Genome-wide association studies (GWAS) have identified more than 150 genetic variations associated with increased risk for breast cancer. Most of these variants are not located in protein-coding gene regions but are assumed to regulate the expression of certain genes.
One way to figure out what these variants are doing is to conduct a cis-eQTL analysis. That’s a way of detecting changes in the expression of genes presumably regulated by a nearby variant.
Using four large-scale data sets from normal and cancerous breast tissue samples, Xingyi Guo, Ph.D., and colleagues identified 101 candidate breast cancer susceptibility genes with variant-associated gene expression changes. In breast cancer cells grown in culture, the researchers also demonstrated how three genes promoted tumor growth by disrupting normal cell behavior.
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