The search for low-penetrance breast cancer genes

Background

Fifteen per cent to 20% of the familial clustering of breast cancer is explained by the effects of highly penetrant mutations in BRCA1 and BRCA2. Modelling based on the patterns of familial aggregation of breast cancer in the relatives of cases ascertained on a population basis suggests that much of the remaining familial effect is due to the combined effects of genetic variants individually of small effect. The numbers of such variants, their allele frequencies and the strength of their effects is not known.

Methods

We have carried out association studies to search for common variants (minor allele frequency >5–10%) that contribute to predisposition,. To date we have studied 400 SNPs in 110 genes using a two-stage study design, in which a first set of 2300 cases and controls is analysed and all SNPs with a significance value of P < 0.1 or better are then tested in a second, similar, case/control set.

Results

No individual SNP has, to date, given a P value for association (based on genotype distribution) lower than 10^-4. A number of SNPs give P values between 10^-2 and 10^-4, depending on the genetic model that is chosen for the analysis. Most of these are probably false positives, the consequence of multiple testing. However, comparison of the distribution of P values across the entire study set with that expected if there were no genetic effect suggests that some of these are probably true positive associations, representing low-level predisposing effects.

Conclusions

A candidate gene approach is slow and relatively expensive, and has not so far yielded unequivocal positive results for any individual gene. The 'genetic architecture' of breast cancer – that is, the number and characteristics of predisposing genetic variants – is still not known. In an attempt to elucidate this and to hasten the process of gene discovery, we have initiated (with collaborators in the UK and at Perlegen Science Inc.) a genome-wide scan. Again we use a two-stage approach. In the first stage we will evaluate 266,000 SNPs in 400 breast cancer cases and 400 controls. The cases will be 'enriched' for genetic effects by choosing those with a family history, tested negative for BRCA1/2 mutation. In the second stage, ~5% of SNPs will be further evaluated in 4600 cases and controls. A final stage of evaluation for positives from the second stage, and from our earlier studies, will require analysis of a further, very large (~10,000), case/control set, which we hope to assemble through international collaboration.