The genetics of breast cancer: risk factors for disease

enetics of breast cancer: risk factors for disease Review (5338) Total Article Views Authors: Andrew Collins, Ioannis Politopoulos Published Date January 2011 Volume 2011:4 Pages 11 - 19 DOI: http://dx.doi.org/10.2147/TACG.S13139 Andrew Collins, Ioannis Politopoulos Genetic Epidemiology and Bioinformatics Research Group, Human Genetics Research Division, Southampton General Hospital, School of Medicine, University of Southampton, Southampton, UK Abstract: The genetic factors known to be involved in breast cancer risk comprise about 30 genes. These include the high-penetrance early-onset breast cancer genes, BRCA1 and BRCA2, a number of rare cancer syndrome genes, and rare genes with more moderate penetrance. A larger group of common variants has more recently been identified through genome-wide association studies. Quite a number of these common variants are mapped to genomic regions without being firmly associated with specific genes. It is thought that most of these variants have gene regulatory functions, but their precise roles in disease susceptibility are not well understood. Common variants account for only a small percentage of the risk of disease because they have low penetrance. Collectively, the breast cancer genes identified to date contribute only ~30% of the familial risk. Therefore, there is much interest in accounting for the missing heritability, and possible sources include loss of information through ignoring phenotype heterogeneity (disease subtypes have genetic differences), gene–gene and gene–environment interaction, and rarer forms of variation. Identification of these rarer variations in coding regions is now feasible and cost effective through exome sequencing, which has already identified high-penetrance variants for some rare diseases. Targeting more ‘extreme’ breast cancer phenotypes, particularly cases with early-onset disease, a strong family history (not accounted for by BRCA mutations), and with specific tumor subtypes, provides a route to progress using next-generation sequencing methods.