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This group focuses on how polygenic variation contributes to susceptibility to breast and lung cancer. They analyze mechanisms both at single loci, and at the level of gene regulatory networks. Aims: 1) to improve recognition of high risk groups within the population and 2) ultimately, to devise strategies for prevention based on mechanisms of risk. The 11q13 and FGFR2 risk loci were among the first breast cancer risk loci identified. To gain insight into their mechanism of function, genetic fine-mapping was carried out in collaboration with the iCOGS consortium for both loci and combined with functional studies using DNase hypersensitivity, transcriptional assays, chromatin immunoprecipitation and 3C (chromatin conformation capture). Likely functional variants and the regulated target genes were identified. Interestingly the initial risk association was driven by multiple independent risk signals for both genes and allele-specific binding by the transcription factors ELK4 and GATA3, and FOXA1 and E2F1 was shown to underlie changes in transcriptional activity of the target genes CCND1 and FGFR2, respectively. The findings highlight that regulatory mechanisms at risk loci are highly complex. The most important practical consequence of the polygenic model is that it implies a distribution of risk in the population. The question is, does the large number of different possible combinations of variants imply a similarly large number of different mechanisms ? which would be difficult to unravel and difficult to target for prevention ? or do these combinations all converge in the end on a small number of common mechanisms? To address this, two approaches were taken: 1. An extension of variant set enrichment analysis to show that the set of FGFR2-regulated genes are themselves enriched among the eQTLs at the top 68 breast cancer GWAS loci: that is, among the genes whose expression is altered by the SNPs that lie in the same haplotype block as the ?tagging SNP? detected by GWAS. This result implies a degree of clustering of mechanism around the FGFR2 pathway among the top breast GWAS hits. 2. A wider look at the distribution of the eQTLs related to the top GWAS loci across the regulons in the entire breast cancer regulatory network. Our preliminary results (Figure 2) (unpublished) suggest a markedly non-random distribution, which implies that mechanisms of polygenic susceptibility may be less heterogeneous that we had feared. In the future, these results will be extended and the same approaches applied to lung cancer.