Unlocking New Insights Into Breast Cancer Risk

A new study led by William Letsou, Ph.D., assistant professor of biological and chemical sciences, could change how scientists and clinicians understand genetic predisposition to breast cancer, a condition that affects one in eight American women in her lifetime.

Knowing a patient’s genetic predisposition to breast cancer can help clinicians predict the likelihood of disease development and select the most effective treatment options. While 27 percent of all breast cancers may be caused by inherited genetic mutations, not all mutations have the same impact. For example, BRCA gene mutations, which are known to directly increase breast cancer risk, are found in only 10 percent of breast cancer patients. Yet these patients can be up to six times more likely to develop the disease. On the other hand, some studies suggest that having many commonly occurring variations in DNA building blocks can impact one’s chances of developing the disease.

The study, published in Life Science Alliance, suggests another scenario: Having a certain rare combination of common variants could highly increase breast cancer risk.

Letsou and his co-authors, including researchers from St. Jude Children’s Research Hospital, the University of Minnesota, and the University of Alberta (Canada), developed a new algorithm to analyze the genetic makeup of 9,000 women with breast cancer. Within this group, the researchers singled out women who carry the same variant of a single nucleotide polymorphism (SNP)—a variation of one DNA base in a gene sequence—previously linked to breast cancer risk.

The team discovered that the women with this SNP could be further categorized into subgroups based on other nearby variants they had inherited. Although these inheritance patterns were rare, they occurred more frequently in those diagnosed with breast cancer—in fact, four times as often. The findings suggest that having a certain combination of common variants could increase one’s risk significantly.

“To date, the role of computational biology has been to uncover how thousands of common polymorphisms additively impact disease risk. Basically, the more variants you carry, the higher your risk of developing certain cancers. However, our new computational method shows that having a specific combination of common variants may be enough to increase disease risk,” says Letsou.

The researchers hope that their method will uncover additional rare combinations of SNPs in other genes, which may, in the long term, allow clinicians to assess breast cancer risk better and inform targeted therapies for different subsets of patients.