Epigenome-wide ovarian cancer analysis identifies a methylation profile differentiating clear-cell histology with epigenetic silencing of the HERG K+ channel.

Ovarian cancer remains the leading cause of death in women with gynecologic malignancies, despite surgical advances and the development of more effective chemotherapeutics. As increasing evidence indicates that clear-cell ovarian cancer may have unique pathogenesis, further understanding of molecular features may enable us to begin to understand the underlying biology and histology-specific information for improved outcomes. To study epigenetics in clear-cell ovarian cancer, fresh frozen tumor DNA (n = 485) was assayed on Illumina Infinium HumanMethylation450 BeadChips. We identified a clear-cell ovarian cancer tumor methylation profile (n = 163) which we validated in two independent replication sets (set 1, n = 163; set 2, n = 159), highlighting 22 CpG loci associated with nine genes (VWA1, FOXP1, FGFRL1, LINC00340, KCNH2, ANK1, ATXN2, NDRG21 and SLC16A11). Nearly all of the differentially methylated CpGs showed a propensity toward hypermethylation among clear-cell cases. Several loci methylation inversely correlated with tumor gene expression, most notably KCNH2 (HERG, a potassium channel) (P = 9.5 × 10(-7)), indicating epigenetic silencing. In addition, a predicted methylation class mainly represented by the clear-cell cases (20 clear cell out of 23 cases) had improved survival time. Although these analyses included only 30 clear-cell carcinomas, results suggest that loss of expression of KCNH2 (HERG) by methylation could be a good prognostic marker, given that overexpression of the potassium (K(+)) channel Eag family members promotes increased proliferation and results in poor prognosis. Validation in a bigger cohort of clear-cell tumors of the ovary is warranted.

Identification of a novel percent mammographic density locus at 12q24.

Percent mammographic density adjusted for age and body mass index (BMI) is one of the strongest risk factors for breast cancer and has a heritable component that remains largely unidentified. We performed a three-stage genome-wide association study (GWAS) of percent mammographic density to identify novel genetic loci associated with this trait. In stage 1, we combined three GWASs of percent density comprised of 1241 women from studies at the Mayo Clinic and identified the top 48 loci (99 single nucleotide polymorphisms). We attempted replication of these loci in 7018 women from seven additional studies (stage 2). The meta-analysis of stage 1 and 2 data identified a novel locus, rs1265507 on 12q24, associated with percent density, adjusting for age and BMI (P = 4.43 × 10(-8)). We refined the 12q24 locus with 459 additional variants (stage 3) in a combined analysis of all three stages (n = 10 377) and confirmed that rs1265507 has the strongest association in the 12q24 region (P = 1.03 × 10(-8)). Rs1265507 is located between the genes TBX5 and TBX3, which are members of the phylogenetically conserved T-box gene family and encode transcription factors involved in developmental regulation. Understanding the mechanism underlying this association will provide insight into the genetics of breast tissue composition.

Genetic polymorphisms associated with carotid artery intima-media thickness and coronary artery calcification in women of the Kronos Early Estrogen Prevention Study.

Menopausal hormone treatment (MHT) may limit progression of cardiovascular disease (CVD) but poses a thrombosis risk. To test targeted candidate gene variation for association with subclinical CVD defined by carotid artery intima-media thickness (CIMT) and coronary artery calcification (CAC), 610 women participating in the Kronos Early Estrogen Prevention Study (KEEPS), a clinical trial of MHT to prevent progression of CVD, were genotyped for 13,229 single nucleotide polymorphisms (SNPs) within 764 genes from anticoagulant, procoagulant, fibrinolytic, or innate immunity pathways. According to linear regression, proportion of European ancestry correlated negatively, but age at enrollment and pulse pressure correlated positively with CIMT. Adjusting for these variables, two SNPs, one on chromosome 2 for MAP4K4 gene (rs2236935, ß = 0.037, P value = 2.36 × 10(-06)) and one on chromosome 5 for IL5 gene (rs739318, ß = 0.051, P value = 5.02 × 10(-05)), associated positively with CIMT; two SNPs on chromosome 17 for CCL5 (rs4796119, ß = -0.043, P value = 3.59 × 10(-05); rs2291299, ß = -0.032, P value = 5.59 × 10(-05)) correlated negatively with CIMT; only rs2236935 remained significant after correcting for multiple testing. Using logistic regression, when we adjusted for waist circumference, two SNPs (rs11465886, IRAK2, chromosome 3, OR = 3.91, P value = 1.10 × 10(-04); and rs17751769, SERPINA1, chromosome 14, OR = 1.96, P value = 2.42 × 10(-04)) associated positively with a CAC score of >0 Agatston unit; one SNP (rs630014, ABO, OR = 0.51, P value = 2.51 × 10(-04)) associated negatively; none remained significant after correcting for multiple testing. Whether these SNPs associate with CIMT and CAC in women randomized to MHT remains to be determined.

Genome-wide gene-set analysis for identification of pathways associated with alcohol dependence.

It is believed that multiple genetic variants with small individual effects contribute to the risk of alcohol dependence. Such polygenic effects are difficult to detect in genome-wide association studies that test for association of the phenotype with each single nucleotide polymorphism (SNP) individually. To overcome this challenge, gene-set analysis (GSA) methods that jointly test for the effects of pre-defined groups of genes have been proposed. Rather than testing for association between the phenotype and individual SNPs, these analyses evaluate the global evidence of association with a set of related genes enabling the identification of cellular or molecular pathways or biological processes that play a role in development of the disease. It is hoped that by aggregating the evidence of association for all available SNPs in a group of related genes, these approaches will have enhanced power to detect genetic associations with complex traits. We performed GSA using data from a genome-wide study of 1165 alcohol-dependent cases and 1379 controls from the Study of Addiction: Genetics and Environment (SAGE), for all 200 pathways listed in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results demonstrated a potential role of the 'synthesis and degradation of ketone bodies' pathway. Our results also support the potential involvement of the 'neuroactive ligand-receptor interaction' pathway, which has previously been implicated in addictive disorders. These findings demonstrate the utility of GSA in the study of complex disease, and suggest specific directions for further research into the genetic architecture of alcohol dependence.

No evidence for association of inherited variation in genes involved in mitosis and percent mammographic density.

INTRODUCTION: Increased mammographic breast density is one of the strongest risk factors for breast cancer. While two-thirds of the variation in mammographic density appears to be genetically influenced, few variants have been identified. We examined the association of inherited variation in genes from pathways that mediate cell division with percent mammographic density (PMD) adjusted for age, body mass index (BMI) and postmenopausal hormones, in two studies of healthy postmenopausal women. METHODS: We investigated 2,058 single nucleotide polymorphisms (SNPs) in 378 genes involved in regulation of mitosis for associations with adjusted PMD among 484 unaffected postmenopausal controls (without breast cancer) from the Mayo Clinic Breast Cancer Study (MCBCS) and replicated the findings in postmenopausal controls (n = 726) from the Singapore and Sweden Breast Cancer Study (SASBAC) study. PMD was assessed in both studies by a computer-thresholding method (Cumulus) and linear regression approaches were used to assess the association of SNPs and PMD, adjusted for age, BMI and postmenopausal hormones. A P-value threshold of 4.2 × 10-5 based on a Bonferroni correction of effective number of independent tests was used for statistical significance. Further, a pathway-level analysis was conducted of all 378 genes using the self-contained gene-set analysis method GLOSSI. RESULTS: A variant in PRPF4, rs10733604, was significantly associated with adjusted PMD in the MCBCS (P = 2.7 × 10-7), otherwise, no single SNP was associated with PMD. Additionally, the pathway analysis provided no evidence of enrichment in the number of associations observed between SNPs in the mitotic genes and PMD (P = 0.60). We evaluated rs10733604 (PRPF4), and 73 other SNPs at P < 0.05 from 51 genes in the SASBAC study. There was no evidence of an association of rs10733604 (PRPF4) with adjusted PMD in SASBAC (P = 0.23). There were, however, consistent associations (P < 0.05) of variants at the putative locus, LOC375190, Aurora B kinase (AURKB), and Mini-chromosome maintenance complex component 3 (MCM3) with adjusted PMD, although these were not statistically significant. CONCLUSIONS: Our findings do not support a role of inherited variation in genes involved in regulation of cell division and adjusted percent mammographic density in postmenopausal women.

SNPPicker: high quality tag SNP selection across multiple populations.

BACKGROUND: Linkage Disequilibrium (LD) bin-tagging algorithms identify a reduced set of tag SNPs that can capture the genetic variation in a population without genotyping every single SNP. However, existing tag SNP selection algorithms for designing custom genotyping panels do not take into account all platform dependent factors affecting the likelihood of a tag SNP to be successfully genotyped and many of the constraints that can be imposed by the user. RESULTS: SNPPicker optimizes the selection of tag SNPs from common bin-tagging programs to design custom genotyping panels. The application uses a multi-step search strategy in combination with a statistical model to maximize the genotyping success of the selected tag SNPs. User preference toward functional SNPs can also be taken into account as secondary criteria. SNPPicker can also optimize tag SNP selection for a panel tagging multiple populations. SNPPicker can optimize custom genotyping panels including all the assay-specific constraints of Illumina's GoldenGate and Infinium assays. CONCLUSIONS: A new application has been developed to maximize the success of custom multi-population genotyping panels. SNPPicker also takes into account user constraints including options for controlling runtime. Perl Scripts, Java source code and executables are available under an open source license for download at http://mayoresearch.mayo.edu/mayo/research/biostat/software.cfm.

Genomics of the NF-κB signaling pathway: hypothesized role in ovarian cancer.

OBJECTIVE: We sought to review evidence linking nuclear factor-kappa B (NF-κB) to ovarian cancer and to identify genetic variants involved in NF-κB signaling. METHODS: PubMed was reviewed to inform on ovarian cancer biology and NF-κB signaling and to identify key genes. Public linkage disequilibrium (LD) data were analyzed to identify informative inherited variants (tagSNPs) using ldSelect. RESULTS: We identified 319 key NF-κB genes including five NF-κB subunits, 167 activating genes, and 55 inhibiting genes. We found that the 1000 Genomes Project was the most informative LD source for most genes (92.8%), and we identified 13,027 LD bins (r (2) ≥ 0.9, minor allele frequency ≥ 0.05) and 1,018 putative-functional variants worthy of investigation. We also report that reliance on a commonly used genome-wide SNP array and genotype imputation with HapMap Phase II data provides data on only 74% of the common inherited NF-κB SNPs of interest. CONCLUSIONS: Compelling evidence suggests that NF-κB plays a critical role in ovarian cancer, yet inherited variation in these genes has not been thoroughly assessed in relation to disease risk or outcome. We present a collection of variants in key genes and suggest creation of a custom genotyping array as an optimal approach.

Variants in estrogen-related genes and risk of Parkinson's disease.

Incidence rates of Parkinson's disease are higher in men than in women at all ages, and these differences may be a result of the neuroprotective effects of estrogen on the nigrostriatal pathway. We investigated the association of common variants in 4 estrogen-related genes with Parkinson's disease. Tagging single-nucleotide polymorphisms in the CYP19A1, ESR1, ESR2, and PRDM2 genes were selected from the International Haplotype Map and genotyped in 1103 Parkinson's disease cases from the upper Midwest of the United States and in 1103 individually matched controls (654 unaffected siblings, and 449 unrelated controls from the same region). Of 137 informative single-nucleotide polymorphisms, 2 PRDM2 single-nucleotide polymorphisms were significantly associated with an increased risk of Parkinson's disease at the Bonferroni-corrected significance level of 0.0004 (rs2744690: OR, 1.54; SE(logOR), .109; 99.96% CI, 1.05-2.26; uncorrected P = .0001; rs2744687: OR, 1.53; SE(logOR), .113; 99.96% CI, 1.03-2.29, uncorrected P = .0002); the association was significant in the women-only stratum but not in the men-only stratum. An additional 6 single-nucleotide polymorphisms in PRDM2, 2 in ESR1, 1 in ESR2, and 1 in CYP19A1 had significant P values in the overall sample before Bonferroni correction. None of the single-nucleotide polymorphisms were significantly associated with age at onset of Parkinson's disease after Bonferroni correction. Our results confirm the association of PRDM2 variants with Parkinson's disease susceptibility, especially in women.

Common variants in PARK loci and related genes and Parkinson's disease.

Rare mutations in PARK loci genes cause Parkinson's disease (PD) in some families and isolated populations. We investigated the association of common variants in PARK loci and related genes with PD susceptibility and age at onset in an outbred population. A total of 1,103 PD cases from the upper Midwest, USA, were individually matched to unaffected siblings (n = 654) or unrelated controls (n = 449) from the same region. Using a sequencing approach in 25 cases and 25 controls, single nucleotide polymorphisms (SNPs) in species-conserved regions of PARK loci and related genes were detected. We selected additional tag SNPs from the HapMap. We genotyped a total of 235 SNPs and two variable number tandem repeats in the ATP13A2, DJ1, LRRK1, LRRK2, MAPT, Omi/HtrA2, PARK2, PINK1, SNCA, SNCB, SNCG, SPR, and UCHL1 genes in all 2,206 subjects. Case-control analyses were performed to study association with PD susceptibility, while cases-only analyses were used to study association with age at onset. Only MAPT SNP rs2435200 was associated with PD susceptibility after correction for multiple testing (OR = 0.74, 95% CI = 0.64-0.86, uncorrected P < 0.0001, log additive model); however, 16 additional MAPT variants, seven SNCA variants, and one LRRK2, PARK2, and UCHL1 variants each had significant uncorrected P-values. There were no significant associations for age at onset after correction for multiple testing. Our results confirm the association of MAPT and SNCA genes with PD susceptibility but show limited association of other PARK loci and related genes with PD.

Nucleotide excision repair pathway polymorphisms and pancreatic cancer risk: evidence for role of MMS19L.

BACKGROUND: Nucleotide excision repair is a vital response to DNA damage, including damage from tobacco exposure. Single nucleotide polymorphisms (SNP) in the nucleotide excision repair pathway may encode alterations that affect DNA repair function and therefore influence the risk of pancreatic cancer development. METHODS: A clinic-based case-control study in non-Hispanic white persons compared 1,143 patients with pancreatic adenocarcinoma with 1,097 healthy controls. Twenty-seven genes directly and indirectly involved in the nucleotide excision repair pathway were identified and 236 tag-SNPs were selected from 26 of these (one had no SNPs identified). Association studies were done at the gene level by principal components analysis, whereas recursive partitioning analysis was utilized to identify potential gene-gene and gene-environment interactions within the pathway. At the individual SNP level, adjusted additive, dominant, and recessive models were investigated, and gene-environment interactions were also assessed. RESULTS: Gene level analyses showed an association of the MMS19L genotype (chromosome 10q24.1) with altered pancreatic cancer risk (P = 0.023). Haplotype analysis of MMS19L also showed a significant association (P = 0.0132). Analyses of seven individual SNPs in this gene showed both protective and risk associations for minor alleles, broadly distributed across patient subgroups defined by smoking status, sex, and age. CONCLUSION: In a candidate pathway SNP association study analysis, common variation in a nucleotide excision repair gene, MMS19L, was associated with the risk of pancreatic cancer.

Candidate gene analysis using imputed genotypes: cell cycle single-nucleotide polymorphisms and ovarian cancer risk.

Polymorphisms in genes critical to cell cycle control are outstanding candidates for association with ovarian cancer risk; numerous genes have been interrogated by multiple research groups using differing tagging single-nucleotide polymorphism (SNP) sets. To maximize information gleaned from existing genotype data, we conducted a combined analysis of five independent studies of invasive epithelial ovarian cancer. Up to 2,120 cases and 3,382 controls were genotyped in the course of two collaborations at a variety of SNPs in 11 cell cycle genes (CDKN2C, CDKN1A, CCND3, CCND1, CCND2, CDKN1B, CDK2, CDK4, RB1, CDKN2D, and CCNE1) and one gene region (CDKN2A-CDKN2B). Because of the semi-overlapping nature of the 123 assayed tagging SNPs, we performed multiple imputation based on fastPHASE using data from White non-Hispanic study participants and participants in the international HapMap Consortium and National Institute of Environmental Health Sciences SNPs Program. Logistic regression assuming a log-additive model was done on combined and imputed data. We observed strengthened signals in imputation-based analyses at several SNPs, particularly CDKN2A-CDKN2B rs3731239; CCND1 rs602652, rs3212879, rs649392, and rs3212891; CDK2 rs2069391, rs2069414, and rs17528736; and CCNE1 rs3218036. These results exemplify the utility of imputation in candidate gene studies and lend evidence to a role of cell cycle genes in ovarian cancer etiology, suggest a reduced set of SNPs to target in additional cases and controls.

Polymorphisms in NF-kappaB inhibitors and risk of epithelial ovarian cancer.

BACKGROUND: The nuclear factor-kappaB (NF-kappaB) family is a set of transcription factors with key roles in the induction of the inflammatory response and may be the link between inflammation and cancer development. This pathway has been shown to influence ovarian epithelial tissue repair. Inhibitors of kappaB (IkappaB) prevent NF-kappaB activation by sequestering NF-kappaB proteins in the cytoplasm until IkappaB proteins are phosphorylated and degraded. METHODS: We used a case-control study to evaluate the association between single nucleotide polymorphisms (SNPs) in NFKBIA and NFKBIB (the genes encoding IkappaBalpha and IkappaBbeta, respectively) and risk of epithelial ovarian cancer. We queried 19 tagSNPs and putative-functional SNPs among 930 epithelial ovarian cancer cases and 1,037 controls from two studies. RESULTS: The minor allele for one synonymous SNP in NFKBIA, rs1957106, was associated with decreased risk (p = 0.03). CONCLUSION: Considering the number of single-SNP tests performed and null gene-level results, we conclude that NFKBIA and NFKBIB are not likely to harbor ovarian cancer risk alleles. Due to its biological significance in ovarian cancer, additional genes encoding NF-kappaB subunits, activating and inhibiting molecules, and signaling molecules warrant interrogation.

Polymorphisms in the FGF2 gene and risk of serous ovarian cancer: results from the ovarian cancer association consortium.

Fibroblast growth factor (FGF)-2 (basic) is a potent angiogenic molecule involved in tumor progression, and is one of several growth factors with a central role in ovarian carcinogenesis. We hypothesized that common single nucleotide polymorphisms (SNPs) in the FGF2 gene may alter angiogenic potential and thereby susceptibility to ovarian cancer. We analyzed 25 FGF2 tgSNPs using five independent study populations from the United States and Australia. Analysis was restricted to non-Hispanic White women with serous ovarian carcinoma (1269 cases and 2829 controls). There were no statistically significant associations between any FGF2 SNPs and ovarian cancer risk. There were two nominally statistically significant associations between heterozygosity for two FGF2 SNPs (rs308379 and rs308447; p < .05) and serous ovarian cancer risk in the combined dataset, but rare homozygous estimates did not achieve statistical significance, nor were they consistent with the log additive model of inheritance. Overall genetic variation in FGF2 does not appear to play a role in susceptibility to ovarian cancer.

Genetic variation in stromal proteins decorin and lumican with breast cancer: investigations in two case-control studies.

INTRODUCTION: The stroma is the supportive framework of biologic tissue in the breast, consisting of various proteins such as the proteoglycans, decorin and lumican. Altered expression of decorin and lumican is associated with breast tumors. We hypothesized that genetic variation in the decorin (DCN) and lumican (LUM) genes may contribute to breast cancer. METHODS: We investigated associations of 14 common polymorphisms in the DCN and LUM genes with 798 breast cancer cases and 843 controls from Mayo Clinic, MN, USA. One polymorphism per gene with the strongest risk association in the Mayo Clinic sample was genotyped in 4,470 breast cancer cases and 4,560 controls from East Anglia, England (Studies of Epidemiology and Risk Factors in Cancer Heredity (SEARCH)). RESULTS: In the Mayo Clinic sample, six polymorphisms were associated with breast cancer risk (P trend

Association of genetic variation in genes implicated in the beta-catenin destruction complex with risk of breast cancer.

Aberrant Wnt/beta-catenin signaling leading to nuclear accumulation of the oncogene product beta-catenin is observed in a wide spectrum of human malignancies. The destruction complex in the Wnt/beta-catenin pathway is critical for regulating the level of beta-catenin in the cytoplasm and in the nucleus. Here, we report a comprehensive study of the contribution of genetic variation in six genes encoding the beta-catenin destruction complex (APC, AXIN1, AXIN2, CSNK1D, CSNK1E, and GSK3B) to breast cancer using a Mayo Clinic Breast Cancer Case-Control Study. A total of 79 candidate functional and tagging single nucleotide polymorphisms (SNP) were genotyped in 798 invasive cases and 843 unaffected controls. Of these, rs454886 in the APC tumor suppressor gene was associated with increased breast cancer risk (per allele odds ratio, 1.23; 95% confidence intervals, 1.05-1.43; P(trend) = 0.01). In addition, five SNPs in AXIN2 were associated with increased risk of breast cancer (P(trend) < 0.05). Haplotype-based tests identified significant associations between specific haplotypes in APC and AXIN2 (P < or = 0.03) and breast cancer risk. Further characterization of the APC and AXIN2 variants suggested that AXIN2 rs4791171 was significantly associated with risk in premenopausal (P(trend) = 0.0002) but not in postmenopausal women. The combination of our findings and numerous genetic and functional studies showing that APC and AXIN2 perform crucial tumor suppressor functions suggest that further investigation of the contribution of AXIN2 and APC SNPs to breast cancer risk are needed.

Association of Common Susceptibility Variants of Pancreatic Cancer in Higher-Risk Patients: A PACGENE Study.

Individuals from pancreatic cancer families are at increased risk, not only of pancreatic cancer, but also of melanoma, breast, ovarian, and colon cancers. While some of the increased risk may be due to mutations in high-penetrance genes (i.e., BRCA2, PALB2, ATM, p16/CDKN2A or DNA mismatch repair genes), common genetic variants may also be involved. In a high-risk population of cases with either a family history of pancreatic cancer or early-onset pancreatic cancer (diagnosis before the age of 50 years), we examined the role of genetic variants previously associated with risk of pancreatic, breast, ovarian, or prostate cancer. We genotyped 985 cases (79 early-onset cases, 906 cases with a family history of pancreatic cancer) and 877 controls for 215,389 SNPs using the iSelect Collaborative Oncological Gene-Environment Study (iCOGS) array with custom content. Logistic regression was performed using a log-linear additive model. We replicated several previously reported pancreatic cancer susceptibility loci, including recently identified variants on 2p13.3 and 7p13 (2p13.3, rs1486134: OR = 1.36; 95% CI, 1.13-1.63; P = 9.29 × 10(-4); 7p13, rs17688601: OR = 0.76; 95% CI, 0.63-0.93; P = 6.59 × 10(-3)). For the replicated loci, the magnitude of association observed in these high-risk patients was similar to that observed in studies of unselected patients. In addition to the established pancreatic cancer loci, we also found suggestive evidence of association (P < 5 × 10(-5)) to pancreatic cancer for SNPs at HDAC9 (7p21.1) and COL6A2 (21q22.3). Even in high-risk populations, common variants influence pancreatic cancer susceptibility. Cancer Epidemiol Biomarkers Prev; 25(7); 1185-91. ©2016 AACR.

A targeted genetic association study of epithelial ovarian cancer susceptibility.

BACKGROUND: Genome-wide association studies have identified several common susceptibility alleles for epithelial ovarian cancer (EOC). To further understand EOC susceptibility, we examined previously ungenotyped candidate variants, including uncommon variants and those residing within known susceptibility loci. RESULTS: At nine of eleven previously published EOC susceptibility regions (2q31, 3q25, 5p15, 8q21, 8q24, 10p12, 17q12, 17q21.31, and 19p13), novel variants were identified that were more strongly associated with risk than previously reported variants. Beyond known susceptibility regions, no variants were found to be associated with EOC risk at genome-wide statistical significance (p <5x10(-8)), nor were any significant after Bonferroni correction for 17,000 variants (p< 3x10-6). METHODS: A customized genotyping array was used to assess over 17,000 variants in coding, non-coding, regulatory, and known susceptibility regions in 4,973 EOC cases and 5,640 controls from 13 independent studies. Susceptibility for EOC overall and for select histotypes was evaluated using logistic regression adjusted for age, study site, and population substructure. CONCLUSION: Given the novel variants identified within the 2q31, 3q25, 5p15, 8q21, 8q24, 10p12, 17q12, 17q21.31, and 19p13 regions, larger follow-up genotyping studies, using imputation where necessary, are needed for fine-mapping and confirmation of low frequency variants that fall below statistical significance.

The association of copy number variation and percent mammographic density.

BACKGROUND: Percent mammographic density (PD) estimates the proportion of stromal, fat, and epithelial breast tissues on the mammogram image. Adjusted for age and body mass index (BMI), PD is one of the strongest risk factors for breast cancer. Inherited factors are hypothesized to explain between 30 and 60% of the variance in this trait. However, previously identified common genetic variants account for less than 6% of the variance in PD, leaving much of the genetic contribution to this trait unexplained. We performed the first study to examine whether germline copy number variation (CNV) are associated with PD. Two genome-wide association studies (GWAS) of percent density conducted on the Illumina 660W-Quad were used to identify and replicate the association between candidate CNVs and PD: the Minnesota Breast Cancer Family Study (MBCFS) and controls from the Mayo Venous Thromboembolism (Mayo VTE) Case-Control Study, with 585 and 328 women, respectively. Linear models were utilized to examine the association of each probe with PD, adjusted for age, menopausal status and BMI. Segmentation was subsequently performed on the probe-level test statistics to identify candidate CNV regions that were associated with PD. RESULTS: Sixty-one probes from five chromosomal regions [3q26.1 (2 regions), 8q24.22, 11p15.3, and 17q22] were significantly associated with PD in MBCFS (p-values <0.0001). A CNV at 3q26.1 showed the greatest evidence for association with PD; a region without any known SNPs. Conversely, the CNV at 17q22 was largely due to the association between SNPs and PD in the region. SNPs in the 8q24.22 region have been shown to be associated with risk of many cancers; however, SNPs in this region were not responsible for the observed CNV association. While we were unable to replicate the associations with PD, two of the five CNVs (3q26.1 and 11p15.3) were also observed in the Mayo VTE controls. CONCLUSIONS: CNVs may help to explain some of the variability in PD that is currently unexplained by SNPs. While we were able to replicate the existence of two CNVs across the two GWAS studies, we were unable to replicate the associations with PD. Even so, the proximity of the identified CNV regions to loci known to be associated with breast cancer risk suggests further investigation and potentially shared genetic mechanisms underlying the PD and breast cancer association.

Cross Cancer Genomic Investigation of Inflammation Pathway for Five Common Cancers: Lung, Ovary, Prostate, Breast, and Colorectal Cancer.

BACKGROUND: Inflammation has been hypothesized to increase the risk of cancer development as an initiator or promoter, yet no large-scale study of inherited variation across cancer sites has been conducted. METHODS: We conducted a cross-cancer genomic analysis for the inflammation pathway based on 48 genome-wide association studies within the National Cancer Institute GAME-ON Network across five common cancer sites, with a total of 64 591 cancer patients and 74 467 control patients. Subset-based meta-analysis was used to account for possible disease heterogeneity, and hierarchical modeling was employed to estimate the effect of the subcomponents within the inflammation pathway. The network was visualized by enrichment map. All statistical tests were two-sided. RESULTS: We identified three pleiotropic loci within the inflammation pathway, including one novel locus in Ch12q24 encoding SH2B3 (rs3184504), which reached GWAS significance with a P value of 1.78 x 10(-8), and it showed an association with lung cancer (P = 2.01 x 10(-6)), colorectal cancer (GECCO P = 6.72x10(-6); CORECT P = 3.32x10(-5)), and breast cancer (P = .009). We also identified five key subpathway components with genetic variants that are relevant for the risk of these five cancer sites: inflammatory response for colorectal cancer (P = .006), inflammation related cell cycle gene for lung cancer (P = 1.35x10(-6)), and activation of immune response for ovarian cancer (P = .009). In addition, sequence variations in immune system development played a role in breast cancer etiology (P = .001) and innate immune response was involved in the risk of both colorectal (P = .022) and ovarian cancer (P = .003). CONCLUSIONS: Genetic variations in inflammation and its related subpathway components are keys to the development of lung, colorectal, ovary, and breast cancer, including SH2B3, which is associated with lung, colorectal, and breast cancer.

Methylation of leukocyte DNA and ovarian cancer: relationships with disease status and outcome.

BACKGROUND: Genome-wide interrogation of DNA methylation (DNAm) in blood-derived leukocytes has become feasible with the advent of CpG genotyping arrays. In epithelial ovarian cancer (EOC), one report found substantial DNAm differences between cases and controls; however, many of these disease-associated CpGs were attributed to differences in white blood cell type distributions. METHODS: We examined blood-based DNAm in 336 EOC cases and 398 controls; we included only high-quality CpG loci that did not show evidence of association with white blood cell type distributions to evaluate association with case status and overall survival. RESULTS: Of 13,816 CpGs, no significant associations were observed with survival, although eight CpGs associated with survival at p < 10-3, including methylation within a CpG island located in the promoter region of GABRE (p = 5.38 x 10-5, HR = 0.95). In contrast, 53 CpG methylation sites were significantly associated with EOC risk (p <5 x10-6). The top association was observed for the methylation probe cg04834572 located approximately 315 kb upstream of DUSP13 (p = 1.6 x10-14). Other disease-associated CpGs included those near or within HHIP (cg14580567; p =5.6x10-11), HDAC3 (cg10414058; p = 6.3x10-12), and SCR (cg05498681; p = 4.8x10-7). CONCLUSIONS: We have identified several CpGs in leukocytes that are differentially methylated by case-control status. Since a retrospective study design was used, we cannot differentiate whether DNAm was etiologic or resulting from EOC; thus, prospective studies of EOC-associated loci are the critical next step.