September 16, 2021

Structural variants in breast cancer risk genes

Vanderbilt epidemiologists conducted in-depth whole genome sequencing of breast cancer risk genes in Black women, who die at higher rates and have more aggressive disease, to discover mutations that may improve testing and treatment selection.

Many genetic variants have been identified related to the risk of breast cancer — the second leading cause of cancer death among women in the United States, but most studies have focused on single site genetic changes, or short insertions or deletions. Little is known about structural gene variants, such as large deletions, that may have a greater impact on gene function. 

Wei Zheng, MD, PhD, MPH, and colleagues previously conducted a whole genome sequencing (WGS) study in 128 patients of Asian and European descent and identified six novel deletions in breast cancer predisposition genes. They have now expanded the study to evaluate breast cancer genetic risk variants in women of African ancestry: 1,340 patients with invasive breast cancer and 675 controls. African American women die at a higher rate and have more aggressive breast cancer than white women. 

The researchers identified 25 large deletions in breast cancer predisposition genes, including eight that likely result in protein truncation and were associated with increased breast cancer risk. They also detected 56 deletions in suspected breast cancer predisposition genes. 

The study, reported in Human Genetics, is the largest to use WGS to systematically search for deletions in known and suspected breast cancer predisposition genes. The findings may improve clinical testing and selection of breast cancer treatment. 

The WGS data was generated as part of the African American Breast Cancer Genetic (AABCG) Consortium and the Ghana Breast Health Study (GBHS). The research was supported primarily by the National Institutes of Health (grant CA202981). 

Other Vanderbilt contributors to the study included Zhishan Chen, PhD, Xingyi Guo, PhD, Jirong Long, PhD, Jie Ping, PhD, Bingshan Li, PhD, Xiao-Ou Shu, MD, PhD, Guochong Jia, MPH, William J. Blot, PhD, and Qiuyin Cai, MD, PhD.