image: UMass Amherst's Hankinson says current models are not as good as they need to be for predicting individual breast cancer risk. She wants to improve prediction so that a woman and her health care provider have a better sense of where she stands on the risk scale. view more
Credit: UMass Amherst
AMHERST, Mass. - Epidemiologist Susan Hankinson at the University of Massachusetts Amherst has received a five-year, $4.2 million grant from the National Cancer Institute to build upon and advance her research group's earlier work to identify and validate hormonal markers to better predict the risk of invasive breast cancer in postmenopausal women.
Hankinson, who was the principal investigator of the Nurses' Health Study (NHS) cohort at Brigham and Women's Hospital from 2006-11 and is now at UMass Amherst's School of Public Health and Health Sciences (SPHHS), says the investigation will take two directions, both related to recent findings that suggest measuring only "the classic estrogens" as risk biomarkers may miss "a sizeable component of estrogenic activity" also relevant to risk.
Hankinson says, "We want to improve breast cancer risk prediction so that a woman and her health care provider have a better sense as to where she stands on the risk scale. If a woman finds she is on the higher end of the risk scale, she can consider taking action such as lifestyle changes or whether to take one of the breast cancer preventive drugs. Unfortunately, current models are not as good as they need to be for predicting individualized risk. In this project we will both evaluate improvements in risk prediction, and collaborate with several other research groups to validate our findings."
The researchers, including SPHHS biostatistician Jing Qian, will analyze blood samples collected from thousands of NHS participants for associations with 27-hydroxycholesterol (27HC), an estrogen receptor modulator, and an estrogen bioassay in relation to breast cancer risk. They will also study the insulin pathway.
Hankinson says "In postmenopausal women there is some evidence that c-peptide, a reflection of insulin secretion, may increase proliferation and lead to subsequent breast cancer." Therefore, they will also evaluate several new aspects of the relationship between plasma c-peptide and breast cancer risk. "With 26 years of follow-up and two blood samples collected 10 years apart in a subset of women, we will evaluate the importance of timing of c-peptide exposure in breast carcinogenesis," the researchers state.
Breast cancer is the most commonly diagnosed malignancy among United States women, Hankinson points out. She recalls, "Some of my first papers on plasma hormones and breast cancer risk came out in the 1990s, and here we are making some progress, perhaps closing in on some biomarkers that could be really useful. It would be very nice to see improvement in the current individual risk prediction models being used today."
Using a prospective, nested case-control design, they will also analyze blood from among the 32,826 NHS participants who provided a sample in 1989-90 and, for 18,743 of these, a second sample in 1999-2000. This is to evaluate c-peptide, 27HC, as well as the estrogen bioassay that assesses estrogen pathway activation in relation to breast cancer risk.
She and colleagues hope this project, working from discovery of new hormonal biomarkers to practical application of well confirmed biomarkers in risk prediction models, will "add considerable insight into breast cancer etiology and ways to better identify high risk women who may benefit from risk reduction efforts, for example, chemoprevention."
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