Risch, Harvey A.

Abstract Background: Nulliparity is an established endometrial cancer risk factor, but whether this association is related to infertility is unclear. Although there are many underlying causes of infertility, few studies have assessed risk relationships according to specific causes. Despite concerns that most treatments induce ovulation and that the endometrium is highly hormonally-responsive, previous studies have provided conflicting results on treatment associations. Methods: To address these issues, we conducted a pooled analysis of 8,151 cases and12,471 controls from 2 cohort and 12 case-control studies conducted in 1982 to 2009 (N. America, Europe, Australia, Asia). All studies provided self-reported infertility, causes and treatments, except for 1 study that relied on data from national registries. Study-specific exposures and covariate data were harmonized across studies. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI), adjusted for study, age, interview year, race, parity, oral contraceptive and menopausal hormone use, and body mass index. If data were not reported for a particular variable, that study was excluded from the variable-specific analysis. Results: Nulliparous women had an elevated endometrial cancer risk compared with parous women (adjusted OR=1.73; 95% CI: 1.58-1.90).Women with self-reported infertility also had an increased risk (adjusted OR=1.22; 95% CI: 1.13-1.32) compared with those without infertility issues, even after adjusting for parity; the strongest associations was seen among studies that defined infertility as unsuccessfully trying to conceive for 2+ years (adjusted OR=1.31; 95% CI: 1.07-1.60). Infertility was associated with similar risks among nulliparous (1.22; 1.10-1.48) and parous (1.22; 1.12-1.34) women, although there was no increased risk associated with infertility among those who had given birth to 3+ children. Two infertility causes associated with risk elevation were endometriosis (adjusted OR=2.08; 95% CI: 1.46-2.95 compared with women no infertility problems) and anovulation (adjusted OR=1.40; 95% CI: 1.16-1.70). Based on relatively small numbers, none of the individual treatments (in vitro fertilization, selective estrogen response modulators, gonatropins, progestins, estrogens) were substantially related to risk. Conclusion: Based on mainly self-reported infertility data, we found that parity and infertility independently contribute to endometrial cancer risk, with parity seemingly being the predominant risk predictor. Understanding residual endometrial cancer relationships related to causes of infertility and infertility treatment may benefit from documented medical information on causes of infertility and treatment parameters. Citation Format: Hannah P. Yang, Linda S. Cook, Elisabete Weiderpass, Hans-Olov Adami, Kristin E. Anderson, Hui Cai, James R. Cerhan, Tess Clendenen, Ashley S. Felix, Christine Friedenreich, Montserrat Garcia-Closas, Marc T. Goodman, Xiaolin Liang, Jolanta Lissowska, Lingeng Lu, Anthony M. Magliocco, Susan E. McCann, Kristen B. Moysich, Sara H. Olson, Malcolm C. Pike, Silvia Polidoro, Fulvio Ricceri, Harvey Risch, Carlotta Sacerdote, V. Wendy Setiawan, Xiao Ou Shu, Amanda B. Spurdle, Britton Trabert, Penelope M. Webb, Nicolas Wentzensen, Yong-Bing Xiang, Youming Xu, Herbert Yu, Anne Zeleniuch-Jacquotte, Louise A. Brinton. Infertility and risk of incident endometrial carcinoma: a pooled analysis from the Epidemiology of Endometrial Cancer Consortium. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2167. doi:10.1158/1538-7445.AM2014-2167

ScopeWe reevaluated previously reported associations between variants in pathways of one‐carbon (1‐C) (folate) transfer genes and ovarian carcinoma (OC) risk, and in related pathways of purine and pyrimidine metabolism, and assessed interactions with folate intake.Methods and resultsOdds ratios (OR) for 446 genetic variants were estimated among 13 410 OC cases and 22 635 controls, and among 2281 cases and 3444 controls with folate information. Following multiple testing correction, the most significant main effect associations were for dihydropyrimidine dehydrogenase (DPYD) variants rs11587873 (OR = 0.92; p = 6 × 10−5) and rs828054 (OR = 1.06; p = 1 × 10−4). Thirteen variants in the pyrimidine metabolism genes, DPYD, DPYS, PPAT, and TYMS, also interacted significantly with folate in a multivariant analysis (corrected p = 9.9 × 10−6) but collectively explained only 0.2% of OC risk. Although no other associations were significant after multiple testing correction, variants in SHMT1 in 1‐C transfer, previously reported with OC, suggested lower risk at higher folate (pinteraction = 0.03–0.006).ConclusionVariation in pyrimidine metabolism genes, particularly DPYD, which was previously reported to be associated with OC, may influence risk; however, stratification by folate intake is unlikely to modify disease risk appreciably in these women. SHMT1 SNP‐by‐folate interactions are plausible but require further validation. Polymorphisms in selected genes in purine metabolism were not associated with OC.

Abstract Background: There are several well-established environmental risk factors for ovarian cancer, and recent genome-wide association studies have also identified six variants that influence disease risk. However, the interplay between such risk factors and susceptibility loci has not been studied. Methods: Data from 14 ovarian cancer case–control studies were pooled, and stratified analyses by each environmental risk factor with tests for heterogeneity were conducted to determine the presence of interactions for all histologic subtypes. A genetic “risk score” was created to consider the effects of all six variants simultaneously. A multivariate model was fit to examine the association between all environmental risk factors and genetic risk score on ovarian cancer risk. Results: Among 7,374 controls and 5,566 cases, there was no statistical evidence of interaction between the six SNPs or genetic risk score and the environmental risk factors on ovarian cancer risk. In a main effects model, women in the highest genetic risk score quartile had a 65% increased risk of ovarian cancer compared with women in the lowest [95% confidence interval (CI), 1.48–1.84]. Analyses by histologic subtype yielded risk differences across subtype for endometriosis (Phet < 0.001), parity (Phet < 0.01), and tubal ligation (Phet = 0.041). Conclusions: The lack of interactions suggests that a multiplicative model is the best fit for these data. Under such a model, we provide a robust estimate of the effect of each risk factor that sets the stage for absolute risk prediction modeling that considers both environmental and genetic risk factors. Further research into the observed differences in risk across histologic subtype is warranted. Cancer Epidemiol Biomarkers Prev; 22(5); 880–90. ©2013 AACR.

Abstract Population stratification in case-control studies can result from differences in ancestral make-up between cases and controls due to sampling variation. Ancestry is therefore routinely estimated and controlled for in these studies. Although less common, it is also possible for ancestry to truly be associated to the disease of interest. Controlling for ancestry can then compromise the power to detect variants that underlie both ancestry and disease. Using data from a multi-center case-control study of epithelial ovarian cancer (OC) among women of European-American ethnicity in which case-control samples were drawn from four geographically distinct North-American sites, we developed a three-step method to investigate whether the stratification observed across the four sites is due to chance or to a non-spurious association between European ancestry and OC. First, we collapsed genome-wide data into two principal components (PCs) that represent the major axes of European ancestral variation, which correspond to north-south and to west-east geographical clines. Next, we determined the discriminant function based on these two PCs that best separates cases and controls for each individual study site and we used the largest angle between the four discriminant function vectors as a measure of similarity ranging from 0 degrees, where all four vectors are exactly the same, to 180 degrees where two of the vectors face exactly opposite directions. If stratification is due to sampling, it is unlikely that the four sites will present similar discriminant functions by chance alone. We then gauged significance of similarity by permuting the case control status across individuals within each site and recalculating the maximum angle between the discriminant function vectors, thus obtaining a null distribution for the statistic. We found that all four sites present the greatest separation between cases and controls on the west-east axis of ancestral variation, with a higher proportion of ovarian cancer cases presenting western ancestry. The largest angle between the four discriminant function vectors observed was of 36.5 degrees. Permutation testing showed this level of similarity between the functions to have a p-value < 0.01 and suggests that OC risk is somehow tied to European ancestry. It remains to be seen whether shared culture or other exposures such as parity or oral contraceptive use explain this connection or whether genetic variants underlie it and are potentially being missed due to routine ancestry control in association testing. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1678. doi:1538-7445.AM2012-1678

Abstract DNA copy number variations (CNVs) are a significant and ubiquitous source of human genetic variation. However, the influence of CNVs on cancer susceptibility remains poorly understood. Out of 83 genome-wide association studies (GWAS) on cancer to date, only a few studies found significant associations on germline CNVs and cancer. Here we analyzed data from our ongoing two-stage GWAS of four North American case-control studies to test the hypothesis that CNVs in germline DNA from peripheral blood lymphocytes may serve as risk factors for epithelial ovarian cancer (EOC). To reduce disease heterogeneity, we focused on the subset of cases with serous histology. The analysis was therefore based on 942 serous ovarian cancer patients and 1,682 healthy controls who were genotyped using the Illumina 610K quad array. Subjects with extreme noise and genomic waviness in log R ratio (LR) were excluded prior to segmentation; principal component analysis was performed to adjust for batch effects. CNV segmentation was performed on LR data from 22 autosomes using circular binary segmentation embedded in the Copy Number Analysis Module from Golden Helix SNP Variation Suite version 7. Copy number segment covariates were discretized based on the thresholds that signify a transition between copy number states (deletion/no deletion; duplication/no duplication) after the segmentation. Unconditional logistic regression on a log-additive model was used to evaluate the association between copy number states and serous EOC risk after adjusting for study sites. By comparing single marker copy number states at 388,958 SNPs on 22 autosomes, we observed a total of 134 SNPs significantly associated with risk of serous EOC with a p value below 10−6. Associations with deletion polymorphisms were observed on chromosomes 7, 8, 14, and 18 when controlling for false discovery rate at 1%; no duplication polymorphisms were significant. We observed a large deletion at chromosome 14 that occurred in 8.9% of cases but in only 3.9% of controls, with a p value of 5.59×10−8 (Odds Ratio (OR): 2.56, 95% confidence interval (CI): 1.82-3.60). Another common deletion on chromosome 7 occurred in 8.8% of cases and only 4.3% of controls (p=3.83×10−6; OR: 2.23, 95% CI: 1.60-3.10). Two additional regions on chromosomes 8 and 18 with deletion events less than 5% were also identified. Women who harbored the deletion on chromosome 8 were at lower risk of developing serous ovarian cancer (p=4.83×10−8; OR: 0.04, 95% CI: 0.01-0.30). Women who carried the deletion on chromosome 18 had an increased risk for serous EOC (p=9.04×10−7; OR: 7.26, 95% CI: 2.94-17.97). Further validation of these four regions using independent data sets is currently underway. In summary, this is the largest reported genome-wide study of CNVs and serous EOC risk. These preliminary results suggested that germline CNVs may play an important role in ovarian cancer susceptibility. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1649. doi:1538-7445.AM2012-1649

Abstract Mi(cro)RNAs are short non-coding RNA molecules that play a key role in carcinogenesis by regulating tumor suppressors and oncogenes. Published data has implicated miRNAs in ovarian cancer (OC) development and progression, and we hypothesize that single nucleotide polymorphisms (SNPs) in sites of miRNA: messenger RNA (mRNA) binding may influence OC risk by altering expression levels of targeted mRNAs. To evaluate associations between SNPs in miRNA binding sites and OC risk, we used bioinformatics tools and public databases to identify miRNA binding SNPs relevant to ovarian cancer. We then evaluated the frequency of approximately 1,100 SNPs in ∼20,000 epithelial OC cases and 20,000 controls represented in the international Collaborative Oncological Gene-environment Study. Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) between genotypes and case status, with adjustment for the first five principal components representing European ancestry. Log-additive genetic models were applied to each SNP, modeling the number of copies of the minor allele. Subgroup analysis was conducted for serous adenocarcinomas, the most predominant histologic subtype of epithelial OC. Preliminary analysis of 11,215 invasive epithelial OCs and 15,910 controls included four SNPs with P<10−6 and 1 SNP with P<10−5. Analysis of 6,215 invasive serous adenocarcinomas revealed two SNPs with P<10−7 and three SNPs with P<10−6. Noteworthy is rs6104808, a C>T SNP predicted to reside in a highly conserved miRNA binding site of BTBD3 (BTB POZ domain containing 3), a transcription factor suggested to be involved in cell proliferation, cancer progression, and response to platinum-based chemotherapy. rs6104808 was associated with a decreased risk of OC overall (OR (95% CI): 0.42 (0.28-0.62), P=1.26 x 10−5)), and the association was stronger among cases with serous adenocarcinoma (OR (95% CI): 0.30 (0.17-0.50), P=9.89 x 10−6)). This represents the largest, most comprehensive epidemiologic study to date to evaluate associations between miRNA binding site SNPs and OC susceptibility. Although based on a preliminary analysis, these data suggest a significant role and putative biological mechanism for common germline variants in miRNA binding sites leading to cancer development. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2927. doi:1538-7445.AM2012-2927

Abstract The etiology of ovarian cancer is poorly understood but there is clearly a heritable component. Efforts to identify susceptibility alleles rarely consider interactions among alleles or their joint effects because it quickly becomes computationally intractable. In this study, we sought to identify multi-SNP effects jointly with a pathway-based analysis (GSEA-SNP) of 1,952 EOC cases and 2,042 frequency-matched controls genotyped with the Illumina 610K array. All subjects were self-reported non-Hispanic non-Jewish Caucasians, with SNP and sample call rates > 95%. Subjects with ambiguous gender, unresolved identical genotypes and < 80% European ancestry were excluded. SNPs with MAF < 1% were excluded. Missing genotypes were inferred using Mach based on the HapMap CEU population. SNPs not within introns were annotated to genes within 100 bp. We retrieved the following databases of gene sets (GSs) from a compiled database, MsigDB: human chromosome and cytogenetic band, chemical and genetic perturbations, canonical pathways, microRNA binding targets, transcription factor targets (TFT), cancer gene neighborhood (CGN), Cancer modules and Gene Ontology. The GSEA-SNP approach calculates and rank orders the trend statistic for association between each SNP and EOC risk. The Enrichment Score (ES) estimates the overrepresentation of top-ranked SNPs for each GS; the statistical significance was estimated using 10,000 permutations. The ES was normalized according to the size of GS to yield Normalized Enrichment Score (NES). The false discovery (FDR) rate was estimated using NES to adjust for multiple hypothesis testing. A total of 5181 gene-sets were included in the analysis. When controlling the FDR at 15%, 14 of the GSs were highly enriched with association signals, including two chromosomal regions, 8q13 (p = 0.0055, FDR = 0.15) and 6p24 (p = 0.0012, FDR = 0.08). BIOCARTA_LYM_PATHWAY, a pathway related to cell adhesion and diapedesis of lymphocytes, was also significant (p = 0.0002, FDR = 0.12). A TFT GS, composed of genes with promoter regions around transcription start sites containing the motif GGCNRNWCTTYS, was associated with risk (p = 0.0004, FDR = 0.08). Currently, no known transcription factors bind to this computationally predicted motif. Molecular function of double stranded RNA binding was also enriched (p = 0.005, FDR = 0.10). The remaining enriched sets were CGN sets, for which the neighborhoods around the cancer genes were originally defined using correlation of gene expression from 4 large data sets of various cancer types. The enriched CGN included: CD48 (p = 0.011), CD53 (p = 0.009), CD97 (p = 0.011), INPP5D (p = 0.010), PTPN6 (p = 0.008), VAV1 (p = 0.011), ITGAL (p = 0.012), PTPRC (p = 0.012), and STAT6 (p = 0.010). In summary, these analyses detected biologically plausible GSs related to etiology of EOC, highlighting SNPs in core enrichment groups that were not identified using individual SNP tests. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4729. doi:10.1158/1538-7445.AM2011-4729

Abstract Background: Single nucleotide polymorphisms (SNP) in microRNA-related genes have been associated with epithelial ovarian cancer (EOC) risk in two reports, yet associated alleles may be inconsistent across studies. Methods: We conducted a pooled analysis of previously identified SNPs by combining genotype data from 3,973 invasive EOC cases and 3,276 controls from the Ovarian Cancer Association Consortium. We also conducted imputation to obtain dense coverage of genes and comparable genotype data for all studies. In total, 226 SNPs within 15 kb of 4 miRNA biogenesis genes (DDX20, DROSHA, GEMIN4, and XPO5) and 23 SNPs located within putative miRNA binding sites of 6 genes (CAV1, COL18A1, E2F2, IL1R1, KRAS, and UGT2A3) were genotyped or imputed and analyzed in the entire dataset. Results: After adjustment for European ancestry, no overall association was observed between any of the analyzed SNPs and EOC risk. Conclusions: Common variants in these evaluated genes do not seem to be strongly associated with EOC risk. Impact: This analysis suggests earlier associations between EOC risk and SNPs in these genes may have been chance findings, possibly confounded by population admixture. To more adequately evaluate the relationship between genetic variants and cancer risk, large sample sizes are needed, adjustment for population stratification should be carried out, and use of imputed SNP data should be considered. Cancer Epidemiol Biomarkers Prev; 20(8); 1793–7. ©2011 AACR.

Abstract Background: Mitochondria contribute to oxidative stress, a phenomenon implicated in ovarian carcinogenesis. We hypothesized that inherited variants in mitochondrial-related genes influence epithelial ovarian cancer (EOC) susceptibility. Methods: Through a multicenter study of 1,815 Caucasian EOC cases and 1,900 controls, we investigated associations between EOC risk and 128 single nucleotide polymorphisms (SNPs) from 22 genes/regions within the mitochondrial genome (mtDNA) and 2,839 nuclear-encoded SNPs localized to 138 genes involved in mitochondrial biogenesis (BIO, n = 35), steroid hormone metabolism (HOR, n = 13), and oxidative phosphorylation (OXP, n = 90) pathways. Unconditional logistic regression was used to estimate OR and 95% CI between genotype and case status. Overall significance of each gene and pathway was evaluated by using Fisher's method to combine SNP-level evidence. At the SNP level, we investigated whether lifetime ovulation, hormone replacement therapy (HRT), and cigarette smoking were confounders or modifiers of associations. Results: Interindividual variation involving BIO was most strongly associated with EOC risk (empirical P = 0.050), especially for NRF1, MTERF, PPARGC1A, ESRRA, and CAMK2D. Several SNP-level associations strengthened after adjustment for nongenetic factors, particularly for MTERF. Statistical interactions with cigarette smoking and HRT use were observed with MTERF and CAMK2D SNPs, respectively. Overall variation within mtDNA, HOR, and OXP was not statistically significant (empirical P > 0.10). Conclusion: We provide novel evidence to suggest that variants in mitochondrial biogenesis genes may influence EOC susceptibility. Impact: A deeper understanding of the complex mechanisms implicated in mitochondrial biogenesis and oxidative stress may aid in developing strategies to reduce morbidity and mortality from EOC. Cancer Epidemiol Biomarkers Prev; 20(6); 1131–45. ©2011 AACR.