New Results in Susceptibility to Breast Cancer and their Implications
Authors: Bruce Ponder, Paul Pharoah, Dennis Ballinger, David Cox, Alison Dunning, Douglas Easton
Journal: Clinical Cancer Research (2007)

KN01  The extent of familial clustering of breast cancer provides an estimate of the total inherited contribution to susceptibility. Of this, roughly 25% has been explained by moderately or strongly predisposing mutations in genes such as BRCA1 and 2, CHK2, TP53 and others. The pattern of familial clustering outside the known effects of these mutations suggests that the remaining 75% of predisposition is mostly explained by polygenic effects - that is, the combined effects of many genetic variants of individually small effect. No inference can be made, however, about the proportions in which the predisposing variants are common or rare, strong or weak.  Because the supposed polygenic variants are individually of weak effect, they do not cause multiple case families and cannot be sought by classical linkage analysis. Instead a case control strategy is used, called an  study. In this, the frequency of occurrence of individual genetic variants (measured as single nucleotide polymorphisms, or SNPs) is compared between a large set of breast cancer cases, and healthy controls of the same genetic background. A reproducible difference in SNP frequency between cases and controls that implies that that SNP, or one closely associated with it in the genome (in linkage disequilibrium, within the same haplotype block) confirms susceptibility. This method generally has good statistical power to detect variants only with a frequency in the population of 5 to 10% or greater. A given gene is  tested if a set of variants is identified that are able to report, through linkage disequilibrium, on all the other common genetic variants in that gene (in this case, the gene is said to be completely tagged).  The power of such studies can be expressed in terms of the probability of detection, at a given significance level, of any common variant that accounts for a specified proportion - say 1% of the total genetic contribution to susceptibility. A high level of statistical significance is required before a putative association can be accepted. This is primarily because of the low prior probability that a given variant, out of the millions in the genome, would in fact be truly associated with susceptibility. p values of 10-2 and less are not uncommon, but cannot be accepted until they have been shown to be replicable in a number of independent studies using different sample sets. To address this, we and others set up an International Breast Cancer Association Consortium (BCAC), which currently has over 20,000 cases and 20,000 controls, for replication studies.  The first attempts at association studies were directed at single candidate genes. These studies were largely unproductive. In order to speed up the rate of discovery, we designed in 2003 the first genome-wide association study for breast cancer. In this we were able to test simultaneously a set of 266,000 variants, distributed across the genome and chosen to give the best compromise between cost and completeness of coverage. We used a three-stage design. In the first stage, 400 cases and controls were compared using all 266,000 SNPs. The cases were chosen for having strong family histories and were, therefore, presumably genetically enriched. In Stage 2, the top ranked 5% of SNPs from Stage 1 were tested in a population-based set of 4,000 cases and controls. In Stage 3, so far the top 30 SNPs from Stage 2 have been further tested in the 20,000 cases and controls of the Breast Cancer Consortium. We estimate that this study had roughly 65% coverage of the genome, and 90% power to detect any common genetic variant that accounts for 1% of the total genetic effect.  Of the 30 top ranked SNPs from Stage 2, five were clearly reproducible in the BCAC case control set in Stage 3; three gave borderline results in the same direction as had been observed in Stage 2; and the remainder showed no effect and were presumably therefore technical artefacts or false positives. The SNP which showed the strongest association lay in an intron of the gene FGFR2. The assignment of the other variants to specific genes is still provisional, because in each case the variant lies within a large linkage disequilibirium region in the genome. In total, the five SNPs for which there is unequivocal association account for just under 4% of the total genetic variance. Studies are underway to identify the causative SNPs from within the linkage disequilibrium blocks, and to elucidate their function.  Individually, these SNPs confer small relative risks - of the order of 1.1 to 1.3 fold as heterozygotes, and a maximum of 1.6 fold in the FGFR2 homozygote. They are therefore, taken singly, unlikely to be of great clinical value in refining estimates of individual risk. In combination, however, polygenic variants may have quite striking effects. Modelling by our group suggests that, if all the putative genetic variants could be identified and used to construct a risk profile, it would be found that approximately half of all breast cancer occurs in the 12% of women most at risk. However, we are some way from identifying all of those variants. The variants that have been identified to date might allow one to identify a predisposed 10% of women who have 15% of breast cancer incidence.  On the other hand, because the FGFR2 variant, for example, is common (allele frequency 38%), despite its relatively modest effect on risk, it has a high attributable fraction. That is to say, if the effect of that variant could be neutralised in the population, total breast cancer incidence might be reduced by approximately 16%. In principle, therefore, an intervention that would neutralise the effect of the FGFR2 SNP might have significant public health application. But of course such a proposed intervention also raises a myriad of problems around risks and benefits, how these could be assessed, public understanding, etc. An interesting but speculative possibility is to ask whether all of the individual genetic variants that in combination would place a woman at high risk are independent of one another; or whether perhaps in any given individual there is an association of variants that target different part of the same physiological process or network. It the latter were true, it might conceivably be that one could identify a disturbed phenotype related to that genetic network, modulation of which in the population by acceptable methods might significantly reduce the overall breast cancer burden. This would be analogous to cholesterol or blood pressure for cancer.