Pharoah, Paul D.P.

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 Background: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. Methods: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. Cancer Epidemiol Biomarkers Prev; 24(10); 1574–84. ©2015 AACR.

Abstract Purpose: Chemotherapy resistance remains a major challenge in the treatment of ovarian cancer. We hypothesize that germline polymorphisms might be associated with clinical outcome. Experimental Design: We analyzed approximately 2.8 million genotyped and imputed SNPs from the iCOGS experiment for progression-free survival (PFS) and overall survival (OS) in 2,901 European epithelial ovarian cancer (EOC) patients who underwent first-line treatment of cytoreductive surgery and chemotherapy regardless of regimen, and in a subset of 1,098 patients treated with ≥4 cycles of paclitaxel and carboplatin at standard doses. We evaluated the top SNPs in 4,434 EOC patients, including patients from The Cancer Genome Atlas. In addition, we conducted pathway analysis of all intragenic SNPs and tested their association with PFS and OS using gene set enrichment analysis. Results: Five SNPs were significantly associated (P ≤ 1.0 × 10−5) with poorer outcomes in at least one of the four analyses, three of which, rs4910232 (11p15.3), rs2549714 (16q23), and rs6674079 (1q22), were located in long noncoding RNAs (lncRNAs) RP11-179A10.1, RP11-314O13.1, and RP11-284F21.8, respectively (P ≤ 7.1 × 10−6). ENCODE ChIP-seq data at 1q22 for normal ovary show evidence of histone modification around RP11-284F21.8, and rs6674079 is perfectly correlated with another SNP within the super-enhancer MEF2D, expression levels of which were reportedly associated with prognosis in another solid tumor. YAP1- and WWTR1 (TAZ)-stimulated gene expression and high-density lipoprotein (HDL)-mediated lipid transport pathways were associated with PFS and OS, respectively, in the cohort who had standard chemotherapy (pGSEA ≤6 × 10−3). Conclusions: We have identified SNPs in three lncRNAs that might be important targets for novel EOC therapies. Clin Cancer Res; 21(23); 5264–76. ©2015 AACR.

Abstract Background: Common genetic variants identified by genome-wide association studies and follow-up genotyping initiatives only explain a small proportion of the heritability of epithelial ovarian cancer (EOC). We hypothesized that some of the missing heritability may be explained by rare (minor allele frequency (MAF) <0.5%) and low-frequency (MAF 0.5-5%) protein-coding variants that are not well captured by genotyping arrays that focus on common variants. Methods: To examine the association between uncommon variants and EOC susceptibility, we genotyped 7,060 EOC cases and 6,712 controls from the Ovarian Cancer Association Consortium using the Affymetrix Axiom Exome Genotyping Array. This platform contains 300,785 putative functional coding variants selected from exome sequences of 12,000+ individuals representing multiple ethnicities and complex traits. After performing quality control (QC), we used unconditional logistic regression treating the number of minor alleles carried as an ordinal variable (log-additive model) to evaluate SNP-EOC risk associations. Genotype cluster plots were visually inspected for top-ranking variants to determine assay success, and allele frequencies of samples from the 1000 Genomes Project and other cohorts were evaluated for QC purposes. Results: A total of 13,318 samples (97%) passed QC, and 12,779 eligible samples (6,293 invasive serous and endometrioid cases and 6,486 controls) were included in the analyses. 280,737 (93%) of the 300,785 attempted markers were successfully genotyped and had call rates >90%. After removing 31,436 monomorphic markers, the 249,301 remaining markers were included in association analyses. We confirmed variants at previously reported EOC susceptibility loci (9p22, 3q25, 17cen-q21.3, and 8q24), with p-values between 10-5 and 10-11. Several correlated low-frequency non-synonymous variants (MAF=5%) residing in a novel EOC susceptibility gene at 3q25.31 were risk-associated. The most significant variant at 3q25.31 had an OR=1.36 and p = 5.58x10-8. Also noteworthy is a rare variant at 15q15.1-q21.1 (MAF=0.5%) that introduces a stop codon in a gene belonging to the tyrosine kinase family (OR=0.39, CI=0.26-0.58, p = 4.52x10-6). We also identified a more common synonymous coding variant in a phosphatase at 6q21.3 that was associated with increased risk (OR=1.22, CI=1.13-1.33, p = 1.84x10-6, MAF=9.6%). Population stratification and gene-based analyses are underway to further examine the impact of the newly-identified variants on EOC risk. A meta-analysis to include data from an additional 2104 EOC cases and 2516 controls genotyped with Illumina's HumanExome Beadchip rare variant array is also underway. Functional analysis of the most promising variants will follow. Conclusions: Preliminary data from this large-scale study reveals novel rare and low-frequency variants that may influence susceptibility to epithelial ovarian cancer. Citation Format: Jennifer Permuth-Wey, Y. Ann Chen, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Simon Gayther, Ellen L. Goode, Edwin Iversen, Alvaro N.A. Monteiro, Leigh Pearce, Paul D.P. Pharoah, Catherine M. Phelan, Ailith Pirie, Susan Ramus, Mary Ann Rossing, Joellen M. Schildkraut, Thomas A. Sellers, on behalf of the Ovarian Cancer Association Consortium. Exome genotyping array identifies rare and low-frequency variants that may be associated with ovarian cancer risk. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 946. doi:10.1158/1538-7445.AM2014-946

Abstract Primary and acquired chemotherapy resistance remains a major challenge in the treatment of ovarian cancer. We hypothesize that heritable polymorphisms might be associated with clinical outcome. Through the Ovarian Cancer Association Consortium, we have collected detailed clinical data from a large number of ovarian cancer patients. We have conducted association analyses of progression-free survival (PFS) and overall survival (OS) for 2,901 European women with ovarian carcinoma for ∼8 million imputed SNPs with minor allele frequency ≥ 0.02 and good imputation quality (imputation r2 ≥ 0.3) from the iCOGS experiment (Pharoah et al Nat Genet. 2013). Cox regression models adjusted for known prognostic factors were used to assess the log-additive effects of SNPs on PFS and OS in 2,825 patients who underwent cytoreductive surgery and received any chemotherapy (‘all chemo’) and in the subset of 1,098 patients who underwent cytoreductive surgery followed by ≥ 4 cycles of carboplatin AUC 5 or 6 and paclitaxel 175 or 135 mg/m2 intravenously (‘standard chemo’). We identified five SNPs at four loci that were significantly associated with outcome (p ≤ 10-7) in at least one of four analyses (Table). Analysis of expression data for genes within a 1Mb region flanking each lead SNP indicates significant associations between nearby genes and ovarian cancer survival. Of particular interest is the heat shock protein crystalline αB (CRYAB) at 11q23.1. We have also identified significant associations with KIAA1598 and RAVER2. Further analysis of these loci in a larger genotyped sample is necessary to definitively identify SNP(s) associated with outcome. Our study adds to the growing evidence that genetic variants are associated with ovarian cancer prognosis. Table: SNPs associated with ovarian cancer outcome and gene expression Overall Survival (P)*Progression-Free Survival (P)*Lead SNPChromosome LocusImputation R²Expression AnalysisAll chemoStandard chemoAll chemoStandard chemors1429768671p31.30.742.14E-0512.69E-044.68E-055.11E-073.64E-09rs559375217q32.30.600.198.58E-082.32E-052.80E-031.85E-03rs7885346210q26.110.602.23E-0724.57E-036.57E-081.65E-016.85E-03rs1089121911q23.10.841.53E-0531.51E-059.50E-081.50E-042.32E-04rs3579103211q23.10.811.53E-0531.66E-055.88E-086.46E-051.87E-04*P-values are adjusted for known confounders of ovarian cancer outcomes; FIGO stage, grade, histology, residual disease, and additionally for age at diagnosis for OS.1 RAVER2; 2 KIAA1598; 3 CRYAB Citation Format: Sharon E. Johnatty, Jonathan Tyrer, Jonathan Beesley, Bo Gao, Yi Lu, Stuart MacGregor, Anna deFazio, Paul Pharoah, Ellen Goode, Georgia Chenevix-Trench. Identification of genetic loci associated with ovarian cancer prognosis. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3286. doi:10.1158/1538-7445.AM2014-3286

Abstract An ovarian cancer Genome Wide Association Study (GWAS) identified 9p22.2 as a novel susceptibility locus with the most statistically significant single nucleotide polymorphisms (SNPs) located in an intergenic region near the Basonuclin 2 (BNC2) gene, which codes for a putative transcription regulator containing three pairs of zinc finger (ZF) domains. The minor alleles are protective in terms of ovarian cancer susceptibility. However, the molecular mechanisms by which these SNPs modify susceptibility remain largely unknown. The significant SNPs in the 9p22.2 locus lie in non-coding regions and therefore are hypothesized to affect the activity of regulatory elements and modify the expression of a target gene(s). In order to test this hypothesis we conducted fine mapping for the locus which delimited a ∼74kb region containing SNPs with a p-value less than 10-8. FAIRE-Seq and ChIP-Seq experiments for histone markers conducted in immortalized ovarian surface epithelial cells (IOSE) and fallopian tube epithelial cells (IFTE) were used to prioritize functional SNP candidates which overlap with regulatory elements. Luciferase assays tested the ability of these regulatory elements to activate transcription. Chromosome conformation capture (3C) experiments demonstrate a physical interaction between the BNC2 promoter and candidate regulatory elements containing risk-associated SNPs. Methylation Quantification at Trait Loci (mQTL) revealed an association between decreased methylation at the BNC2 promoter and the protective minor alleles. Expression analysis shows decreased expression of BNC2 in cancer versus normal tissue implicating tumor suppressor function of BNC2. Therefore the protective minor allele likely increases expression of BNC2 which in turn contains tumor suppressing properties that decrease ovarian cancer risk. BNC2 protein is in complex with transcriptional regulatory proteins, in particular the NURD complex components. Moreover, BNC2 acts as a transcriptional repressor in in vitro transfection assays indicating that it functions in transcriptional repression. We then used protein binding microarrays and CHIP-Seq experiments to identify its putative DNA binding motifs and its downstream target genes. Analysis of this data suggests that BNC2 functions in a regulatory transcription network that impacts on genes implicated in ovarian cancer with enrichment for genes in the TGF-beta response pathway. Citation Format: Melissa A. Buckley, Howard C. Shen, Gustavo A. Mendoza-Fandino, Nicholas T. Woods, Anxhela Gjyshi, Juliet French, Kate Lawrenson, Honglin Song, Jonathan Tyrer, Renato S. Carvalho, Alexandra Valle, Ann Chen, Sean Yoder, Gregory Bloom, Ya-Yu Tsai, Ally Yang, Timothy R. Hughes, Xiaotao Qu, Mine Cicek, Melissa Larson, Ellen Goode, Brooke Fridley, Susan Ramus, Georgia Chenevix-Trench, Paul Pharoah, Thomas A. Sellers, Simon Gayther, Alvaro N.A. Monteiro, Ovarian Cancer Association Consortium. Functional analysis of the 9p22 locus implicates the transcriptional regulation of BNC2 as a mechanism in ovarian cancer predisposition. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3285. doi:10.1158/1538-7445.AM2014-3285

Abstract Background Genome-wide association studies (GWAS) previously identified 8 new risk loci for all subtypes of epithelial ovarian carcinoma (EOC) and one specific to invasive serous EOC. One locus, at 2q31, was also associated with invasive mucinous EOC (mEOC) at P=7.3 x 10-7 (Nat Genet 2010:874). Here, we report new risk loci for mEOC, which is thought to develop from a borderline mucinous tumor. These loci may provide clues to the molecular basis of the disease. Methods We used genotype data from 4 GWAS of EOC and from multiple case-control studies in the Ovarian Cancer Association Consortium that had been genotyped using the iCOGS custom SNP panel (210k SNPs) developed for the Collaborative Oncological Gene-environment Study. We imputed genotypes of common variation across the genome using the 1000 Genomes Project reference panel and tested for association using log-additive unconditional regression models. Results Genotypes were available for 1,643 combined invasive and borderline mEOC and for 1,002 invasive-only mEOC of European ancestry. Three loci in new regions, and one locus in a previously published region, with minor allele frequency (MAF) > 1% and P ≤ 10-7 were found. The imputed SNP rs72831838 (imputation r2=0.67, MAF=0.15) is located at 2q13 in an intron of the PAX8 (paired box 8) gene (all mEOC OR=1.35, P=4.2 x 10-8 and invasive-only OR=1.43, P=9.6 x 10-8). PAX8 is a transcription factor and may be a Müllerian lineage marker that distinguishes carcinomas of gynecologic origin from other sites. The imputed variant at chr19:39745695 (imputation r2=0.61, MAF=0.32) is an insertion/deletion polymorphism located at 19q13.2 and falls within the MSRB1P1 (methionine sulfoxide reductase B1 pseudogene 1). This locus was associated with decreased risk (all mEOC OR=0.74, P = 2.1 x 10-9 and invasive-only OR=0.79, P = 8.1 x 10-5) and is enriched with the H3K27Ac histone mark that identifies active enhancers of gene expression. The imputed SNP rs6425050 (imputation r2=0.45, MAF=0.19) is located at 1q25 (all mEOC OR=1.38, P=4.7 x 10-8 and invasive-only OR=1.41, P=1.6x10-6). This SNP is intronic to PLA2G4A (phospholipase A2, group IVA), which encodes an enzyme that hydrolyzes membrane phospholipids for eicosanoid metabolism and signaling. None of these loci were associated with other EOC histological subtypes at P ≤ 10-7. The genotyped SNP, rs711830 (MAF=0.32), is located at 2q31.1 in the 3′ region of the HOXD3 homeobox gene (all mEOC OR=1.30, P=7.5 x 10-12 and invasive-only OR=1.26, P=7.8 x 10-7). This SNP is highly correlated (r2=0.99) with rs2072590, which is located 5.3kb upstream and previously reported by us to be associated with mEOC and invasive serous EOC (Nat Genet 2010:874). The HOXD3 locus is highly conserved and may also be a marker of Müllerian cell type origin. Conclusions The 3 new loci for mEOC require confirmation by genotyping. Fine mapping and functional analysis of all loci is needed in order to determine their likely target genes. Citation Format: Linda E. Kelemen, Jonathan Tyrer, Catherine M. Phelan, Susan J. Ramus, Andrew Berchuck, Simon A. Gayther, Ellen L. Goode, Celeste L. Pearce, Joellen M. Schildkraut, Georiga Chenevix-Trench, Alvaro N. Monteiro, Marc T. Goodman, Thomas A. Sellers, Paul PD Pharoah. GWAS identifies risk variants for mucinous ovarian carcinoma. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3283. doi:10.1158/1538-7445.AM2014-3283

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 Background: Genome-wide association studies have identified multiple genetic variants associated with prostate cancer risk which explain a substantial proportion of familial relative risk. These variants can be used to stratify individuals by their risk of prostate cancer. Methods: We genotyped 25 prostate cancer susceptibility loci in 40,414 individuals and derived a polygenic risk score (PRS). We estimated empirical odds ratios (OR) for prostate cancer associated with different risk strata defined by PRS and derived age-specific absolute risks of developing prostate cancer by PRS stratum and family history. Results: The prostate cancer risk for men in the top 1% of the PRS distribution was 30.6 (95% CI, 16.4–57.3) fold compared with men in the bottom 1%, and 4.2 (95% CI, 3.2–5.5) fold compared with the median risk. The absolute risk of prostate cancer by age of 85 years was 65.8% for a man with family history in the top 1% of the PRS distribution, compared with 3.7% for a man in the bottom 1%. The PRS was only weakly correlated with serum PSA level (correlation = 0.09). Conclusions: Risk profiling can identify men at substantially increased or reduced risk of prostate cancer. The effect size, measured by OR per unit PRS, was higher in men at younger ages and in men with family history of prostate cancer. Incorporating additional newly identified loci into a PRS should improve the predictive value of risk profiles. Impact: We demonstrate that the risk profiling based on SNPs can identify men at substantially increased or reduced risk that could have useful implications for targeted prevention and screening programs. Cancer Epidemiol Biomarkers Prev; 24(7); 1121–9. ©2015 AACR.