Predicting cancer risk using genetic variation


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Douglas Easton1
1University of Cambridge, Cambridge, UK

Abstract

Common cancers exhibit familial aggregation, consistent with substantial variation in inherited susceptibility. The majority of this variation appears to be mediated through a combination of genetic variants of individually small effect. Approximately 200 such loci for common cancers have already been definitively identified, primarily through genome-wide association studies (GWAS), and ongoing studies are expected to reveal many more. In most cases, the genes underlying these associations are not known, and point to unexplored mechanisms of cancer susceptibility, while some (e.g. MSMB for prostate cancer) may have immediate practical application. While the risks associated with low-penetrance alleles are modest, their effects combine multiplicatively and can give rise to substantial variation in predicted risks. For example, based on the currently loci for breast cancer, the 1% of the population of at highest risk have a risk that is 2.5 fold higher than the population average, while the lowest 1% have a risk that is 1/3 of the population average. For prostate cancer, the discrimination is greater: the top 1% of the population have a risk that is 4-5 fold greater than the population average. Genetic risks also appear to combine multiplicatively with other risk factors, such as mammographic density. Genetic profiling may have important implications for risk prediction, particularly in individuals with a family history of cancer, targeted screening and prevention strategies.