Disruption in circadian gene expression, whether due to genetic variation or environmental factors (e.g., light at night, shiftwork), is associated with increased incidence of breast, prostate, gastrointestinal and hematologic cancers and gliomas. Circadian genes are highly expressed in the ovaries where they regulate ovulation; circadian disruption is associated with several ovarian cancer risk factors (e.g., endometriosis). However, no studies have examined variation in germline circadian genes as predictors of ovarian cancer risk and invasiveness. The goal of the current study was to examine single nucleotide polymorphisms (SNPs) in circadian genes BMAL1, CRY2, CSNK1E, NPAS2, PER3, REV1 and TIMELESS and downstream transcription factors KLF10 and SENP3 as predictors of risk of epithelial ovarian cancer (EOC) and histopathologic subtypes. The study included a test set of 3,761 EOC cases and 2,722 controls and a validation set of 44,308 samples including 18,174 (10,316 serous) cases and 26,134 controls from 43 studies participating in the Ovarian Cancer Association Consortium (OCAC). Analysis of genotype data from 36 genotyped SNPs and 4600 imputed SNPs indicated that the most significant association was rs117104877 in BMAL1 (OR = 0.79, 95% CI = 0.68-0.90, p = 5.59 × 10-4]. Functional analysis revealed a significant down regulation of BMAL1 expression following cMYC overexpression and increasing transformation in ovarian surface epithelial (OSE) cells as well as alternative splicing of BMAL1 exons in ovarian and granulosa cells. These results suggest that variation in circadian genes, and specifically BMAL1, may be associated with risk of ovarian cancer, likely through disruption of hormonal pathways.

Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10(-5)). For three cis-eQTL associations (P<1.4 × 10(-3), FDR<0.05) at 1p36 (CDC42), 1p34 (CDCA8) and 2q31 (HOXD9), we evaluate the functional role of each candidate by perturbing expression of each gene in HGSOC precursor cells. Overexpression of HOXD9 increases anchorage-independent growth, shortens population-doubling time and reduces contact inhibition. Chromosome conformation capture identifies an interaction between rs2857532 and the HOXD9 promoter, suggesting this SNP is a leading causal variant. Transcriptomic profiling after HOXD9 overexpression reveals enrichment of HGSOC risk variants within HOXD9 target genes (P=6 × 10(-10) for risk variants (P<10(-4)) within 10 kb of a HOXD9 target gene in ovarian cells), suggesting a broader role for this network in genetic susceptibility to HGSOC.

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.

Large predators play important ecological roles, yet many are disproportionately imperiled. In marine systems, artificial reefs are often deployed to restore degraded reefs or supplement existing reefs, but it remains unknown whether these interventions benefit large predators. Comparative field surveys of thirty artificial and natural reefs across ~200 km of the North Carolina, USA coast revealed large reef-associated predators were more dense on artificial than natural reefs. This pattern was associated with higher densities of transient predators (e.g. jacks, mackerel, barracuda, sharks) on artificial reefs, but not of resident predators (e.g., grouper, snapper). Further analyses revealed that this pattern of higher transient predator densities on artificial reefs related to reef morphology, as artificial reefs composed of ships hosted higher transient predator densities than concrete reefs. The strength of the positive association between artificial reefs and transient predators increased with a fundamental habitat trait-vertical extent. Taller artificial reefs had higher densities of transient predators, even when accounting for habitat area. A global literature review of high trophic level fishes on artificial and natural habitats suggests that the overall pattern of more predators on artificial habitats is generalizable. Together, these findings provide evidence that artificial habitats, especially those like sunken ships that provide high vertical structure, may support large predators.

Repeated exposure to the acute proinflammatory environment that follows ovulation at the ovarian surface and distal fallopian tube over a woman's reproductive years may increase ovarian cancer risk. To address this, analyses included individual-level data from 558,709 naturally menopausal women across 20 prospective cohorts, among whom 3,246 developed invasive epithelial ovarian cancer (2,045 serous, 319 endometrioid, 184 mucinous, 121 clear cell, 577 other/unknown). Cox models were used to estimate multivariable-adjusted HRs between lifetime ovulatory cycles (LOC) and its components and ovarian cancer risk overall and by histotype. Women in the 90th percentile of LOC (>514 cycles) were almost twice as likely to be diagnosed with ovarian cancer than women in the 10th percentile (<294) [HR (95% confidence interval): 1.92 (1.60-2.30)]. Risk increased 14% per 5-year increase in LOC (60 cycles) [(1.10-1.17)]; this association remained after adjustment for LOC components: number of pregnancies and oral contraceptive use [1.08 (1.04-1.12)]. The association varied by histotype, with increased risk of serous [1.13 (1.09-1.17)], endometrioid [1.20 (1.10-1.32)], and clear cell [1.37 (1.18-1.58)], but not mucinous [0.99 (0.88-1.10), P-heterogeneity = 0.01] tumors. Heterogeneity across histotypes was reduced [P-heterogeneity = 0.15] with adjustment for LOC components [1.08 serous, 1.11 endometrioid, 1.26 clear cell, 0.94 mucinous]. Although the 10-year absolute risk of ovarian cancer is small, it roughly doubles as the number of LOC rises from approximately 300 to 500. The consistency and linearity of effects strongly support the hypothesis that each ovulation leads to small increases in the risk of most ovarian cancers, a risk that cumulates through life, suggesting this as an important area for identifying intervention strategies. SIGNIFICANCE: Although ovarian cancer is rare, risk of most ovarian cancers doubles as the number of lifetime ovulatory cycles increases from approximately 300 to 500. Thus, identifying an important area for cancer prevention research.

Copy number variants (CNVs) have been implicated in many complex diseases. We examined whether inherited CNVs were associated with overall survival among women with invasive epithelial ovarian cancer. Germline DNA from 1,056 cases (494 deceased, average of 3.7 years follow-up) was interrogated with the Illumina 610 quad genome-wide array containing, after quality control exclusions, 581,903 single nucleotide polymorphisms (SNPs) and 17,917 CNV probes. Comprehensive analysis capitalized upon the strengths of three complementary approaches to CNV classification. First, to identify small CNVs, single markers were evaluated and, where associated with survival, consecutive markers were combined. Two chromosomal regions were associated with survival using this approach (14q31.3 rs2274736 p = 1.59 × 10(-6), p = 0.001; 22q13.31 rs2285164 p = 4.01 × 10(-5), p = 0.009), but were not significant after multiple testing correction. Second, to identify large CNVs, genome-wide segmentation was conducted to characterize chromosomal gains and losses, and association with survival was evaluated by segment. Four regions were associated with survival (1q21.3 loss p = 0.005, 5p14.1 loss p = 0.004, 9p23 loss p = 0.002, and 15q22.31 gain p = 0.002); however, again, after correcting for multiple testing, no regions were statistically significant, and none were in common with the single marker approach. Finally, to evaluate associations with general amounts of copy number changes across the genome, we estimated CNV burden based on genome-wide numbers of gains and losses; no associations with survival were observed (p > 0.40). Although CNVs that were not well-covered by the Illumina 610 quad array merit investigation, these data suggest no association between inherited CNVs and survival after ovarian cancer.

Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations.

Variants of Uncertain Significance (VUS) are genetic variants whose association with a disease phenotype has not been established. They are a common finding in sequencing-based genetic tests and pose a significant clinical challenge. The objective of this study was to assess the use of functional data to classify variants according to pathogenicity. We conduct functional analysis of a large set of BRCA1 VUS combining a validated functional assay with VarCall, a Bayesian hierarchical model to estimate the likelihood of pathogenicity given the functional data. The results from the functional assays were incorporated into a joint analysis of 214 BRCA1 VUS to predict their likelihood of pathogenicity (breast cancer). We show that applying the VarCall model (1.0 sensitivity; lower bound of 95% confidence interval (CI) = 0.75 and 1.0 specificity; lower bound of 95% CI = 0.83) to the current set of BRCA1 variants, use of the functional data would significantly reduce the number of VUS associated with the C-terminal region of the BRCA1 protein by ~ 87%. We extend this work developing yeast-based functional assays for two other genes coding for BRCT domain containing proteins, MCPH1 and MDC1. Analysis of missense variants in MCPH1 and MDC1 shows that structural inference based on the BRCA1 data set can aid in prioritising variants for further analysis. Taken together our results indicate that systematic functional assays can provide a robust tool to aid in clinical annotation of VUS. We propose that well-validated functional assays could be used for clinical annotation even in the absence of additional sources of evidence.

Many variants of uncertain significance (VUS) have been identified in BRCA2 through clinical genetic testing. VUS pose a significant clinical challenge because the contribution of these variants to cancer risk has not been determined. We conducted a comprehensive assessment of VUS in the BRCA2 C-terminal DNA binding domain (DBD) by using a validated functional assay of BRCA2 homologous recombination (HR) DNA-repair activity and defined a classifier of variant pathogenicity. Among 139 variants evaluated, 54 had ?99% probability of pathogenicity, and 73 had ?95% probability of neutrality. Functional assay results were compared with predictions of variant pathogenicity from the Align-GVGD protein-sequence-based prediction algorithm, which has been used for variant classification. Relative to the HR assay, Align-GVGD significantly (p < 0.05) over-predicted pathogenic variants. We subsequently combined functional and Align-GVGD prediction results in a Bayesian hierarchical model (VarCall) to estimate the overall probability of pathogenicity for each VUS. In addition, to predict the effects of all other BRCA2 DBD variants and to prioritize variants for functional studies, we used the endoPhenotype-Optimized Sequence Ensemble (ePOSE) algorithm to train classifiers for BRCA2 variants by using data from the HR functional assay. Together, the results show that systematic functional assays in combination with in silico predictors of pathogenicity provide robust tools for clinical annotation of BRCA2 VUS.

We hypothesized that variants in genes expressed as a consequence of interactions between ovarian cancer cells and the host micro-environment could contribute to cancer susceptibility. We therefore used a two-stage approach to evaluate common single nucleotide polymorphisms (SNPs) in 173 genes involved in stromal epithelial interactions in the Ovarian Cancer Association Consortium (OCAC). In the discovery stage, cases with epithelial ovarian cancer (n=675) and controls (n=1,162) were genotyped at 1,536 SNPs using an Illumina GoldenGate assay. Based on Positive Predictive Value estimates, three SNPs-PODXL rs1013368, ITGA6 rs13027811, and MMP3 rs522616-were selected for replication using TaqMan genotyping in up to 3,059 serous invasive cases and 8,905 controls from 16 OCAC case-control studies. An additional 18 SNPs with Pper-allele<0.05 in the discovery stage were selected for replication in a subset of five OCAC studies (n=1,233 serous invasive cases; n=3,364 controls). The discovery stage associations in PODXL, ITGA6, and MMP3 were attenuated in the larger replication set (adj. Pper-allele>or=0.5). However genotypes at TERT rs7726159 were associated with ovarian cancer risk in the smaller, five-study replication study (Pper-allele=0.03). Combined analysis of the discovery and replication sets for this TERT SNP showed an increased risk of serous ovarian cancer among non-Hispanic whites [adj. ORper-allele 1.14 (1.04-1.24) p=0.003]. Our study adds to the growing evidence that, like the 8q24 locus, the telomerase reverse transcriptase locus at 5p15.33, is a general cancer susceptibility locus.

We previously identified a panel of genes associated with outcome of ovarian cancer. The purpose of the current study was to assess whether variants in these genes correlated with ovarian cancer risk.

Mutation screening of the breast and ovarian cancer-predisposition genes BRCA1 and BRCA2 is becoming an increasingly important part of clinical practice. Classification of rare nontruncating sequence variants in these genes is problematic, because it is not known whether these subtle changes alter function sufficiently to predispose cells to cancer development. Using data from the Myriad Genetic Laboratories database of nearly 70,000 full-sequence tests, we assessed the clinical significance of 1,433 sequence variants of unknown significance (VUSs) in the BRCA genes. Three independent measures were employed in the assessment: co-occurrence in trans of a VUS with known deleterious mutations; detailed analysis, by logistic regression, of personal and family history of cancer in VUS-carrying probands; and, in a subset of probands, an analysis of cosegregation with disease in pedigrees. For each of these factors, a likelihood ratio was computed under the hypothesis that the VUSs were equivalent to an "average" deleterious mutation, compared with neutral, with respect to risk. The likelihood ratios derived from each component were combined to provide an overall assessment for each VUS. A total of 133 VUSs had odds of at least 100 : 1 in favor of neutrality with respect to risk, whereas 43 had odds of at least 20 : 1 in favor of being deleterious. VUSs with evidence in favor of causality were those that were predicted to affect splicing, fell at positions that are highly conserved among BRCA orthologs, and were more likely to be located in specific domains of the proteins. In addition to their utility for improved genetics counseling of patients and their families, the global assessment reported here will be invaluable for validation of functional assays, structural models, and in silico analyses.

We analyzed the association between 53 genes related to DNA repair and p53-mediated damage response and serous ovarian cancer risk using case-control data from the North Carolina Ovarian Cancer Study (NCOCS), a population-based, case-control study.

BRCA1 (Breast Cancer 1, early onset) is linked to breast and ovarian cancer predisposition. Still, the risks conferred by a significant portion of BRCA1 variants identified in the population remains unknown. Most of these variants of uncertain significance are missense alterations. However, the functional implications of small in-frame deletions and/or insertions (indels) are also difficult to predict. Our group has previously evaluated the functional impact of 347 missense variants using an extensively validated transcriptional activity assay. Here we show a systematic assessment of 30 naturally occurring in-frame indels located at the C-terminal region of BRCA1. We identified positions sensitive and tolerant to alterations, expanding the knowledge of structural determinants of BRCA1 function. We further designed and assessed the impact of four single codon deletions in the tBRCT linker region and six nonsense variants at the C-terminus end of BRCA1. Amino acid substitutions, deletions or insertions in the disordered region do not significantly impact activity and are not likely to constitute pathogenic alleles. On the other hand, a sizeable fraction of in-frame indels at the BRCT domain significantly impact function. We then use a Bayesian integrative statistical model to derive the probability of pathogenicity for each variant. Our data highlights the importance of assessing the impact of small in-frame indels in BRCA1 to improve risk assessment and clinical decisions for carriers.

Defective cellular transport processes can lead to aberrant accumulation of trace elements, iron, small molecules and hormones in the cell, which in turn may promote the formation of reactive oxygen species, promoting DNA damage and aberrant expression of key regulatory cancer genes. As DNA damage and uncontrolled proliferation are hallmarks of cancer, including epithelial ovarian cancer (EOC), we hypothesized that inherited variation in the cellular transport genes contributes to EOC risk.

Remodeling of cellular metabolism appears to be a consequence and possibly a cause of oncogenic transformation in human cancers. Specific aspects of altered tumor metabolism may be amenable to therapeutic intervention and could be coordinated with other targeted therapies. In breast cancer, the genetic landscape has been defined most comprehensively in efforts such as The Cancer Genome Atlas (TCGA). However, little is known about how alterations of tumor metabolism correlate with this landscape.

Sequencing-based genetic tests to identify individuals at increased risk of hereditary breast and ovarian cancers have resulted in the identification of more than 40,000 sequence variants of BRCA1 and BRCA2. A majority of these variants are considered to be variants of uncertain significance (VUS) because their impact on disease risk remains unknown, largely due to lack of sufficient familial linkage and epidemiological data. Several assays have been developed to examine the effect of VUS on protein function, which can be used to assess their impact on cancer susceptibility. In this study, we report the functional characterization of 88 BRCA2 variants, including several previously uncharacterized variants, using a well-established mouse embryonic stem cell (mESC)-based assay. We have examined their ability to rescue the lethality of Brca2 null mESC as well as sensitivity to six DNA damaging agents including ionizing radiation and a PARP inhibitor. We have also examined the impact of BRCA2 variants on splicing. In addition, we have developed a computational model to determine the probability of impact on function of the variants that can be used for risk assessment. In contrast to the previous VarCall models that are based on a single functional assay, we have developed a new platform to analyze the data from multiple functional assays separately and in combination. We have validated our VarCall models using 12 known pathogenic and 10 neutral variants and demonstrated their usefulness in determining the pathogenicity of BRCA2 variants that are listed as VUS or as variants with conflicting functional interpretation.

Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10(-8). Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.

Germline inactivating variants in BRCA1 lead to a significantly increased risk of breast and ovarian cancers in carriers. While the functional effect of many variants can be inferred from the DNA sequence, determining the effect of missense variants present a significant challenge. A series of biochemical and cell biological assays have been successfully used to explore the impact of these variants on the function of BRCA1, which contribute to assessing their likelihood of pathogenicity. It has been determined that variants that co-localize with structural or functional motifs are more likely to disrupt the stability and function of BRCA1. Here we assess the functional impact of 37 variants chosen to probe the functional impact of variants in phosphorylation sites and in the BRCT domains. In addition, we perform a meta-analysis of 170 unique variants tested by the transcription activation assays in the carboxy-terminal domain of BRCA1 using a recently developed computation model to provide assessment for functional impact and their likelihood of pathogenicity.

Genetic association studies are conducted to discover genetic loci that contribute to an inherited trait, identify the variants behind these associations and ascertain their functional role in determining the phenotype. To date, functional annotations of the genetic variants have rarely played more than an indirect role in assessing evidence for association. Here, we demonstrate how these data can be systematically integrated into an association study's analysis plan.