Citations

ABSTRACTEpithelial‐mesenchymal transition (EMT) is a process whereby epithelial cells assume mesenchymal characteristics to facilitate cancer metastasis. However, EMT also contributes to the initiation and development of primary tumors. Prior studies that explored the hypothesis that EMT gene variants contribute to epithelial ovarian carcinoma (EOC) risk have been based on small sample sizes and none have sought replication in an independent population. We screened 15,816 single‐nucleotide polymorphisms (SNPs) in 296 genes in a discovery phase using data from a genome‐wide association study of EOC among women of European ancestry (1,947 cases and 2,009 controls) and identified 793 variants in 278 EMT‐related genes that were nominally (P < 0.05) associated with invasive EOC. These SNPs were then genotyped in a larger study of 14,525 invasive‐cancer patients and 23,447 controls. A P‐value <0.05 and a false discovery rate (FDR) <0.2 were considered statistically significant. In the larger dataset, GPC6/GPC5 rs17702471 was associated with the endometrioid subtype among Caucasians (odds ratio (OR) = 1.16, 95% CI = 1.07–1.25, P = 0.0003, FDR = 0.19), whereas F8 rs7053448 (OR = 1.69, 95% CI = 1.27–2.24, P = 0.0003, FDR = 0.12), F8 rs7058826 (OR = 1.69, 95% CI = 1.27–2.24, P = 0.0003, FDR = 0.12), and CAPN13 rs1983383 (OR = 0.79, 95% CI = 0.69–0.90, P = 0.0005, FDR = 0.12) were associated with combined invasive EOC among Asians. In silico functional analyses revealed that GPC6/GPC5 rs17702471 coincided with DNA regulatory elements. These results suggest that EMT gene variants do not appear to play a significant role in the susceptibility to EOC.

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 Background: Unnecessary intervention and overtreatment of indolent disease are common challenges in clinical management of prostate cancer. Improved tools to distinguish lethal from indolent disease are critical. Methods: We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR). Results: We observed no significant association between genetic variants and prostate cancer survival. Conclusions: Common genetic variants with large impact on prostate cancer survival were not observed in this study. Impact: Future studies should be designed for identification of rare variants with large effect sizes or common variants with small effect sizes. Cancer Epidemiol Biomarkers Prev; 24(11); 1796–800. ©2015 AACR.

Abstract The known genetic variance for epithelial ovarian cancer (EOC) accounts for less than half the familial risks of the disease. BRCA1 and BRCA2 are the major high-penetrance EOC susceptibility genes. More recently genes that interact with BRCA1 and BRCA2 in the same biological pathways, but conferring more moderate penetrance (e.g. RAD51C, RAD51D) have also been identified. Mutations in these genes result in defects in homologous recombination and double strand break repair (HR/DSB). We hypothesized that other genes operating in these and other DNA repair pathways may also confer EOC susceptibility. Whole exome sequencing data, available from more than 400 high-grade serous ovarian cancers, were used to identify 24 candidate genes harboring germline truncating mutations in at least 2 cases, followed by replication analysis using targeted resequencing in ~3,000 cases and 3,000 controls. Subjects were also sequenced for the known susceptibility genes listed above. The data confirmed the previously reported contributions of BRCA1, BRCA2, RAD51C and RAD51D to EOC. In addition, we identified BRIP1, and FANCM as candidate EOC susceptibility genes. Surprisingly, for several genes we found truncating mutations were equally prevalent in cases as they were in controls. These mutations may still represent rare low-penetrance susceptibility alleles for EOC, which we are too limited in sample size and power to confirm; or more likely, it indicates that cells can tolerate heterozygous loss-of-function mutations in apparently critical DNA repair genes without any impact on neoplastic development. These findings may have implications for risk prediction and prevention strategies for EOC and possibly for the identification of novel therapeutic targets. Citation Format: Susan J. Ramus, Honglin Song, Ed Dicks, Maria Intermaggio, Jane Hayward, Jonathan P. Tyrer, Jacek Gronwald, Susanne Krüger Kjær, Alice Wittemore, Beth Karlan, Kunle Odunsi, Usha Menon, David D. Bowtell, Ellen L. Goode, Paul D.P. Pharoah, Simon A. Gayther. Whole exome and targeted resequencing, of population based ovarian cancer cases and controls, identifies susceptibility genes for ovarian cancer [abstract]. In: Proceedings of the 10th Biennial Ovarian Cancer Research Symposium; Sep 8-9, 2014; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(16 Suppl):Abstract nr POSTER-CTRL-1213.

Abstract Background: We investigated the role of multifactor interactions and epithelial ovarian cancer (EOC) risk using data collected within the Collaborative Oncological Gene-environment Study and the Ovarian Cancer Association Consortium containing 18,000 EOC cases and 26,000 controls. To date, researchers have identified 18 EOC susceptibility loci. However, it has been estimated that many more common variant loci exist; we hypothesized that some of the unexplained variation is due to gene-environment interactions. Similar to breast and endometrial cancers, many EOC risk factors relate to estrogen exposure, and increased levels of estrogen has been associated with obesity in post-menopausal women. Therefore, we hypothesized that gene-environment interactions dealing with hormone-related risk factors could differ between obese and non-obese women. Methods: We considered multifactor interactions between single nucleotide polymorphisms (SNPs) and six hormone-related factors: oral contraceptive use; parity; endometriosis; tubal ligation; hormone replacement therapy (HRT); and estrogen use; and assessed whether these GE interactions differed between obese and non-obese women. The SNPs included in this analysis included the top associated markers within the 18 confirmed risk loci, as well as, 36,811 SNPs that lie within 84 candidate gene regions related to hormone biosynthesis & metabolism and insulin-like growth factors. For the candidate SNP analyses, we assessed multifactor interactions across environmental factors using logistic regression models including age, study site, and population substructure. For the candidate gene analyses, a two-stage screening and testing procedure was utilized. All analyses were completed including: (1) all histologies; and (2) only serous histology. Results: For the 18 known EOC risk loci, no hormone-related risk factors showed statistically significant interaction at a threshold of 10-4. In contrast, the two-stage analysis of the candidate genes found several significant gene-environment-environment effects, after adjusting for multiple testing. For analysis of all cases, the SNPs in the following candidate genes showed a multifactor interaction with a hormone-related risk factor and obesity: IGFBP5 (HRT, rs729597, p = 1.3×10-13), CGA (HRT, rs58124219, p = 1.0×10-5), and SSTR1 (parity, rs77266093, p = 1.1×10-5). Similarly, the serous histology analyses detected a multifactor interaction with HRT, obesity and IGFBP5 (rs729597, p = 8.8×10-5). Additionally, serous only analyses also detected an interaction involving ESR1 (tubal ligation, Chr6:152246911(indel), p = 8.0×10-6). Conclusions: In a very large case-control collection, assessment of multifactor gene-environment interaction is feasible, and, here, suggest that the relationship between SNPs in candidate genes and hormone-related risk factors in EOC susceptibility may vary. Citation Format: Joseph Usset, Brooke Fridley, Ellen Goode, Joellen Schildkraut, Paul Pharoah. Assessment of multifactor gene-environment interactions and ovarian cancer risk: SNPs, obesity, and hormone-related risk factors. [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 4684. doi:10.1158/1538-7445.AM2015-4684

Abstract Background: Recent bioinformatic analyses and high-throughput sequencing efforts have revealed that RNA editing is a widespread post-transcriptional modification that affects non-coding repetitive elements throughout the genome. This modification, which involves the conversion of adenosine into inosine, is mediated by the action of the adenosine deaminases acting on RNA (ADAR) family of enzymes. Based on reports of dysfunctional ADAR expression in epithelial ovarian cancers (EOC), we hypothesized that single nucleotide polymorphisms (SNPs) in five ADAR genes (ADAD1, ADAR1, ADAR2, ADAR3, SND1) may contribute to EOC susceptibility, potentially by altering the expression of corresponding genes in ovarian tissues. Methods: Using directly genotyped and imputed data from 10,891 invasive EOC cases and 21,693 healthy controls of European ancestry represented in the international Collaborative Oncological Gene-environment Study, we evaluated the frequency of 7,133 SNPs in 5 RNA editing genes. Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) between genotypes and case status under a log-additive genetic model, with adjustment for the first five principal components representing European ancestry. Subgroup analysis was conducted for the four main histologic sub-types of EOC. We also aggregated SNP-level data and conducted gene-level analyses using the Admixture Maximum Likelihood (AML) test and the Sequence-Kernel Association test for the combined effect of common and rare variants (SKAT-CR). Results: Association analysis revealed a top risk-associated SNP (OR (95% CI) = 1.39 (1.17-1.64)) in ADAR3 with P = 1.3 x10−4, 17 additional SNPs in ADAR1, ADAR3, or SND1 with P = 10−4, and 51 SNPs with P = 10−3; this observed number of statistically-significant SNPs was greater than expected. When restricting to the 6,500 invasive serous adenocarcinomas, the magnitude of association strengthened for numerous SNPs. Exploratory analysis for the less common histologic subtypes (endometrioid (n = 1,439), mucinous (n = 696), and clear cell (n = 660)) revealed SNP-level associations (P&lt;10−3) unique to each sub-type. Gene-level analyses based on AML and SKAT-CR revealed that ADAR1 was globally associated (P&lt;0.10) with susceptibility to invasive EOC, with P = 0.024 and P = 0.023, respectively. Expression quantitative trait locus analysis is underway to evaluate associations between genotype and gene expression in EOC and precursor tissues using data from The Cancer Genome Atlas Project and other sources. Conclusions: Preliminary data from this large-scale collaboration suggest that germline variation involving RNA editing genes may influence susceptibility to EOC. This novel finding warrants further investigation, as inherited and acquired alterations affecting RNA editing may serve as important biological mechanisms that promote the development of EOC and possibly other malignancies. Citation Format: Jennifer Permuth-Wey, Brett M. Reid, Y. Ann Chen, Hui-Yi Lin, Alvaro Monteiro, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Simon Gayther, Ellen Goode, Edwin Iversen, Leigh Pearce, Paul D. P. Pharoah, Catherine Phelan, Susan Ramus, Mary Anne Rossing, Joellen Schildkraut, Thomas Sellers, on behalf of the Ovarian Cancer Association Consortium. Inherited variants affecting RNA editing may contribute to ovarian cancer susceptibility. [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 4635. doi:10.1158/1538-7445.AM2015-4635

Abstract Background: Cell-type-specific super enhancers, or large clusters of mediator-rich enhancers, are highly transcribed regions of the genome with key functions in the maintenance of cell identity and control. These regulatory elements are easily perturbed and enriched for disease-associated sequence variation. Identification of disease-associated super-enhancers and investigation of their sequence variants may help identify important, biologically relevant associations previously overlooked by genome-wide studies. Thus, we sought to identify variants within ovarian tissue specific super-enhancers and investigate their association with epithelial ovarian cancer (EOC) susceptibility. Methods: We utilized genotype data from a European population of ∼11,000 invasive EOC cases and 22,000 healthy controls from the Ovarian Cancer Association Consortium. A public catalog of 478 super-enhancers, identified by peak histone H3K27ac ChIP-seq signal in ovarian tissue, was used to identify 72,116 variants located within 344 super-enhancer regions. Unconditional logistic regression (log-additive model) was used to assess individual SNP-EOC risk associations. Additionally, we reviewed associations within 500 kb of super-enhancer regions to identify proximal associated variants. When LD structure indicated, we employed conditional analysis to determine independence of the super-enhancer signal. Gene-EOC risk associations were assessed with the Admixture Maximum Likelihood (AML) test and Sequence-Kernel Association Test (SKAT) for the combined effect of common and rare (MAF&lt;0.01) variants. Models were adjusted for population stratification using the first five principal components. To adjust for multiple comparisons, a false discovery rate of 10% was used. Results: The most significant SNP observed was rs147487657 (p = 7.7×10−6) on locus 2q37.3 in the HDAC4 gene and there were an additional 12 SNPs with p&lt;1.0×10−4, although not significant at 10% FDR. Gene-level analyses identified two super-enhancers significantly associated with EOC risk. An enhancer at the previously reported 2q31 locus, containing HOXD8 and HOXD-AS2, associated (SKAT p = 4.3×10−5; AML p&lt;0.001) with the top SNP located within the 5′UTR of HOXD8 transcription factor (rs847163 (T&gt;C); p&lt;2.08×10−5). Conditional analysis did not identify an independent association within the super-enhancer region. The second EOC-associated super-enhancer identified was at locus 1q32 (SKAT p = 0.00052, AML p = 0.001) containing the CSRP1 gene. There were 6 SNPs with p&lt;0.001 and 16 SNPs with p&lt;0.01, all were inversely associated with risk and consistent with the top hit at rs927901 T&gt;C (OR = 0.94; 95% CI: 0.90-0.97; p = 2.1×10−4). Associations varied by histologic subtype, possibly due to variance in disease relevant super-enhancer cell-type.Conclusion: These findings suggest germline variation within super-enhancer regions may contribute to EOC susceptibility Citation Format: Brett M. Reid, Jennifer Permuth-Wey, Y. Ann Chen, Hui-Yi Lin, Alvaro Monteiro, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Simon Gayther, Ellen L. Goode, Edwin Iversen, Leigh Pearce, Paul Pharoah, Catherine Phelan, Susan Ramus, Mary Anne Rossing, Joellen Schildkraut, Thomas Sellers, on behalf of the Ovarian Cancer Association Consortium. Variants within super-enhancer regulatory elements associate with epithelial ovarian cancer risk. [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 4634. doi:10.1158/1538-7445.AM2015-4634

Abstract Background: Genome wide association studies (GWAS) have identified 20 loci associated with epithelial ovarian cancer (EOC) risk. Additional EOC risk loci await identification, and biological approaches may represent a useful strategy for overcoming sample size limitations. The ENCODE project recently concluded that only ∼1.2% of the genome encodes proteins, but at least 20% exhibits biological function and over 80% exhibits biochemical indices of function. Post-GWAS follow-up studies have firmly established that some associations are due to inter-individual differences in non-coding RNAs (ncRNAs). To estimate the magnitude of impact of variants in long non-coding RNAs (lncRNAs), we assessed enrichment of EOC-associated SNPs in lncRNA regions by comparing the density of EOC-associated loci between lncRNA regions, non-lncRNA regions, and the whole genome. Methods: The study population included ∼18,000 invasive EOC cases and 34,000 healthy controls of European ancestry from the Ovarian Cancer Association Consortium with GWAS data imputed to 1000 Genomes Project (1KGP) density. Density was compared with two measures: average chromosome length required for one EOC-associated SNP (kb/locus) and average number of tested SNPs containing one EOC-associated SNP (SNPs/locus). Coordinates and annotation for 13,870 lncRNA genes were downloaded from the publicly available GENCODE (v19) database and were used to annotate SNPs from the 1KGP imputed GWAS data, yielding 13,192 lncRNA genes with biallelic variants imputed at rsquare ≥0.25. A SNP was considered EOC-associated if it reached a significance level of P&lt;10−5. Results: Genome-wide, 11.6% of the 15,123,646 tested SNPs fell within lncRNA regions. Of 5,294 EOC-associated SNPs that were identified, 27.7% were located within lncRNAs, a higher frequency than expected (&lt;v:shape style = “WIDTH: 16.5pt; HEIGHT: 18pt” id = _x0000_i1026 equationxml = ‘14pχ2′ type = “#_x0000_t75”&gt; = 9.35×10−22). Additionally, EOC-associated SNPs were located on average every 237.6 kb (or 1204 tested SNPs) in lncRNA regions versus every 657.7 kb (or 3489 SNPS) in non-lncRNA regions and every 541.5 kb (or 2857 SNPs) in the whole genome, clearly demonstrating an enrichment of EOC-associated loci in lncRNA regions. A total of 1,464 lncRNA SNPs from 53 unique lncRNAs associated with EOC risk (P&lt;10−5); 70 of the identified lncRNA SNPs had P-values between 10−20 and 10−32, and 221 had P-values between 10−10 and 10−15, representing 21 unique regions &gt; 500kb apart. Conclusions: These results justify efforts to integrate functional and population level genetic data on lncRNA regions to explore a new paradigm that addresses the problem of the missing heritability for cancer where restrictions in sample size and statistical power limit the ability to discover additional risk loci. Citation Format: Thomas A. Sellers, Brett M. Reid, Y. Ann Chen, Hui-Yi Lin, Edward Richards, Jamie Teer, Alvaro Monteiro, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Ellen Goode, Edwin Iverson, Leigh Pearce, Paul Pharoah, Catherine Phelan, Susan Ramus, Mary Anne Rossing, Joellen Schildkraut, Jin Cheng, Simon Gayther, Jennifer Permuth-Wey, on behalf of the Ovarian Cancer Association Consortium. Evidence that long non-coding RNA variants associate with epithelial ovarian cancer risk. [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 4633. doi:10.1158/1538-7445.AM2015-4633

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&gt;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&lt;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