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Women may be able to reduce breast cancer risk predicted by their genes

Date:
May 26, 2016
Source:
Johns Hopkins Bloomberg School of Public Health
Summary:
Women with a high risk of developing breast cancer based on family history and genetic risk can still reduce the chance they will develop the disease in their lifetimes by following a healthy lifestyle, new research suggests.
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Women with a high risk of developing breast cancer based on family history and genetic risk can still reduce the chance they will develop the disease in their lifetimes by following a healthy lifestyle, new research led by the Johns Hopkins Bloomberg School of Public Health suggests.

White women who are at high risk but who had a low body mass index (a marker for obesity), who did not drink or smoke and who did not use hormone replacement therapy, had roughly the same risk as an average white women in United States, the researchers found. The average chance that a 30-year-old, white woman will develop breast cancer before she is 80 is about 11 percent.

The researchers found that roughly 30 percent of breast cancer cases could be prevented by modifying known risk factors -- say, by drinking less alcohol, losing weight and not taking hormone replacement therapy. More importantly, the study found that a larger fraction of total preventable cases would occur among women at higher levels because of genetic risk factors, family history and a few other factors that cannot be modified.

The findings, published May 26 in JAMA Oncology, are a first step in understanding how advances in the field of genetics can be used for developing precision prevention strategies to help women improve their odds of avoiding breast cancer. Breast cancer remains the most common form of malignancy diagnosed in women in western developed countries, with an estimated 232,000 new cases diagnosed in the United States in 2014. Roughly 40,000 women die in the United States from breast cancer each year.

The findings could be particularly useful as the price of genetic testing continues to fall and more women are able to afford the tests, which typically are not covered by insurance. They may also help scientists develop better guidelines for when and how frequently women should be screened for breast cancer, a calculation that is currently based on age, but that could be based on individual risk factors for each individual woman.

"People think that their genetic risk for developing cancer is set in stone," says the study's senior author Nilanjan Chatterjee, PhD, a Bloomberg Distinguished Professor in the Department of Biostatistics at the Bloomberg School. "While you can't change your genes, this study tells us even people who are at high genetic risk can change their health outlook by making better lifestyle choices such as eating right, exercising and quitting smoking."

Chatterjee and his colleagues from more than a dozen institutions around the world developed a model predicting risk of breast cancer by analyzing records on more than 17,000 women with breast cancer and nearly 20,000 women without the disease from the Breast and Prostate Cancer Cohort Consortium and about 6,000 women participating in the 2010 National Health Interview Study. The researchers combined individual-level data on risk factors such as age, weight and smoking status with data on almost 100 common gene variations, each of which are known to have a modest association with breast cancer but in combination they can lead to substantially elevated risk. They further combined this information with population incidence rates from the National Cancer Institute-Surveillance, Epidemiology and End Results Program. The findings are currently applicable only to white women because further studies are needed to understand the association of the genetic variants with risk of breast cancer for other ethnic groups.

The common gene variations studied by the researchers are quite different from the well known rare mutations in genes like BRCA1 and BRCA2, where having a single variant can mean a very high risk of developing breast cancer.

Chatterjee says the findings may add to the process of creating better screening models for breast cancer. Current recommendations in the U.S. do not call for routine mammograms for breast cancer until the age of 50, though previous recommendations suggested age 40.

While getting older is the No. 1 risk factor for developing breast cancer, other factors -- such as family history -- already come into play and more specific genetic risks may one day prove to also play a role. The model shows that, for example, 16 percent of 40-year-old women in the population had the risk of an average 50-year-old woman and thus possibly could benefit by screening earlier. At the same time, 32 percent of 50 year olds had the risk of 40 year olds and they should at least be carefully counseled so that they understand there may be harm associated with screening those at low risk of developing the disease.

While mammograms can detect early-stage breast cancers, there are risks of false-positive results which can add potentially unnecessary pain, cost and distress. So finding a way to screen those at the highest risk more often -- and those at lower risk less often -- could be beneficial. "We aren't saying there will be less screening, just smarter screening," Chatterjee says.

The model is still several years from being ready for routine medical use. First, Chatterjee says, the model needs to be validated in other studies. Second, he says, the cost of widespread genetic testing, while falling precipitously over the last decade, is still a little too high. But he sees the costs continuing to fall in coming years to a level where such testing can become commonplace. Also, he says, a model needs to be developed for other ethnic populations and for specific subtypes of breast cancer which may have different causes and prognostic outlooks.

Chatterjee says he hopes that once women understand that their genes do not completely predict their cancer destiny, they will work even harder to make lifestyle changes that can potentially reduce the risk they will develop the deadly disease.

"Everyone should be doing the right things to stay healthy but motivating people is often hard," he says. "These findings may be able to help people better understand the benefits of a healthy lifestyle at a more individualized level."


Story Source:

Materials provided by Johns Hopkins Bloomberg School of Public Health. Note: Content may be edited for style and length.


Journal Reference:

  1. Paige Maas, Myrto Barrdahl, Amit D. Joshi, Paul L. Auer, Mia M. Gaudet, Roger L. Milne, Fredrick R. Schumacher, William F. Anderson, David Check, Subham Chattopadhyay, Laura Baglietto, Christine D. Berg, Stephen J. Chanock, David G. Cox, Jonine D. Figueroa, Mitchell H. Gail, Barry I. Graubard, Christopher A. Haiman, Susan E. Hankinson, Robert N. Hoover, Claudine Isaacs, Laurence N. Kolonel, Loic Le Marchand, I-Min Lee, Sara Lindström, Kim Overvad, Isabelle Romieu, Maria-Jose Sanchez, Melissa C. Southey, Daniel O. Stram, Rosario Tumino, Tyler J. VanderWeele, Walter C. Willett, Shumin Zhang, Julie E. Buring, Federico Canzian, Susan M. Gapstur, Brian E. Henderson, David J. Hunter, Graham G Giles, Ross L. Prentice, Regina G. Ziegler, Peter Kraft, Montse Garcia-Closas, Nilanjan Chatterjee. Breast Cancer Risk From Modifiable and Nonmodifiable Risk Factors Among White Women in the United States. JAMA Oncology, 2016; DOI: 10.1001/jamaoncol.2016.1025

Cite This Page:

Johns Hopkins Bloomberg School of Public Health. "Women may be able to reduce breast cancer risk predicted by their genes." ScienceDaily. ScienceDaily, 26 May 2016. <www.sciencedaily.com/releases/2016/05/160526120330.htm>.
Johns Hopkins Bloomberg School of Public Health. (2016, May 26). Women may be able to reduce breast cancer risk predicted by their genes. ScienceDaily. Retrieved December 26, 2024 from www.sciencedaily.com/releases/2016/05/160526120330.htm
Johns Hopkins Bloomberg School of Public Health. "Women may be able to reduce breast cancer risk predicted by their genes." ScienceDaily. www.sciencedaily.com/releases/2016/05/160526120330.htm (accessed December 26, 2024).

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