Amplified in Breast Cancer

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BRCA1 is a coactivator of AR, and this activation is mediated in part through an estrogen-receptor coactivator, amplified in breast cancer 1 (AIB1) (73). Rebbeck et al. studied the effect of a glutamine repeat polymorphism at the AIB1 locus, whose functional effect is unknown, using a matched case-control sample of 448 women with germline BRCA1 (n = 370) or BRCA2 (n = 78) mutations (29). These women were at a significantly higher breast cancer risk if they carried alleles with at least 28 or 29 polyglutamine repeats in AIB1, compared with women who carried alleles with fewer repeats (OR = 1.59; 95% CI 1.03-2.47 or OR = 2.85; 95% CI 1.64-4.96, respectively). This effect was also seen when analysis was restricted to only BRCA1 mutation carriers. Women were at an even higher risk if they had AIB1 alleles with at least 28 polyglutamine repeats and were either nulliparous or had had a late age at first live birth (OR = 4.62; 95% CI 2.02-10.56) compared to women with none of these risk factors. The unconditional logistic regression analysis used in this study did not take into account the relatedness of carriers, nor did the study have sufficient power to examine the effect on BRCA2 carriers alone. Colilla et al. (48) appeared to confirm this result and found an interaction with smoking, using a different method to categorize repeat lengths. Three further studies have since attempted to replicate this result, with little success. Kadouri et al. (74) genotyped 311 carriers, 257 of which were of Jewish origin, and, using a maximum likelihood approach to account for ascertainment, found that there was a nonsignificant elevation of breast cancer risk (OR = 1.29; 95% CI 0.85-1.96) in BRCA1 mutation carriers with at least 29 AIB1 repeats. However, when the repeat was analyzed as a continuous variable, the effect was significant, particularly among BRCA1 carriers (RR = 1.25; 95% CI 1.09-1.42). Hughes et al. (75) genotyped 851 BRCA1 and 324 BRCA2 female carriers from 678 families from France, Greece, and the United States, and used a standard Cox proportional hazards model for the analysis. No effect of the AIB1 repeat polymorphisms was found regardless of whether the BRCA1 and BRCA2 carriers were analyzed together (HR = 1.10; 95% CI 0.92-1.11 when analyzed as a continuous variable) or separately. The largest study of the role of the AIB1 repeat polymorphism as a modifier of BRCA1 or BRCA2 evaluated 1090 BRCA1 and 661 BRCA2 carriers from Australia, Europe, and North America (76). The association between genotype and disease risk was assessed using weighted Cox regression analysis, which adjusts for the fact that disease status of the carriers may have affected the likelihood of ascertainment. Robust variance estimates were used to calculate confidence limits, taking into account relatedness between carriers from the same family. There was no evidence for an increased risk of breast cancer associated with the AIB1 glutamine repeat length, whether the repeat was evaluated as a continuous variable, or with cut points of > 28 or > 29 repeats, for BRCA1 or BRCA2 carriers. This study was sufficiently large to detect risk ratios of 1.56 and 2.85 with 91% and 100% power respectively for BRCA1 carriers, and 58% and 100% power for BRCA2 carriers, and so we can confidently exclude any substantial risk of this polymorphism in BRCA1 or BRCA2 carriers.

TP53

Somatic mutations in TP53 are the most frequent events in human cancer, and germline mutations of p53 cause Li Fraumeni syndrome, of which early onset breast cancer is a feature. Polymorphisms of TP53 are therefore good candidates as modifiers of BRCA1 and BRCA2, in particular Pro72Arg, which appears to be a functional SNP (77). There are also multiple intronic polymorphisms in TP53, two of which were examined by Wang-Gohrke et al. (78) in 400 German BRCA1 and BRCA2 carriers but were not found to be associated with risk of ovarian cancer, despite some evidence to the contrary in unselected ovarian cancer cases. The largest study to evaluate TP53 as a modifier of BRCA1 and BRCA2 was of 447 Spanish carriers (including 88 males) from 170 families (79). Osorio et al. genotyped the Pro72Arg SNP, as well as a 16 bp insertion in intron 3, and used unconditional logistic regression to compare haplotype frequencies between early onset breast or ovarian cancer cases and other carriers. They also used robust estimators of variance to take into account the relatedness of the carriers. They found that the "No Ins-72 Pro" haplotype was associated with early age of onset (before age 35) of breast or ovarian cancer in BRCA2 mutation carriers (n = 119) (OR = 2.69; 95% CI 1.15-6.29), but not in BRCA1 carriers (n = 146). This apparent differential effect on BRCA1 versus BRCA2 carriers may be because the penetrance of BRCA2 mutations is lower. They repeated the analyses, including just the 170 index cases from each family (who were therefore unrelated) and found that the results were consistent when the BRCA1 and BRCA2 carriers were combined. Osorio et al. also reported that No Ins-72Arg homozygous cells are more efficient at inducing apoptosis than genotypes with at least one mutant 72Pro allele. A larger study of both BRCA1 and BRCA2 carriers is now warranted to try and validate this association between TP53 haplotypes and risk of cancer in BRCA2 mutation carriers, and to determine whether they also modify risk in BRCA1 mutation carriers.

RAD51

RAD51 currently provides the most convincing evidence for the existence of a modifier gene for cancer risk in BRCA2 mutation carriers. RAD51 is the homolog of bacterial RecA, which is required for recombinational repair of double-strand DNA breaks, in particular for BRCA2-mediated repair (80). Both BRCA1 and BRCA2 interact with RAD51 (81,82), and the RAD51 mouse knockout phenotype resembles the BRCA1 and BRCA2 knockout phenotypes (82). The -135G > C SNP in the 5' untranslated regions (UTR) of RAD51 was first published in a study of 257 female Ashkenazi Jewish carriers from 141 BRCA1 and 64 BRCA2 families (83). Using logistic regression and Cox proportional hazard analysis, no effect was seen on BRCA1 carriers, but the HR for cancer (breast or ovarian) associated with heterozygosity for the C allele in BRCA2 carriers was 4.0 (85% CI 1.3-9.2), largely because of its effect on breast cancer risk. The results were similar when the analysis was restricted to unrelated cases. Three additional studies of this RAD51 SNP as a modifier of BRCA1/2 have been published. Wang et al. (85) genotyped two sets of carriers; in the first set of 186 carriers, the C allele was more common in affected women with a mutation in either BRCA1 or BRCA2. However, when this dataset was combined with a larger set of 466 carriers ascertained by three centers in Australia and the United States, an increased risk of breast cancer was only found among BRCA2 carriers (n = 216; OR = 3.2; 95% CI 1.4-40), while their risk of ovarian cancer appeared to be decreased. Logistic regression was used to determine the effect of the RAD51 SNP on risk, and a bootstrapping resampling technique was employed to calculate CIs and P-values that accounted for the nonindependence of genotypes from related carriers. Kadouri et al. (86) genotyped 297 BRCA1 and BRCA2 carriers from Israel and the United Kingdom for the same SNP in the RAD51 promoter and, using Cox regression, also found an increased risk of breast cancer (HR = 2.09; 95% CI 1.04-4.18) for BRCA2 carriers, and that the median age of breast cancer in BRCA2 carriers with the RAD51 C allele was seven years less than that in RAD51 wild-type carriers. In contrast, Jakubowska et al. (87) evaluated this RAD51 SNP in just 83 pairs of (affected and unaffected) female carriers of the Polish BRCA1 founder mutation, 5382insC. They reported a reduced risk of breast cancer among RAD51 C allele carriers (OR = 0.23; 95% CI 0.07-0.62). If confirmed, RAD51 - 135G > C would be the first SNP found to have opposite effects in BRCA1 and BRCA2 carriers. The function of the - 135G > C SNP in RAD51 is not clear, but being located in the 5' UTR, it could affect mRNA stability or translational efficiency.

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