. Chinnaiyan's platforms that hasn't really been seen yet. And so I think in that way it will really push/advance our understanding of this type of cancer. But in the end we also have a strong emphasis on impact in terms of how can we prevent this disease, how can we detect it earlier, and how can we do better with respect to survivorship.