A total of 77 common genetic variants, known to be associated with breast cancer, have been combined into a single risk factor. It can improve the identification of women with an elevated risk of breast cancer. This factor, known as a polygenic risk score, was built from the genetic data of more than 67,000 women. The results of the research were published in the Journal of the National Cancer Institute (2015; doi:10.1093/jnci/dju397).
Recent large-scale genomic analyses have uncovered dozens of common genetic variants that are associated with breast cancer. Each variant, however, contributes only a tiny amount to a person’s overall risk of developing the disease. The polygenic risk score can be combined with traditional predictors of breast cancer risk such as breast density and family history to improve personalized estimates of breast cancer risk.
“This genetic risk factor adds valuable information to what we already know can affect a woman’s chances of developing breast cancer,” said study co-author Celine Vachon, PhD, an epidemiologist at Mayo Clinic in Rochester, Minnesota. “We are currently developing a test based on these results, and though it isn’t ready for clinical use yet, I think that within the next few years we will be using this approach for better personalized screening and prevention strategies for our patients.”
Scientists have known for decades that genetics can play a role in breast cancer. For example, inheriting a mutation in BRCA1 and BRCA2 genes greatly increase a woman’s risk of developing the disease, but these mutations are rare and account for less than 5% of all breast cancers. More common genetic variations known as single nucleotide polymorphisms (SNPs) also contribute to cancer susceptibility, but the individual contributions are too small to predict breast cancer risk.
In this study, researchers tested whether they could combine the effects of these individual SNPs into a single risk factor for breast cancer. The investigators essentially added up information on 77 SNPs from 33,673 breast cancer patients and 33,381 healthy subjects to derive the polygenic risk score.
They showed that the polygenic risk score could successfully place women into different categories of risk. Compared to women with an average polygenic risk score, women in the top 1% were three times more likely to develop breast cancer. In addition, women in the lowest 1% of the score were at a 70% lower risk of developing breast cancer.
These results indicate that the polygenic risk score is as powerful as other known risk factors such as breast density or family history.
“To do an even better job at risk prediction, we need to include this genetic profile into breast cancer risk models, along with other relevant information like family history, lifestyle risk factors, previous biopsies, and breast density,” said study co-author Fergus Couch, PhD, a molecular geneticist and pathologist at Mayo Clinic. “But first we need to make sure that each of the factors are independent, because if the polygenic risk score is simply repeating what was already accounted for by some of the other known risk factors, then it won’t be valuable in a risk model setting.”