NEW YORK (GenomeWeb News) – Expression levels of several genes related to lipid or fat metabolism may help in predicting whether women at risk of breast cancer are more prone to forms of the disease that respond to estrogen or not, according to a study out today in Cancer Prevention Research.
"It was a surprise for us that these genes are related to fat metabolism, because we would have expected them to be related to estrogen," the study's first author, Jun Wang, a research assistant in senior author Seema Khan's Northwestern University lab, said in a statement. "Now we want to find out why women have higher levels of these genes."
Khan, Wang, and colleagues from Northwestern University and Miami's Mercy Hospital obtained samples from 30 women diagnosed with estrogen receptor-positive or estrogen receptor-negative breast cancer in only one breast and used microarrays to assess gene expression in samples from each woman's other, unaffected breast.
The analysis uncovered 13 genes with higher-than-usual expression levels in seemingly healthy samples from the women with ER-negative breast cancer, an often tricky to treat form of the disease known for its lack of estrogen receptor expression. Eight of the genes came from pathways involved in the metabolism of fatty acids, steroids, or lipids — a pattern that investigators verified using samples from three-dozen more women.
Those involved in the study are optimistic that the gene signature could ultimately be used to determine what type of preventative treatment, if any, should be offered to women believed to be at risk of breast cancer based on incidence of the disease in their close relatives or in those already diagnosed with cancer in one breast.
By using such gene expression information to better understand the pathways that contribute to each form of breast cancer, they noted, there may also be potential for finding new treatment targets.
"Identifying these genes also gives us a target for new therapies," Khan said in a statement. "Once we understand what regulates these genes, we can try to develop a therapy to switch them off."
The hormone receptor status of breast cancers can have implications for everything from disease prognoses to treatment selection. For instance, treatments developed to prevent ER-positive breast cancers are known to be futile against ER-negative breast cancer, Khan and her co-authors noted, often making it tricky to know whether it's worth subjecting high-risk individuals to the potential side effects of such drugs.
In addition, past studies suggest that the hormone status of tumors tends to stay the same for women with unilateral breast cancer who go on to develop cancer in the other breast.
As such, those involved in the new analysis suspected that they might be able to get a peek at the molecular landscape that precedes ER-positive or -negative breast tumors by preemptively testing samples from the unaffected breast of women with cancer in the other breast.
Using Illumina Human WG6 BeadArrays, the team determined gene expression patterns in random fine needle aspirates drawn from the unaffected breasts of 15 women with ER-negative breast cancer and 15 women with an ER-responsive form of the disease.
All told, the researchers tracked down 18 transcripts that were more highly expressed in unaffected samples from the ER-negative women than in corresponding samples from those with ER-positive individuals.
Of these 18 transcripts, five appeared to be duplicates, leaving 13 suspicious genes for testing in the subsequent analyses, they reported, with gene set enrichment placing at least eight of the genes in lipid and/or metabolism-related pathways.
After confirming the lipid and metabolism-related gene expression links by quantitative real-time PCR in samples with sufficient RNA, the team went on to show that these eight genes appeared to cluster samples in ways that corresponded with the presence or absence of estrogen receptor expression as well as the level of that expression.
Researchers again saw significantly higher expression for all eight of the genes when they tested fine needle aspirate-based unaffected breast samples from another 12 women with ER-negative breast cancer and 12 women with ER-positive breast cancer.
Compared with expression profiles in samples from a dozen women without breast cancer, meanwhile, the samples from ER-negative cases showed higher expression at four of the eight genes and ER-positive cases had muted expression at two of the genes.
Two more of the genes in the potential ER-negative signature showed decreased expression across the board in samples from those with breast cancer compared to controls, regardless of whether they had ER-negative or ER-positive tumors.
"Our novel findings that lipid metabolism-related genes are expressed at higher levels in the contralateral [unaffected] breasts of ER-[negative] cases point to potential interactions of the lipid metabolism-sex steroid axis and the metabolic environment of high-risk breasts," study authors explained.
The reason for these expression profiles is yet to be determined, the group pointed out, since features in the unaffected breast might reveal physiological features that set the stage for a certain type of breast cancer, but it could also reflect disease features found in the other, affected breast.
Regardless, they argued that "studies of gene expression profiles in contralateral [unaffected] breast would provide us clues on tumor subtype preference and potential ER-specific biomarkers."