Lipid-metabolism genes are potential biomarkers of estrogen-receptor (ER)-specific breast cancer risk, researchers have found.
Because risk biomarkers that are specific to ER subtypes of breast cancer would aid the development and implementation of distinct prevention strategies, Seema A. Khan, MD, coleader of the Breast Cancer Program at the Robert H. Lurie Comprehensive Cancer Center of Northwestern University in Chicago, Illinois, and colleagues sought to identify women at risk for ER-negative breast cancer. The investigators used fine-needle aspiration to obtain samples that would allow them to examine gene expression in the unaffected breasts of women with unilateral breast cancer. Prior research has indicated that if a woman with cancer in one breast develops cancer in the other breast, the two cancers are likely to have similar hormone-receptor status.
Half of the 30 women studied had ER-positive breast cancer; the remainder had ER-negative disease. A validation set of 36 additional women included 12 with ER-positive breast cancer, 12 with ER-negative cancer, and 12 healthy controls. The cases in each set were matched by age, race, and menopausal status.
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Of the 13 genes expressed at significantly higher levels in samples from ER-negative cancers, eight were associated with lipid metabolism.
“This was interesting because obesity is a breast cancer risk factor for postmenopausal women, but obese women are generally thought to be at increased risk for hormone-sensitive cancer,” explained Khan in a statement issued by the American Association for Cancer Research, publisher of Cancer Prevention Research, in which the study appears. “We were surprised to see that some of these genes that are associated with lipid metabolism are actually more highly expressed in the unaffected breasts of women with [ER]-negative breast cancer.”
Four of the lipid-metabolism genes were found to be significantly overexpressed in ER-negative samples. Two other lipid-metabolism genes were underexpressed in ER-positive samples.
Khan’s team hopes the discovery can eventually be used to determine which women are at risk for a given type of breast cancer so that appropriate prevention strategies can be devised.
