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The human fecal and oral microbiome may play a role in the etiology of breast cancer through modulation of endogenous estrogen metabolism. This study aimed to investigate associations of circulating estrogens and estrogen metabolites with the fecal and oral microbiome in postmenopausal African women. A total of 117 women with fecal (N = 110) and oral (N = 114) microbiome data measured by 16S rRNA gene sequencing, and estrogens and estrogen metabolites data measured by liquid chromatography tandem mass spectrometry were included. The outcomes were measures of the microbiome and the independent variables were the estrogens and estrogen metabolites. Estrogens and estrogen metabolites were associated with the fecal microbial Shannon index (global P

The oral microbiome, like the fecal microbiome, may be related to breast cancer risk. Therefore, we investigated whether the oral microbiome was associated with breast cancer and nonmalignant breast disease, and its relationship with the fecal microbiome in a case-control study in Ghana. A total of 881 women were included (369 breast cancers, 93 nonmalignant cases and 419 population-based controls). The V4 region of the 16S rRNA gene was sequenced from oral and fecal samples. Alpha-diversity (observed amplicon sequence variants [ASVs], Shannon index and Faiths Phylogenetic Diversity) and beta-diversity (Bray-Curtis, Jaccard and weighted and unweighted UniFrac) metrics were computed. MiRKAT and logistic regression models were used to investigate the case-control associations. Oral sample alpha-diversity was inversely associated with breast cancer and nonmalignant breast disease with odds ratios (95% CIs) per every 10 observed ASVs of 0.86 (0.83-0.89) and 0.79 (0.73-0.85), respectively, compared to controls. Beta-diversity was also associated with breast cancer and nonmalignant breast disease compared to controls (P ≤ .001). The relative abundances of Porphyromonas and Fusobacterium were lower for breast cancer cases compared to controls. Alpha-diversity and presence/relative abundance of specific genera from the oral and fecal microbiome were strongly correlated among breast cancer cases, but weakly correlated among controls. Particularly, the relative abundance of oral Porphyromonas was strongly, inversely correlated with fecal Bacteroides among breast cancer cases (r = -.37, P ≤ .001). Many oral microbial metrics were strongly associated with breast cancer and nonmalignant breast disease, and strongly correlated with fecal microbiome among breast cancer cases, but not controls.

BackgroundPostmenopausal pregnenolone and/or progesterone levels in relation to endometrial and ovarian cancer risks have been infrequently evaluated. To address this, we utilized a sensitive and reliable assay to quantify prediagnostic levels of seven markers related to endogenous hormone metabolism.MethodsHormones were quantified in baseline serum collected from postmenopausal women in a cohort study nested within the Breast and Bone Follow-up to the Fracture Intervention Trial (B∼FIT). Women using exogenous hormones at baseline (1992-1993) were excluded. Incident endometrial (n = 65) and ovarian (n = 67) cancers were diagnosed during 12 follow-up years and compared with a subcohort of 345 women (no hysterectomy) and 413 women (no oophorectomy), respectively. Cox models with robust variance were used to estimate cancer risk.ResultsCirculating progesterone levels were not associated with endometrial [tertile (T)3 vs. T1 HR (95% confidence interval): 1.87 (0.85-4.11); P trend = 0.17] or ovarian cancer risk [1.16 (0.58-2.33); 0.73]. Increasing levels of the progesterone-to-estradiol ratio were inversely associated with endometrial cancer risk [T3 vs. T1: 0.29 (0.09-0.95); 0.03]. Increasing levels of 17-hydroxypregnenolone were inversely associated with endometrial cancer risk [0.40 (0.18-0.91); 0.03] and positively associated with ovarian cancer risk [3.11 (1.39-6.93); 0.01].ConclusionsUsing sensitive and reliable assays, this study provides novel data that endogenous progesterone levels are not strongly associated with incident endometrial or ovarian cancer risks. 17-hydroxypregnenolone was positively associated with ovarian cancer and inversely associated with endometrial cancer.ImpactWhile our results require replication in large studies, they provide further support of the hormonal etiology of endometrial and ovarian cancers.

BackgroundThe role of progestogens in colorectal cancer development is poorly characterized. To address this, our group developed a highly sensitive assay to measure concentrations of seven markers of endogenous progestogen metabolism among postmenopausal women.MethodsThe markers were measured in baseline serum collected from postmenopausal women in a case-cohort study within the breast and bone follow-up to the fracture intervention trial (B∼FIT). We followed women not using exogenous hormones at baseline (1992-1993) for up to 12 years: 187 women with incident colorectal cancer diagnosed during follow-up and a subcohort of 495 women selected on strata of age and clinical center. We used adjusted Cox regression models with robust variance to estimate risk for colorectal cancer [hazard ratios (HR), 95% confidence intervals (CI)].ResultsHigh concentrations of pregnenolone and progesterone were not associated with colorectal cancer [quintile(Q)5 versus Q1: pregnenolone HR, 0.71, 95% CI, 0.40-1.25; progesterone HR, 1.25; 95% CI, 0.71-2.22]. A trend of increasing risk was suggested, but statistically imprecise across quintiles of 17-hydroxypregnenolone (Q2 to Q5 HRs, 0.75-1.44; P trend, 0.06).ConclusionsWe used sensitive and reliable assays to measure multiple circulating markers of progestogen metabolism. Progestogens were generally unassociated with colorectal cancer risk in postmenopausal women.ImpactOur findings are consistent with most prior research on circulating endogenous sex hormones, which taken together suggest that sex hormones may not be major drivers of colorectal carcinogenesis in postmenopausal women.

The gut microbiota may play a role in breast cancer etiology by regulating hormonal, metabolic and immunologic pathways. We investigated associations of fecal bacteria with breast cancer and nonmalignant breast disease in a case-control study conducted in Ghana, a country with rising breast cancer incidence and mortality. To do this, we sequenced the V4 region of the 16S rRNA gene to characterize bacteria in fecal samples collected at the time of breast biopsy (N = 379 breast cancer cases, N = 102 nonmalignant breast disease cases, N = 414 population-based controls). We estimated associations of alpha diversity (observed amplicon sequence variants [ASVs], Shannon index, and Faith's phylogenetic diversity), beta diversity (Bray-Curtis and unweighted/weighted UniFrac distance), and the presence and relative abundance of select taxa with breast cancer and nonmalignant breast disease using multivariable unconditional polytomous logistic regression. All alpha diversity metrics were strongly, inversely associated with odds of breast cancer and for those in the highest relative to lowest tertile of observed ASVs, the odds ratio (95% confidence interval) was 0.21 (0.13-0.36; Ptrend

BackgroundAccumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers.MethodsUsing LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data.ResultsGenetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10-5). We found seven loci associated with risk for both cancers (P Bonferroni < 2.4 × 10-9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10-7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation.ConclusionsUsing cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis.ImpactOur research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.

PurposeGene expression-based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features.Experimental designAdopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting.ResultsGene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with >95% accuracy that was maintained in all analytic and biological validations.ConclusionsWe validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications.See related commentary by McMullen et al., p. 5271.

Abstract: Accumulating evidence suggests a relationship between endometrial cancer and epithelial ovarian cancer. For example, endometrial cancer and epithelial ovarian cancer share epidemiological risk factors and molecular features observed across histotypes are held in common (e.g. serous, endometrioid and clear cell). Independent genome-wide association studies (GWAS) for endometrial cancer and epithelial ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. Using GWAS summary statistics, we explored the shared genetic etiology between endometrial cancer and epithelial ovarian cancer. Genetic correlation analysis using LD Score regression revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e. inverse-variance meta-analysis, co-localization, and M-values), and performed analyses by stratified by subtype. We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10−9). In addition, four novel regions at 7p22.2, 7q22.1, 9p12 and 11q13.3 were identified at a sub-genome wide threshold (P < 5 × 10−7). Integration with promoter-associated HiChIP chromatin loops from immortalized endometrium and epithelial ovarian cell lines, and expression quantitative trait loci (eQTL) data highlighted candidate target genes for further investigation.

The association of progesterone/progesterone metabolites with elevated mammographic breast density (MBD) and delayed age-related terminal duct lobular unit (TDLU) involution, strong breast cancer risk factors, has received limited attention. Using a reliable liquid chromatography-tandem mass-spectrometry assay, we quantified serum progesterone/progesterone metabolites and explored cross-sectional relationships with MBD and TDLU involution among women, ages 40-65, undergoing diagnostic breast biopsy. Quantitative MBD measures were estimated in pre-biopsy digital mammograms. TDLU involution was quantified in diagnostic biopsies. Adjusted partial correlations and trends across MBD/TDLU categories were calculated. Pregnenolone was positively associated with percent MBD-area (MBD-A, rho: 0.30; p-trend = 0.01) among premenopausal luteal phase women. Progesterone tended to be positively associated with percent MBD-A among luteal phase (rho: 0.26; p-trend = 0.07) and postmenopausal (rho: 0.17; p-trend = 0.04) women. Consistent with experimental data, implicating an elevated 5α-pregnanes/3α-dihydroprogesterone (5αP/3αHP) metabolite ratio in breast cancer, higher 5αP/3αHP was associated with elevated percent MBD-A among luteal phase (rho: 0.29; p-trend = 0.08), but not postmenopausal women. This exploratory analysis provided some evidence that endogenous progesterone and progesterone metabolites might be correlated with MBD, a strong breast cancer risk factor, in both pre- and postmenopausal women undergoing breast biopsy. Additional studies are needed to understand the role of progesterone/progesterone metabolites in breast tissue composition and breast cancer risk.

PurposeMenopausal hormone therapy (MHT) use induces alterations in circulating estrogens/estrogen metabolites, which may contribute to the altered risk of reproductive tract cancers among current users. Thus, the current study assessed associations between circulating estrogens/estrogen metabolites and ovarian and endometrial cancer risk among MHT users.MethodsWe conducted a nested case-control study among postmenopausal women using MHT at baseline in the Women's Health Initiative Observational Study (179 ovarian cancers, 396 controls; 230 endometrial cancers, 253 controls). Multivariable logistic regression was utilized to estimate odds ratios and 95% confidence intervals overall and by subtype.ResultsEstrogen/estrogen metabolite levels were not associated with overall or serous ovarian cancer risk, examined separately. However, unconjugated estradiol was positively associated with non-serous ovarian cancer risk [quintile 5 vs. quintile 1: 3.01 (1.17-7.73); p-trend = 0.03; p-het

Our knowledge of epidemiologic risk factors for ovarian cancer supports a role for androgens in the pathogenesis of this disease; however, few studies have examined associations between circulating androgens and ovarian cancer risk. Using highly sensitive LC-MS/MS assays, we evaluated associations between pre-diagnostic serum levels of 12 androgens, including novel androgen metabolites that reflect androgen activity in tissues, and ovarian cancer risk among postmenopausal women in a nested case-control study in the Women's Health Initiative (WHI) Observational Study (OS). We frequency-matched 169 ovarian cancer cases to 410 controls from women enrolled in WHI-OS who were not using menopausal hormones at enrollment/blood draw. We estimated associations overall and by subtype (n = 102 serous/67 non-serous) using multivariable adjusted logistic regression. Androgen/androgen metabolite levels were not associated with overall ovarian cancer risk. In analyses by subtype, women with increased levels of androsterone-glucuronide (ADT-G) and total 5-α reduced glucuronide metabolites (markers of tissue-level androgenic activity) were at increased risk of developing non-serous ovarian cancer: ADT-G tertile (T)3 versus T1 odds ratio [OR] (95% confidence interval [CI]) 4.36 (1.68-11.32), p-heterogeneity 0.002; total glucuronide metabolites 3.63 (1.47-8.95), 0.002. Risk of developing serous tumors was unrelated to these markers. ADT-G and total glucuronide metabolites, better markers of tissue-level androgenic activity in women than testosterone, were associated with an increased risk of developing non-serous ovarian cancer. Our work demonstrates that sex steroid metabolism is important in the etiology of non-serous ovarian cancers and supports a heterogeneous hormonal etiology across histologic subtypes of ovarian cancer.

BACKGROUND: Mammographic density (MD) is a strong breast cancer risk factor that reflects fibroglandular and adipose tissue composition, but its biologic underpinnings are poorly understood. Insulin-like growth factor binding proteins (IGFBPs) are markers that may be associated with MD given their hypothesized role in breast carcinogenesis. IGFBPs sequester IGF-I, limiting its bioavailability. Prior studies have found positive associations between circulating IGF-I and the IGF-I:IGFBP-3 ratio and breast cancer risk. We evaluated the associations of IGF-I, IGFBP-3, and six other IGFBPs with MD. METHODS: Serum IGF measures were quantified in 296 women, ages 40-65, undergoing diagnostic image-guided breast biopsy. Volumetric density measures (MD-V) were assessed in pre-biopsy digital mammograms using single X-ray absorptiometry. Area density measures (MD-A) were estimated by computer-assisted thresholding software. Age, body mass index (BMI), and BMI2-adjusted linear regression models were used to examine associations of serum IGF measures with MD. Effect modification by BMI was also assessed. RESULTS: IGF-I and IGFBP-3 were not strongly associated with MD after BMI adjustment. In multivariable analyses among premenopausal women, IGFBP-2 was positively associated with both percent MD-V (β = 1.49, p value = 0.02) and MD-A (β = 1.55, p value = 0.05). Among postmenopausal women, positive relationships between IGFBP-2 and percent MD-V (β = 2.04, p = 0.003) were observed; the positive associations between IGFBP-2 and percent MD-V were stronger among lean women (BMI

BackgroundIn addition to the established association between general obesity and breast cancer risk, central obesity and circulating fasting insulin and glucose have been linked to the development of this common malignancy. Findings from previous studies, however, have been inconsistent, and the nature of the associations is unclear.MethodsWe conducted Mendelian randomization analyses to evaluate the association of breast cancer risk, using genetic instruments, with fasting insulin, fasting glucose, 2-h glucose, body mass index (BMI) and BMI-adjusted waist-hip-ratio (WHRadj BMI). We first confirmed the association of these instruments with type 2 diabetes risk in a large diabetes genome-wide association study consortium. We then investigated their associations with breast cancer risk using individual-level data obtained from 98 842 cases and 83 464 controls of European descent in the Breast Cancer Association Consortium.ResultsAll sets of instruments were associated with risk of type 2 diabetes. Associations with breast cancer risk were found for genetically predicted fasting insulin [odds ratio (OR) = 1.71 per standard deviation (SD) increase, 95% confidence interval (CI) = 1.26-2.31, p  =  5.09  ×  10-4], 2-h glucose (OR = 1.80 per SD increase, 95% CI = 1.3 0-2.49, p  =  4.02  ×  10-4), BMI (OR = 0.70 per 5-unit increase, 95% CI = 0.65-0.76, p  =  5.05  ×  10-19) and WHRadj BMI (OR = 0.85, 95% CI = 0.79-0.91, p  =  9.22  ×  10-6). Stratified analyses showed that genetically predicted fasting insulin was more closely related to risk of estrogen-receptor [ER]-positive cancer, whereas the associations with instruments of 2-h glucose, BMI and WHRadj BMI were consistent regardless of age, menopausal status, estrogen receptor status and family history of breast cancer.ConclusionsWe confirmed the previously reported inverse association of genetically predicted BMI with breast cancer risk, and showed a positive association of genetically predicted fasting insulin and 2-h glucose and an inverse association of WHRadj BMI with breast cancer risk. Our study suggests that genetically determined obesity and glucose/insulin-related traits have an important role in the aetiology of breast cancer.

BackgroundWe examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry.MethodsMeta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP).ResultsWe did not find any variant associated with breast cancer-specific mortality at P

BACKGROUND:Aspirin use is associated with reduced risk of several cancers. A pooled analysis of 12 case-control studies showed a 10% decrease in ovarian cancer risk with regular aspirin use, which was stronger for daily and low-dose users. To prospectively investigate associations of analgesic use with ovarian cancer, we analyzed data from 13 studies in the Ovarian Cancer Cohort Consortium (OC3). METHODS:The current study included 758 829 women who at study enrollment self-reported analgesic use, among whom 3514 developed ovarian cancer. Using Cox regression, we assessed associations between frequent medication use and risk of ovarian cancer. Dose and duration were also evaluated. All statistical tests were two-sided. RESULTS:Women who used aspirin almost daily (≥6 days/wk) vs infrequent/nonuse experienced a 10% reduction in ovarian cancer risk (rate ratio [RR] = 0.90, 95% confidence interval [CI] = 0.82 to 1.00, P = .05). Frequent use (≥4 days/wk) of aspirin (RR = 0.95, 95% CI = 0.88 to 1.03), nonaspirin nonsteroidal anti-inflammatory drugs (NSAIDs; RR = 1.00, 95% CI = 0.90 to 1.11), or acetaminophen (RR = 1.05, 95% CI = 0.88 to 1.24) was not associated with risk. Daily acetaminophen use (RR = 1.28, 95% CI = 1.00 to 1.65, P = .05) was associated with elevated ovarian cancer risk. Risk estimates for frequent, long-term (10+ years) use of aspirin (RR = 1.15, 95% CI = 0.98 to 1.34) or nonaspirin NSAIDs (RR = 1.19, 95% CI = 0.84 to 1.68) were modestly elevated, although not statistically significantly so. CONCLUSIONS:This large, prospective analysis suggests that women who use aspirin daily have a slightly lower risk of developing ovarian cancer (∼10% lower than infrequent/nonuse)-similar to the risk reduction observed in case-control analyses. The observed potential elevated risks for 10+ years of frequent aspirin and NSAID use require further study but could be due to confounding by medical indications for use or variation in drug dosing.

Breast density, a breast cancer risk factor, is a radiologic feature that reflects fibroglandular tissue content relative to breast area or volume. Its histology is incompletely characterized. Here we use deep learning approaches to identify histologic correlates in radiologically-guided biopsies that may underlie breast density and distinguish cancer among women with elevated and low density. We evaluated hematoxylin and eosin (H&E)-stained digitized images from image-guided breast biopsies (n = 852 patients). Breast density was assessed as global and localized fibroglandular volume (%). A convolutional neural network characterized H&E composition. In total 37 features were extracted from the network output, describing tissue quantities and morphological structure. A random forest regression model was trained to identify correlates most predictive of fibroglandular volume (n = 588). Correlations between predicted and radiologically quantified fibroglandular volume were assessed in 264 independent patients. A second random forest classifier was trained to predict diagnosis (invasive vs. benign); performance was assessed using area under receiver-operating characteristics curves (AUC). Using extracted features, regression models predicted global (r = 0.94) and localized (r = 0.93) fibroglandular volume, with fat and non-fatty stromal content representing the strongest correlates, followed by epithelial organization rather than quantity. For predicting cancer among high and low fibroglandular volume, the classifier achieved AUCs of 0.92 and 0.84, respectively, with epithelial organizational features ranking most important. These results suggest non-fatty stroma, fat tissue quantities and epithelial region organization predict fibroglandular volume. The model holds promise for identifying histological correlates of cancer risk in patients with high and low density and warrants further evaluation.

Thymidylate synthase (TYMS) is a crucial enzyme for DNA synthesis. TYMS expression is regulated by its antisense mRNA, ENOSF1. Disrupted regulation may promote uncontrolled DNA synthesis and tumor growth. We sought to replicate our previously reported association between rs495139 in the TYMS-ENOSF1 3' gene region and increased risk of mucinous ovarian carcinoma (MOC) in an independent sample. Genotypes from 24,351 controls to 15,000 women with invasive OC, including 665 MOC, were available. We estimated per-allele odds ratios (OR) and 95% confidence intervals (CI) using unconditional logistic regression, and meta-analysis when combining these data with our previous report. The association between rs495139 and MOC was not significant in the independent sample (OR = 1.09; 95% CI = 0.97⁻1.22; p = 0.15; N = 665 cases). Meta-analysis suggested a weak association (OR = 1.13; 95% CI = 1.03⁻1.24; p = 0.01; N = 1019 cases). No significant association with risk of other OC histologic types was observed (p = 0.05 for tumor heterogeneity). In expression quantitative trait locus (eQTL) analysis, the rs495139 allele was positively associated with ENOSF1 mRNA expression in normal tissues of the gastrointestinal system, particularly esophageal mucosa (r = 0.51, p = 1.7 × 10-28), and nonsignificantly in five MOC tumors. The association results, along with inconclusive tumor eQTL findings, suggest that a true effect of rs495139 might be small.

The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P

BackgroundCoffee consumption has been shown to be associated with various health outcomes in observational studies. However, evidence for its association with epithelial ovarian cancer (EOC) is inconsistent and it is unclear whether these associations are causal.MethodsWe used single nucleotide polymorphisms associated with (i) coffee and (ii) caffeine consumption to perform Mendelian randomization (MR) on EOC risk. We conducted a two-sample MR using genetic data on 44 062 individuals of European ancestry from the Ovarian Cancer Association Consortium (OCAC), and combined instrumental variable estimates using a Wald-type ratio estimator.ResultsFor all EOC cases, the causal odds ratio (COR) for genetically predicted consumption of one additional cup of coffee per day was 0.92 [95% confidence interval (CI): 0.79, 1.06]. The COR was 0.90 (95% CI: 0.73, 1.10) for high-grade serous EOC. The COR for genetically predicted consumption of an additional 80 mg caffeine was 1.01 (95% CI: 0.92, 1.11) for all EOC cases and 0.90 (95% CI: 0.73, 1.10) for high-grade serous cases.ConclusionsWe found no evidence indicative of a strong association between EOC risk and genetically predicted coffee or caffeine levels. However, our estimates were not statistically inconsistent with earlier observational studies and we were unable to rule out small protective associations.

BackgroundObservational studies suggest greater height is associated with increased ovarian cancer risk, but cannot exclude bias and/or confounding as explanations for this. Mendelian randomisation (MR) can provide evidence which may be less prone to bias.MethodsWe pooled data from 39 Ovarian Cancer Association Consortium studies (16,395 cases; 23,003 controls). We applied two-stage predictor-substitution MR, using a weighted genetic risk score combining 609 single-nucleotide polymorphisms. Study-specific odds ratios (OR) and 95% confidence intervals (CI) for the association between genetically predicted height and risk were pooled using random-effects meta-analysis.ResultsGreater genetically predicted height was associated with increased ovarian cancer risk overall (pooled-OR (pOR) = 1.06; 95% CI: 1.01-1.11 per 5 cm increase in height), and separately for invasive (pOR = 1.06; 95% CI: 1.01-1.11) and borderline (pOR = 1.15; 95% CI: 1.02-1.29) tumours.ConclusionsWomen with a genetic propensity to being taller have increased risk of ovarian cancer. This suggests genes influencing height are involved in pathways promoting ovarian carcinogenesis.

Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer mortality in American women. Normal ovarian physiology is intricately connected to small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran) which govern processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. We hypothesized that common germline variation in genes encoding small GTPases is associated with EOC risk. We investigated 322 variants in 88 small GTPase genes in germline DNA of 18,736 EOC patients and 26,138 controls of European ancestry using a custom genotype array and logistic regression fitting log-additive models. Functional annotation was used to identify biofeatures and expression quantitative trait loci that intersect with risk variants. One variant, ARHGEF10L (Rho guanine nucleotide exchange factor 10 like) rs2256787, was associated with increased endometrioid EOC risk (OR = 1.33, p = 4.46 x 10-6). Other variants of interest included another in ARHGEF10L, rs10788679, which was associated with invasive serous EOC risk (OR = 1.07, p = 0.00026) and two variants in AKAP6 (A-kinase anchoring protein 6) which were associated with risk of invasive EOC (rs1955513, OR = 0.90, p = 0.00033; rs927062, OR = 0.94, p = 0.00059). Functional annotation revealed that the two ARHGEF10L variants were located in super-enhancer regions and that AKAP6 rs927062 was associated with expression of GTPase gene ARHGAP5 (Rho GTPase activating protein 5). Inherited variants in ARHGEF10L and AKAP6, with potential transcriptional regulatory function and association with EOC risk, warrant investigation in independent EOC study populations.

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10-8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC.

Endogenous estradiol and estrone are linked causally to increased risks of breast cancer. In this study, we evaluated multiple competing hypotheses for how metabolism of these parent estrogens may influence risk. Prediagnostic concentrations of estradiol, estrone, and 13 metabolites were measured in 1,298 postmenopausal cases of breast cancer and 1,524 matched controls in four separate patient cohorts. The median time between sample collection and diagnosis was 4.4 to 12.7 years across the cohorts. Estrogen analytes were measured in serum or urine by liquid chromatography-tandem mass spectrometry. Total estrogen levels (summing all 15 estrogens/estrogen metabolites) were associated strongly and positively with breast cancer risk. Normalizing total estrogen levels, we also found that a relative increase in levels of 2-hydroxylation pathway metabolites, or in the ratio of 2-hydroxylation:16-hydroxylation pathway metabolites, were associated inversely with breast cancer risk. These associations varied by total estrogen levels, with the largest risk reductions occurring in women in the highest tertile. With appropriate validation, these findings suggest opportunities for breast cancer prevention by modifying individual estrogen metabolism profiles through either lifestyle alterations or chemopreventive strategies. Cancer Res; 77(4); 918-25. ©2017 AACR.

RNA editing in mammals is a form of post-transcriptional modification in which adenosine is converted to inosine by the adenosine deaminases acting on RNA (ADAR) family of enzymes. Based on evidence of altered ADAR expression in epithelial ovarian cancers (EOC), we hypothesized that single nucleotide polymorphisms (SNPs) in ADAR genes modify EOC susceptibility, potentially by altering ovarian tissue gene expression. Using directly genotyped and imputed data from 10,891 invasive EOC cases and 21,693 controls, we evaluated the associations of 5,303 SNPs in ADAD1, ADAR, ADAR2, ADAR3, and SND1. Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI), with adjustment for European ancestry. We conducted gene-level analyses using the Admixture Maximum Likelihood (AML) test and the Sequence-Kernel Association test for common and rare variants (SKAT-CR). Association analysis revealed top risk-associated SNP rs77027562 (OR (95% CI)= 1.39 (1.17-1.64), P=1.0x10-4) in ADAR3 and rs185455523 in SND1 (OR (95% CI)= 0.68 (0.56-0.83), P=2.0x10-4). When restricting to serous histology (n=6,500), the magnitude of association strengthened for rs185455523 (OR=0.60, P=1.0x10-4). Gene-level analyses revealed that variation in ADAR was associated (P

BackgroundRegulatory T (Treg) cells, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and, thus, variants in genes encoding Treg cell immune molecules could be associated with ovarian cancer.MethodsIn a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients.ResultsThe most significant global associations for all genes in the pathway were seen in endometrioid ( p = 0.082) and clear cell ( p = 0.083), with the most significant gene level association seen with TGFBR2 ( p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 ( p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA ( p = 0.035, endometrioid and mucinous), LGALS1 ( p = 0.03, mucinous), STAT5B ( p = 0.022, clear cell), TGFBR1 ( p = 0.021 endometrioid) and TGFBR2 ( p = 0.017 and p = 0.025, endometrioid and mucinous, respectively).ConclusionsCommon inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients.

BackgroundIn vitro and observational epidemiological studies suggest that vitamin D may play a role in cancer prevention. However, the relationship between vitamin D and ovarian cancer is uncertain, with observational studies generating conflicting findings. A potential limitation of observational studies is inadequate control of confounding. To overcome this problem, we used Mendelian randomization (MR) to evaluate the association between single nucleotide polymorphisms (SNPs) associated with circulating 25-hydroxyvitamin D [25(OH)D] concentration and risk of ovarian cancer.MethodsWe employed SNPs with well-established associations with 25(OH)D concentration as instrumental variables for MR: rs7944926 (DHCR7), rs12794714 (CYP2R1) and rs2282679 (GC). We included 31 719 women of European ancestry (10 065 cases, 21 654 controls) from the Ovarian Cancer Association Consortium, who were genotyped using customized Illumina Infinium iSelect (iCOGS) arrays. A two-sample (summary data) MR approach was used and analyses were performed separately for all ovarian cancer (10 065 cases) and for high-grade serous ovarian cancer (4121 cases).ResultsThe odds ratio for epithelial ovarian cancer risk (10 065 cases) estimated by combining the individual SNP associations using inverse variance weighting was 1.27 (95% confidence interval: 1.06 to 1.51) per 20 nmol/L decrease in 25(OH)D concentration. The estimated odds ratio for high-grade serous epithelial ovarian cancer (4121 cases) was 1.54 (1.19, 2.01).ConclusionsGenetically lowered 25-hydroxyvitamin D concentrations were associated with higher ovarian cancer susceptibility in Europeans. These findings suggest that increasing plasma vitamin D levels may reduce risk of ovarian cancer.

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, r(2)  = 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.

Rare and low frequency variants are not well covered in most germline genotyping arrays and are understudied in relation to epithelial ovarian cancer (EOC) risk. To address this gap, we used genotyping arrays targeting rarer protein-coding variation in 8,165 EOC cases and 11,619 controls from the international Ovarian Cancer Association Consortium (OCAC). Pooled association analyses were conducted at the variant and gene level for 98,543 variants directly genotyped through two exome genotyping projects. Only common variants that represent or are in strong linkage disequilibrium (LD) with previously-identified signals at established loci reached traditional thresholds for exome-wide significance (P  P≥5.0 ×10 -  7) were detected for rare and low-frequency variants at 16 novel loci. Four rare missense variants were identified (ACTBL2 rs73757391 (5q11.2), BTD rs200337373 (3p25.1), KRT13 rs150321809 (17q21.2) and MC2R rs104894658 (18p11.21)), but only MC2R rs104894668 had a large effect size (OR = 9.66). Genes most strongly associated with EOC risk included ACTBL2 (PAML = 3.23 × 10 -  5; PSKAT-o = 9.23 × 10 -  4) and KRT13 (PAML = 1.67 × 10 -  4; PSKAT-o = 1.07 × 10 -  5), reaffirming variant-level analysis. In summary, this large study identified several rare and low-frequency variants and genes that may contribute to EOC susceptibility, albeit with possible small effects. Future studies that integrate epidemiology, sequencing, and functional assays are needed to further unravel the unexplained heritability and biology of this disease.

Epithelial ovarian cancer (EOC) is one of the deadliest common cancers. The five most common types of disease are high-grade and low-grade serous, endometrioid, mucinous and clear cell carcinoma. Each of these subtypes present distinct molecular pathogeneses and sensitivities to treatments. Recent studies show that certain genetic variants confer susceptibility to all subtypes while other variants are subtype-specific. Here, we perform an extensive analysis of the genetic architecture of EOC subtypes. To this end, we used data of 10,014 invasive EOC patients and 21,233 controls from the Ovarian Cancer Association Consortium genotyped in the iCOGS array (211,155 SNPs). We estimate the array heritability (attributable to variants tagged on arrays) of each subtype and their genetic correlations. We also look for genetic overlaps with factors such as obesity, smoking behaviors, diabetes, age at menarche and height. We estimated the array heritabilities of high-grade serous disease ([Formula: see text] = 8.8 ± 1.1 %), endometrioid ([Formula: see text] = 3.2 ± 1.6 %), clear cell ([Formula: see text] = 6.7 ± 3.3 %) and all EOC ([Formula: see text] = 5.6 ± 0.6 %). Known associated loci contributed approximately 40 % of the total array heritability for each subtype. The contribution of each chromosome to the total heritability was not proportional to chromosome size. Through bivariate and cross-trait LD score regression, we found evidence of shared genetic backgrounds between the three high-grade subtypes: serous, endometrioid and undifferentiated. Finally, we found significant genetic correlations of all EOC with diabetes and obesity using a polygenic prediction approach.

BackgroundMany epithelial ovarian cancer (EOC) risk factors relate to hormone exposure and elevated estrogen levels are associated with obesity in postmenopausal women. Therefore, we hypothesized that gene-environment interactions related to hormone-related risk factors could differ between obese and non-obese women.MethodsWe considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy, and estrogen use) and assessed whether these interactions differed between obese and non-obese women. Interactions were assessed using logistic regression models and data from 14 case-control studies (6,247 cases; 10,379 controls). Histotype-specific analyses were also completed.ResultsSNPs in the following candidate genes showed notable interaction: IGF1R (rs41497346, estrogen plus progesterone hormone therapy, histology = all, P = 4.9 × 10(-6)) and ESR1 (rs12661437, endometriosis, histology = all, P = 1.5 × 10(-5)). The most notable obesity-gene-hormone risk factor interaction was within INSR (rs113759408, parity, histology = endometrioid, P = 8.8 × 10(-6)).ConclusionsWe have demonstrated the feasibility of assessing multifactor interactions in large genetic epidemiology studies. Follow-up studies are necessary to assess the robustness of our findings for ESR1, CYP11A1, IGF1R, CYP11B1, INSR, and IGFBP2 Future work is needed to develop powerful statistical methods able to detect these complex interactions.ImpactAssessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC susceptibility. Cancer Epidemiol Biomarkers Prev; 25(5); 780-90. ©2016 AACR.

ObjectiveClinical genetic testing is commercially available for rs61764370, an inherited variant residing in a KRAS 3' UTR microRNA binding site, based on suggested associations with increased ovarian and breast cancer risk as well as with survival time. However, prior studies, emphasizing particular subgroups, were relatively small. Therefore, we comprehensively evaluated ovarian and breast cancer risks as well as clinical outcome associated with rs61764370.MethodsCentralized genotyping and analysis were performed for 140,012 women enrolled in the Ovarian Cancer Association Consortium (15,357 ovarian cancer patients; 30,816 controls), the Breast Cancer Association Consortium (33,530 breast cancer patients; 37,640 controls), and the Consortium of Modifiers of BRCA1 and BRCA2 (14,765 BRCA1 and 7904 BRCA2 mutation carriers).ResultsWe found no association with risk of ovarian cancer (OR=0.99, 95% CI 0.94-1.04, p=0.74) or breast cancer (OR=0.98, 95% CI 0.94-1.01, p=0.19) and results were consistent among mutation carriers (BRCA1, ovarian cancer HR=1.09, 95% CI 0.97-1.23, p=0.14, breast cancer HR=1.04, 95% CI 0.97-1.12, p=0.27; BRCA2, ovarian cancer HR=0.89, 95% CI 0.71-1.13, p=0.34, breast cancer HR=1.06, 95% CI 0.94-1.19, p=0.35). Null results were also obtained for associations with overall survival following ovarian cancer (HR=0.94, 95% CI 0.83-1.07, p=0.38), breast cancer (HR=0.96, 95% CI 0.87-1.06, p=0.38), and all other previously-reported associations.Conclusionsrs61764370 is not associated with risk of ovarian or breast cancer nor with clinical outcome for patients with these cancers. Therefore, genotyping this variant has no clinical utility related to the prediction or management of these cancers.

BackgroundWhile numerous susceptibility loci for epithelial ovarian cancer (EOC) have been identified, few associations have been reported with overall survival. In the absence of common prognostic genetic markers, we hypothesize that rare coding variants may be associated with overall EOC survival and assessed their contribution in two exome-based genotyping projects of the Ovarian Cancer Association Consortium (OCAC).MethodsThe primary patient set (Set 1) included 14 independent EOC studies (4,293 patients) and 227,892 variants, and a secondary patient set (Set 2) included six additional EOC studies (1,744 patients) and 114,620 variants. Because power to detect rare variants individually is reduced, gene-level tests were conducted. Sets were analyzed separately at individual variants and by gene, and then combined with meta-analyses (73,203 variants and 13,163 genes overlapped).ResultsNo individual variant reached genome-wide statistical significance. A SNP previously implicated to be associated with EOC risk and, to a lesser extent, survival, rs8170, showed the strongest evidence of association with survival and similar effect size estimates across sets (Pmeta = 1.1E-6, HRSet1 = 1.17, HRSet2 = 1.14). Rare variants in ATG2B, an autophagy gene important for apoptosis, were significantly associated with survival after multiple testing correction (Pmeta = 1.1E-6; Pcorrected = 0.01).ConclusionsCommon variant rs8170 and rare variants in ATG2B may be associated with EOC overall survival, although further study is needed.ImpactThis study represents the first exome-wide association study of EOC survival to include rare variant analyses, and suggests that complementary single variant and gene-level analyses in large studies are needed to identify rare variants that warrant follow-up study. Cancer Epidemiol Biomarkers Prev; 25(3); 446-54. ©2016 AACR.

BackgroundGenome-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.ResultsAt 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

Estrogen metabolites may have different genotoxic and mitogenic properties yet their relationship with endometrial and ovarian cancer risk remains unclear. Within the Breast and Bone Follow-up to the Fracture Intervention Trial (B ∼ FIT, n = 15,595), we conducted a case-cohort study to evaluate 15 pre-diagnostic serum estrogens and estrogen metabolites with risk of incident endometrial and ovarian cancer among postmenopausal women not on hormone therapy. Participants included 66 endometrial and 67 ovarian cancer cases diagnosed during follow-up (∼ 10 years) and subcohorts of 346 and 416 women, respectively, after relevant exclusions. Serum concentrations were measured by liquid chromatography-tandem mass spectrometry. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazard regression. Exposures were categorized in tertiles (T) and analyzed individually, as metabolic pathways (C-2, -4, or -16) and as ratios to parent estrogens (estradiol, estrone). Estradiol was significantly associated with increased endometrial cancer risk (BMI-adjusted HRT3vsT1 = 4.09, 95% CI 1.70, 9.85; p trend = 0.003). 2-Hydroxyestrone and 16α-hydroxyestrone were not associated with endometrial risk after estradiol adjustment (2-OHE1:HRT3vsT1 = 1.97, 95% CI 0.78, 4.94; 16-OHE1:HRT3vsT1 = 1.50, 95% CI 0.65, 3.46; p trend = 0.16 and 0.36, respectively). Ratios of 2- and 4-pathway catechol-to-methylated estrogens remained positively associated with endometrial cancer after BMI or estradiol adjustment (2-pathway catechols-to-methylated: HRT3vsT1 = 4.02, 95% CI 1.60, 10.1; 4-pathway catechols-to-methylated: HRT3vsT1 = 4.59, 95% CI 1.64, 12.9; p trend = 0.002 for both). Estrogens and estrogen metabolites were not associated with ovarian cancer risk; however, larger studies are needed to better evaluate these relationships. Estrogen metabolism may be important in endometrial carcinogenesis, particularly with less extensive methylation of 2- or 4-pathway catechols associated with elevated endometrial cancer risk.

ObjectiveTo evaluate whether endometriosis-associated genetic variation affects risk of ovarian cancer.DesignPooled genetic analysis.SettingUniversity hospital.Patient(s)Genetic data from 46,176 participants (15,361 ovarian cancer cases and 30,815 controls) from 41 ovarian cancer studies.Intervention(s)None.Main outcome measure(s)Endometriosis-associated genetic variation and ovarian cancer.Result(s)There was significant evidence of an association between endometriosis-related genetic variation and ovarian cancer risk, especially for the high-grade serous and clear cell histotypes. Overall we observed 15 significant burden statistics, which was three times more than expected.Conclusion(s)By focusing on candidate regions from a phenotype associated with ovarian cancer, we have shown a clear genetic link between endometriosis and ovarian cancer that warrants further follow-up. The functional significance of the identified regions and SNPs is presently uncertain, though future fine mapping and histotype-specific functional analyses may shed light on the etiologies of both gynecologic conditions.

PurposeChemotherapy resistance remains a major challenge in the treatment of ovarian cancer. We hypothesize that germline polymorphisms might be associated with clinical outcome.Experimental designWe 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.ResultsFive 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)).ConclusionsWe have identified SNPs in three lncRNAs that might be important targets for novel EOC therapies.

BackgroundStudies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites.MethodsBetween 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers.ResultsGWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl (2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE =0.18), and bladder and lung (ρ = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures.ConclusionOur results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.

Epithelial-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

BackgroundStudies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites.MethodsBetween 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers.ResultsGWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl (2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE =0.18), and bladder and lung (ρ = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures.ConclusionOur results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.

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 (r(2) ≥ 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.