A large-scale assessment of two-way SNP interactions in breast cancer susceptibility using 46 450 cases and 42 461 controls from the breast cancer association consortium
Abstract Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70 917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46 450 breast cancer cases and 42 461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P < 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P < 10−4) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P < 10−8. Results from the second analytic approach were consistent with those from the first (P > 10−10). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.
Molecular characterization of mucinous ovarian tumours supports a stratified treatment approach with HER2 targeting in 19% of carcinomas
AbstractMucinous ovarian carcinomas (MCs) typically do not respond to current conventional therapy. We have previously demonstrated amplification of HER2 in 6 of 33 (18.2%) mucinous ovarian carcinomas (MCs) and presented anecdotal evidence of response with HER2‐targeted treatment in a small series of women with recurrent HER2‐amplified (HER2+) MC. Here, we explore HER2 amplification and KRAS mutation status in an independent cohort of 189 MCs and 199 mucinous borderline ovarian tumours (MBOTs) and their association to clinicopathological features. HER2 status was assessed by immunohistochemistry (IHC), FISH, and CISH, and interpreted per ASCO/CAP guidelines, with intratumoural heterogeneity assessment on full sections, where available. KRAS mutation testing was performed with Sanger sequencing. Stage and grade were associated with recurrence on both univariate and multivariate analysis (p < 0.001). Assessment of HER2 status revealed overexpression/amplification of HER2 in 29/154 (18.8%) MCs and 11/176 (6.2%) MBOTs. There was excellent agreement between IHC, FISH, and CISH assessment of HER2 status (perfect concordance of HER2 0 or 1+ IHC with non‐amplified status, and 3+ IHC with amplified status). KRAS mutations were seen in 31/71 (43.6%) MCs and 26/33 (78.8%) MBOTs, and were near mutually exclusive of HER2 amplification. In the 189 MC cases, a total of 54 recurrences and 59 deaths (53 of progressive disease) were observed. Within MCs, either HER2 amplification/overexpression or KRAS mutation was associated with decreased likelihood of disease recurrence (p = 0.019) or death (p = 0.0041) when compared to cases with neither feature. Intratumoural heterogeneity was noted in 26% of HER2‐overexpressing cases. These data support the stratification of MCs for the testing of new treatments, with HER2‐targeted therapy as a viable option for HER2+ advanced or recurrent disease. Further research is required to delineate the molecular and clinical features of the ∼34% of MC cases with neither HER2 amplification nor KRAS mutations.
Low penetrance breast cancer susceptibility loci are associated with specific breast tumor subtypes: findings from the Breast Cancer Association Consortium
AbstractOver 22,000 cases of ovarian cancer were diagnosed in 2007 in the United States, but only a fraction of them can be attributed to mutations in highly penetrant genes such as BRCA1. To determine whether low-penetrance genetic variants contribute to ovarian cancer risk, we genotyped 1,536 single nucleotide polymorphisms (SNP) in several candidate gene pathways in 848 epithelial ovarian cancer cases and 798 controls in the North Carolina Ovarian Cancer Study (NCO) using a customized Illumina array. The inflammation gene interleukin-18 (IL18) showed the strongest evidence for association with epithelial ovarian cancer in a gene-by-gene analysis (P = 0.002) with a <25% chance of being a false-positive finding (q value = 0.240). Using a multivariate model search algorithm over 11 IL18 tagging SNPs, we found that the association was best modeled by rs1834481. Further, this SNP uniquely tagged a significantly associated IL18 haplotype and there was an increased risk of epithelial ovarian cancer per rs1834481 allele (odds ratio, 1.24; 95% confidence interval, 1.06-1.45). In a replication stage, 12 independent studies from the Ovarian Cancer Association Consortium (OCAC) genotyped rs1834481 in an additional 5,877 cases and 7,791 controls. The fixed effects estimate per rs1834481 allele was null (odds ratio, 0.99; 95% confidence interval, 0.94-1.05) when data from the 12 OCAC studies were combined. The effect estimate remained unchanged with the addition of the initial North Carolina Ovarian Cancer Study data. This analysis shows the importance of consortia, like the OCAC, in either confirming or refuting the validity of putative findings in studies with smaller sample sizes. (Cancer Epidemiol Biomarkers Prev 2008;17(12):3567–72)