Michailidou, Kyriaki

Background BRCA1 interacting protein C-terminal helicase 1 (BRIP1) is one of the Fanconi Anaemia Complementation (FANC) group family of DNA repair proteins. Biallelic mutations in BRIP1 are responsible for FANC group J, and previous studies have also suggested that rare protein truncating variants in BRIP1 are associated with an increased risk of breast cancer. These studies have led to inclusion of BRIP1 on targeted sequencing panels for breast cancer risk prediction. Methods We evaluated a truncating variant, p.Arg798Ter (rs137852986), and 10 missense variants of BRIP1, in 48 144 cases and 43 607 controls of European origin, drawn from 41 studies participating in the Breast Cancer Association Consortium (BCAC). Additionally, we sequenced the coding regions of BRIP1 in 13 213 cases and 5242 controls from the UK, 1313 cases and 1123 controls from three population-based studies as part of the Breast Cancer Family Registry, and 1853 familial cases and 2001 controls from Australia. Results The rare truncating allele of rs137852986 was observed in 23 cases and 18 controls in Europeans in BCAC (OR 1.09, 95% CI 0.58 to 2.03, p=0.79). Truncating variants were found in the sequencing studies in 34 cases (0.21%) and 19 controls (0.23%) (combined OR 0.90, 95% CI 0.48 to 1.70, p=0.75). Conclusions These results suggest that truncating variants in BRIP1, and in particular p.Arg798Ter, are not associated with a substantial increase in breast cancer risk. Such observations have important implications for the reporting of results from breast cancer screening panels.

Previous genome‐wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. A fine‐mapping study across 2.06 Mb (chr8:127,561,724–129,624,067, hg19) in 55,540 breast cancer cases and 51,168 controls within the Breast Cancer Association Consortium was conducted. Three additional independent association signals in women of European ancestry, represented by rs35961416 (OR = 0.95, 95% CI = 0.93–0.97, conditional p = 5.8 × 10−6), rs7815245 (OR = 0.94, 95% CI = 0.91–0.96, conditional p = 1.1 × 10−6) and rs2033101 (OR = 1.05, 95% CI = 1.02–1.07, conditional p = 1.1 × 10−4) were found. Integrative analysis using functional genomic data from the Roadmap Epigenomics, the Encyclopedia of DNA Elements project, the Cancer Genome Atlas and other public resources implied that SNPs rs7815245 in Signal 3, and rs1121948 in Signal 5 (in linkage disequilibrium with rs11780156, r2 = 0.77), were putatively functional variants for two of the five independent association signals. The results highlighted multiple 8q24 variants associated with breast cancer susceptibility in women of European ancestry.

Abstract Background: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. Methods: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. Results: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10−4; OR, 1.04; 95% confidence interval (CI), 1.02–1.07] and rs77928427 (P = 1.86 × 10−4; OR, 1.04; 95% CI, 1.02–1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r2 ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor–binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. Conclusion: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. Impact: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk. Cancer Epidemiol Biomarkers Prev; 24(11); 1680–91. ©2015 AACR.

Abstract Genome-wide association studies (GWAS) have identified several susceptibility regions that confer risk of two or more cancers. A region at 19p13 is associated with both breast and ovarian cancer risk in the general population as well as in BRCA1/BRCA2 mutation carriers. Using the iCOGs custom genotyping array, we analyzed 438 SNPs in this region in 7,435 ER-negative breast cancer cases and 42,599 controls from BCAC, and 15,347 ovarian cancer cases and 30,845 controls from OCAC and 15,252 BRCA1 mutation carriers. We identified two significant peaks of association. Peak 1, consisting of 13 highly correlated SNPs (r2>0.95), spans a 19.4kb region harboring the BABAM1, ANKLE1 and ABHD8 genes. Peak 1 SNPs are associated with serous ovarian cancer (top hit rs4808075, P = 9.2×10-20), ER-negative breast cancer (rs61494113, P = 1.1×10-13) and breast cancer in BRCA1 mutation carriers (rs61494113, P = 7.7×10-16). Peak 2 spans over 100kb and contains 7 SNPs associated with breast cancer in BRCA1 mutation carriers only (rs4464206, P = 8.9×10-8). Multiple assays were used to establish the putative functional roles of risk SNPs and candidate susceptibility genes in this region. Expression quantitative trait locus (eQTL) analyses identified significant genotype-gene expression correlations between genotype at the Peak 1 SNP rs480816 and ABHD8 expression in ovarian tumors (P = 3.0×10-5) and normal breast tissues (P = 2.8×10-3). The Peak 2 SNP, rs7246243, was significantly associated with BABAM1 expression (P = 5×10-3) in normal breast tissue only. Overexpression of BABAM1 in normal ovarian and breast cells did not modulate neoplastic phenotypes, whereas overexpression of ABHD8 induced a significant reduction in migration in both cell types in vitro. Differentially expressed genes in ABHD8 models, identified by RNAseq, were associated with cellular movement (P<1.82×10-44). Chromosome conformation capture (3C) identified an interaction between the ABHD8 promoter and a region containing 4 risk SNPs (rs4808075, rs10419397, rs56069439 and rs4808076) in breast and ovarian normal and cancer cells but only rs56069439 coincides with epigenetic enhancer marks in breast and ovarian cells. CRISPR/Cas9 genome editing was used to delete a 57bp region containing rs56069439 and expression of BABAM1, ANKLE1 and ABHD8 were measured. Taken together, these data suggest a common functional mechanism underlying risk of breast and ovarian cancer at this locus, mediated by rs56069439 variants differentially regulating expression of ABHD8, a gene involved in cell motility. Citation Format: Kate Lawrenson, Siddhartha Kar, Karoline Kuckenbaeker, Stacey Edwards, Qiyuan Li, Jonathan Tyrer, Jonathan Beesley, Kyriaki Michailidou, Susan Ramus, Alison Dunning, Fergus Couch, Alvaro Monteiro, Jacques Simard, Matthew Freedman, Douglas Easton, Georgia Chenevix-Trench, Paul Pharoah, Antonis Antoniou, Simon Gayther, OCAC, BCAC and CIMBA. Common functional mechanisms underlying pleiotropy at the 19p13.1 breast and ovarian cancer cusceptibility locus. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2783. doi:10.1158/1538-7445.AM2015-2783

Abstract Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10−5). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk. Cancer Res; 75(12); 2457–67. ©2015 AACR.

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.