Allelic imbalance in BRCA1 and BRCA2 gene expression is associated with an increased breast cancer risk

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Abstract

The contribution of BRCA1 and BRCA2 to familial and non-familial forms of breast cancer has been difficult to accurately estimate because of the myriad of potential genetic and epigenetic mechanisms that can ultimately influence their expression and involvement in cellular activities. As one of these potential mechanisms, we investigated whether allelic imbalance (AI) of BRCA1 or BRCA2 expression was associated with an increased risk of developing breast cancer. By developing a quantitative approach utilizing allele-specific real-time PCR, we first evaluated AI caused by nonsense-mediated mRNA decay in patients with frameshift mutations in BRCA1 and BRCA2. We next measured AI for BRCA1 and BRCA2 in lymphocytes from three groups: familial breast cancer patients, non-familial breast cancer patients and age-matched cancer-free females. The AI ratios of BRCA1, but not BRCA2, in the lymphocytes from familial breast cancer patients were found to be significantly increased as compared to cancer-free women (BRCA1: 0.424 versus 0.211, P = 0.00001; BRCA2: 0.206 versus 0.172, P = 0.38). Similarly, the AI ratios were greater for BRCA1 and BRCA2 in the lymphocytes of non-familial breast cancer cases versus controls (BRCA1: 0.353, P = 0.002; BRCA2: 0.267, P = 0.03). Furthermore, the distribution of under-expressed alleles between cancer-free controls and familial cases was significantly different for both BRCA1 and BRCA2 gene expression (P < 0.02 and P < 0.02, respectively). In conclusion, we have found that AI affecting BRCA1 and to a lesser extent BRCA2 may contribute to both familial and non-familial forms of breast cancer. © The Author 2008. Published by Oxford University Press. All rights reserved.

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Chen, X., Weaver, J., Bove, B. A., Vanderveer, L. A., Weil, S. C., Miron, A., … Godwin, A. K. (2008). Allelic imbalance in BRCA1 and BRCA2 gene expression is associated with an increased breast cancer risk. Human Molecular Genetics, 17(9), 1336–1348. https://doi.org/10.1093/hmg/ddn022

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