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DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P < 7.94 × 10−7. Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely MAPT, HOXB3, ABHD8, ARHGAP27, and SKAP1. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. Significance: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.

Background: Ovarian cancer is the deadliest gynecologic cancer. Standard treatments for advanced stage high-grade serous ovarian cancer, the most common type, include (1) primary cytoreductive surgery (PCS) followed by adjuvant chemotherapy or (2) neoadjuvant chemotherapy (NACT) with interval debulking surgery. Patients in whom PCS is unlikely to yield optimal cytoreduction to no visible residual disease (R0) or who have medical contraindications to PCS are recommended to undergo NACT. Previous studies on associations between environmental factors and risk of any macroscopic residual disease have yielded inconsistent results. We aimed to (1) comprehensively examine the associations between demographic, lifestyle and reproductive factors and risk of residual disease after PCS; and (2) develop and internally validate a risk prediction model based on these factors. Methods: We used pooled data on 3,492 women who had PCS following a diagnosis with advanced stage high-grade serous ovarian, fallopian tube or primary peritoneal cancers from the Ovarian Cancer Association Consortium. Fifteen exposures of interest included age at diagnosis, menopausal status, race/ethnicity, education level, first-degree family history of ovarian cancer, endometriosis, smoking, body mass index, parity, incomplete pregnancy, tubal ligation, use of combined oral contraceptives, depot-medroxyprogesterone acetate, estrogen (ET), and combined estrogen-progestin therapy. We fit logistic regression models to examine each exposure-residual disease association in 80% of the data (n=2,794; random selection of participants). We developed a risk prediction model including the factors with p-values ≤0.2. Area under the receiver operating characteristic curve (AUC) was used to assess the model’s discrimination in the remaining 20% of the data (n=698). Results: Of the 3,492 participants, 2,003 (57%) had residual disease following PCS. Older age at diagnosis was associated with an increased risk of residual disease (OR=1.07 per five years, 95% CI 1.03-1.11). In contrast, a family history of ovarian cancer (OR=0.63, 95% CI 0.42-0.95) or ET use for 5+ years (OR=0.61, 95% CI 0.39-0.96) were associated with achieving R0. These above factors were included in the risk prediction model as were race/ethnicity, personal history of endometriosis, and smoking, whose p-values ≤0.2. The model showed modest performance in the validation set (AUC=0.64). Conclusions: Younger age at diagnosis, family history of ovarian cancer, and long-term ET use were associated with achieving R0 following PCS. Future studies incorporating genetic and clinical factors to improve the risk prediction for residual disease following PCS are warranted. Citation Format: Minh Tung Phung, Andrew Berchuck, Ellen L. Goode, Marc T. Goodman, Gillian E. Hanley, Jean Richardson, Bronwyn Grout, Anne Chase, Cindy McKinnon Deurloo, Beth Y. Karlan, Toon Van Gorp, Keitaro Matsuo, Karen McLean, Malcolm C. Pike, Joellen M. Schildkraut, Kathryn L. Terry, Anna DeFazio, Penelope M. Webb, Paul D. P. Pharoah, Susan J. Ramus, Celeste Leigh Pearce. Environmental factors associated with residual disease after ovarian cancer primary cytoreduction surgery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2248.

Background: Infertility is related to both nulligravidity and endometriosis, which are both well-established risk factors for ovarian cancer. Infertility is also characterized by various underlying causes and can be treated with different types of fertility drugs. However, most studies to date have been unable to properly address these important issues when examining the infertility-ovarian cancer association due to small numbers of patients and a lack of detailed infertility and risk factor information. Methods: We pooled self-reported data from 8,324 invasive, epithelial ovarian cancer cases and 13,325 control women in eight population-based case-control studies participating in the Ovarian Cancer Association Consortium (OCAC) to study the infertility-ovarian cancer relationship. Women classified as having a history of infertility were those who had spoken to a doctor about infertility problems or those who had regular sexual intercourse without birth control for a prolonged period (usually one year) without getting pregnant. Cause of infertility as well as use of fertility drugs was examined among those who experienced infertility issues. These associations with risk of ovarian cancer were evaluated using logistic regression models and quantified using odds ratios (ORs) and 95% confidence intervals (CIs). Gravidity and endometriosis were considered in the analyses as well as potential confounding factors. Results: Overall, infertility was not associated with risk of ovarian cancer (OR=1.02, 95% CI 0.95-1.09). However, women who reported their infertility was due to problems with ovulation or menstruation showed a decreased risk (OR=0.72, 95% CI 0.52-1.01 and OR=0.62, 95% CI 0.43-0.91, respectively) whereas women who reported their infertility was due to endometriosis were at an increased risk (OR=1.54, 95% CI 1.19-1.98). Among women who reported infertility issues, use of fertility drugs was not associated with an increased risk of ovarian cancer regardless of their gravidity status (OR=0.89, 95% CI 0.76-1.05). Conclusions: The relationship between infertility and risk of ovarian cancer is complex. Although infertility does not appear to be an independent risk factor for ovarian cancer, specific causes of infertility may be differentially associated with ovarian cancer risk, which may shed light on the disease’s underlying etiology. In addition, for women experiencing infertility issues, use of fertility drugs did not show an increased risk of ovarian cancer, which may have important clinical implications. Citation Format: Alice W. Lee, Minh T. Phung, Allan Jensen, Anna H. Wu, Daniel W. Cramer, Francesmary Modugno, Holly Harris, Jennifer A. Doherty, Joellen Schildkraut, Kathryn L. Terry, Kirsten B. Moysich, Malcolm C. Pike, Marc T. Goodman, Penelope M. Webb, Susanne K. Kjaer, Celeste L. Pearce. Exploring the impact of infertility and its treatments on risk of ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 736.

Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P < 2.2 × 10−6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 10−7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P < 1.47 × 10−3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis. Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. Cancer Res; 78(18); 5419–30. ©2018 AACR.

Background: Ovarian cancer is the eighth-most common cancer among women. Although a number of established risk factors exist for this disease, analyses of these exposures have largely not taken into account potential interactions. We present an interaction analysis of eight ovarian cancer risk factors, followed by the creation of modifiable and non-modifiable risk scores for the disease. Methods: Data used in this analysis come from nine studies in the Ovarian Cancer Association Consortium (OCAC): one from Australia, one from Europe and seven from the US. Analyses were restricted to pre-menopausal women without first-degree family histories of ovarian cancer, leading to a final study population of 1504 cases and 3515 controls. Five potentially modifiable predictors (oral contraceptive (OC) use duration, body mass index, tubal ligation, hysterectomy and breastfeeding) and three non-modifiable predictors (parity, incomplete pregnancies and history of endometriosis) were considered. A complete analysis of interactions between the eight variables as well as with age, race/ethnicity, education level and study site was conducted. No statistically significant pairwise interactions were found with likelihood ratio statistics, thus suggesting no departure from multiplicativity in the odds ratios. The modifiable and non-modifiable risk scores were calculated as the product of the odds ratios for each group of exposures. Logistic regression was used to model the association between ovarian cancer and the risk scores. Age, race/ethnicity, education level and study site were included in the model. Results: The associations between the second, third and fourth quartiles of the modifiable risk score compared to the lowest quartile were 1.67 (95% CI 1.35-2.09), 2.18 (95% CI 1.76-2.71) and 3.72 (95% CI 3.04-4.57), respectively. The odds ratios for the non-modifiable risk score were 1.17 (95% CI 0.95-1.44), 1.24 (95% CI 0.99-1.54) and 2.06 (95% CI 1.68-2.53), respectively for the second, third and fourth quartiles compared to the first. Women in the highest quartiles of both the modifiable and non-modifiable risk scores, representing 14.6% of the women, had a 7.67-fold increased risk of ovarian cancer (95% CI 4.68-11.39) compared to women in the lowest quartiles for both risk scores (3.6% of the women). Conclusions: Pre-menopausal women in the highest risk quartiles have a substantially elevated risk of ovarian cancer based on these eight exposures. Modifiable factors contribute more than non-modifiable factors to ovarian cancer risk among pre-menopausal women with no family history in our study. Women in the highest risk group (fourth quartile of both risk scores) could reduce their risk by intervening on the modifiable exposures; for example, 63% of women in this group had not used oral contraceptives and 93% had not had tubal ligation. However, careful consideration of the risks and benefits of such prevention measures is needed. Citation Format: Minh Tung Phung, Bhramar Mukherjee, Alice W. Lee, Penelope M. Webb, Harvey A. Risch, Jennifer Anne Doherty, Holly R. Harris, Marc T. Goodman, Roberta B. Ness, Francesmary Modugno, Allan Jensen, Susanne K. Kjaer, Kathryn L. Terry, Daniel W. Cramer, Argyrios Ziogas, Hoda Anton-Culver, Malcolm C. Pike, Anna H. Wu, Celeste Leigh Pearce. Ovarian cancer risk factors multiply to create high risk in pre-menopausal women [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3498.

Introduction Although most women with high-grade serous ovarian cancer (HGSC) die within five years, approximately 15% will survive for 10 or more years. The factors contributing to this exceptional survival are currently unknown, but are thought to be a complex interaction between clinical, genetic, immunologic, and lifestyle factors. The purpose of this study is to qualitatively explore factors that may influence exceptional ovarian cancer survival. Methodological Approach Four focus groups, one each in Los Angeles (California), Ann Arbor (Michigan), New York (New York) and Edmonton (Alberta, Canada), were conducted. Women previously diagnosed with HGSC who have survived 5 or more years were invited to participate. Physical activity, diet, meditation, prayer, treatment, integrative medicine, and side effects were explored in the semi-structured focus group interviews. All four sessions were audiotaped and transcribed. The transcriptions were coded by two individuals using grounded theory. The coded transcripts were analyzed using Dedoose. Findings Of the 26 women who participated, 24 were diagnosed with HGSC. Two women, one with a stage III, low-grade mucinous tumor and another with a MMMT carcinosarcoma, did not meet our inclusion criteria, but were not asked to leave. Among the 24 women with HGSC, 19 have survived 10 or more years, two 8-9 years and three 5-7 years; all but one woman had stage III or IV disease. Three overarching themes were uncovered: (a) Survivors were highly motivated to improve lifestyle factors, including but not limited to fitness and diet, and had, in fact, done so; (b) Survivors had a strong life purpose, which manifested as positivity, taking charge, and self-advocacy; and (c) Survivors were able to draw on strong support systems, which included family, friends, support groups, faith, and healthcare workers. Conclusion HGSC long-term survivors have varying experiences with their cancer, but share motivation and persistence, strong life purpose, and strong support systems. This study sheds light on how the specific behaviors and attitudes of patients may contribute to their long-term survival with HGSC. Focus groups are preparatory to further prospective studies that will determine whether short term and long term survivors differ on these characteristics. Our results highlight the need for more research to gain better understanding of the role that life purpose and support systems play in survival with HGSC. Citation Format: Aliya Alimujiang, Lilah Khoja, Ashley Wiensch, Malcolm C. Pike, Penelope Webb, Anne Chase, Jean Richardson, Celeste Leigh Pearce. Ovarian cancer survivors' views of factors that influenced their exceptional survival: A qualitative study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3288.

High-risk susceptibility genes explain

Introduction Previous observational studies investigating height, body mass index and serum lipid levels as prognostic factors in ovarian cancer have been inconclusive. In addition to possible influences of reverse causation, it is possible that factors such as diet, socio-economic status and other lifestyle factors are confounding true associations. Mendelian Randomization (MR) utilises genotype data for variants associated with phenotypes of interest to create genetic risk scores for these modifiable exposures. One advantage of using genetic markers as proxies is that they are determined from birth and are therefore unaffected by confounding variables. We aim to use MR to investigate the association between height, BMI and serum lipid levels (high-density lipoprotein (HDL), low-density lipoprotein (LDL) and triglycerides) and ovarian cancer prognosis in the absence of confounding variables. Methods We used data from 12,908 invasive ovarian cancer cases with 5,813 events from 26 studies in the Ovarian Cancer Association Consortium. All individuals were of European ancestry. We calculated genetic risk scores for each individual for height, BMI and serum lipids by taking the sum of the alleles associated with the trait, weighted by the size of their effect on the trait. The genetic risk scores were then included in a Cox proportional hazards model adjusted for study and two principal components to test for association with prognosis. For the analysis of height, we included 422 uncorrelated single nucleotide polymorphisms identified by the Genetic Investigation of Anthropometric Traits (GIANT) consortium as associated with height at genome-wide significance. In the analysis of BMI, we included 32 SNPs associated with BMI in analyses by the GIANT consortium. In order to account for the pleiotropy between the three lipid types we included the genetic risk scores for each of the three traits in a joint analysis. SNPs identified by the Global Lipids Genetics Consortium as associated with lipid levels were included: 95 with HDL, 82 with LDL and 64 with triglycerides. Results We found no evidence of association between the five genetic risk scores and ovarian cancer prognosis. The genetic risk score for height had an estimated hazard ratio of 1.01, 95% confidence interval 0.94 - 1.08, p-value = 0.82. The hazard ratio for BMI was 1.00, 95% CI 0.95 - 1.05, p-value = 0.99. The hazard ratios for HDL, LDL and triglycerides were 1.03(0.94-1.13), 1.02(0.94-1.12) and 1.08(0.96-1.21) respectively with p-values = 0.53, 0.58 and 0.19. Conclusion Our study does not provide any evidence of association between height, BMI and serum lipid levels and ovarian cancer prognosis. Citation Format: Ailith Pirie, Suzanne C. Dixon, Penelope M. Webb, Wei Zheng, Paul D. P. Pharoah, on behalf of the Ovarian Cancer Association Consortium. The effect of height, BMI and serum lipid levels on ovarian cancer prognosis in over 12,000 women: a Mendelian randomization study. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4637. doi:10.1158/1538-7445.AM2015-4637

INTRODUCTION: Observational studies have reported positive associations between higher body mass index (BMI) and risks of borderline ovarian tumors and non-high grade serous ovarian cancer (non-HGSC), but the lack of association observed for HGSC may be due to bias arising from weight loss before diagnosis. Observational studies also suggest a positive association between greater height and ovarian cancer risk, but confounding factors may be obscuring the true relationship. The Mendelian randomization (MR) technique uses genetic markers as proxies for environmental risk factors, and can overcome the limitations of bias and confounding which affect observational studies. AIM / METHODS: This study used MR to elucidate the relationship between body size (BMI and height) and risk of ovarian cancer. We pooled data from 16,395 cases and 23,003 controls, all genetically European, from 39 studies in the Ovarian Cancer Association Consortium. We constructed a weighted genetic risk score (GRS) for each trait, summing trait-increasing alleles at 31 single nucleotide polymorphisms (SNPs) associated with BMI and 609 SNPs associated with height in genome-wide association studies, weighting alleles by published β-coefficients for their effect on the trait. Each GRS was a strong instrument for the trait (F-statistics 33.8 [BMI] and 516 [height]). In a two-stage predictor substitution MR approach, we used multivariate logistic regression to model case-control status on body size predicted by each GRS. Study-specific estimates per 5-unit increase in predicted BMI or height were pooled to generate pooled odds ratios (OR) and 95% confidence intervals (CI) using random-effects meta-analysis. Our primary hypotheses were that genetic BMI would be associated with increased risk of non-HGSC but not HGSC and genetic height would be associated with increased risk of ovarian cancer overall. RESULTS: Higher genetically-predicted BMI was associated with increased risk of non-HGSC cancer (OR 1.37, 95% CI 1.02-1.83 per 5-unit increase) but not HGSC (OR 1.05, 95% CI 0.83-1.33). In secondary analyses stratified by behavior/subtype, the strongest association was seen for low grade/borderline serous cancers (OR 2.02, 95% CI 1.24-3.30). Women with greater genetically-predicted height had a modestly increased risk of all (invasive and borderline) ovarian tumors (OR 1.06, 95% CI 1.01-1.11 per 5 cm). In secondary analyses stratified by histologic subtype, the strongest association was seen for clear cell cancers (OR 1.20, 95% CI 1.04-1.38). CONCLUSION: This study is the first to apply MR to investigate ovarian cancer risk factors. These data confirm results from epidemiologic studies, suggesting that obesity is causally associated with non-HGSC, but does not increase risk of the most common HGSC subtype. They also support an association between height and ovarian cancer. Citation Format: Suzanne C. Dixon, Christina M. Nagle, Aaron P. Thrift, Paul D.P Pharoah, Ailith Pirie, Celeste Leigh Pearce, Wei Zheng, Penelope M. Webb, for the Ovarian Cancer Association Consortium. Association of adult body mass index and height with risk of ovarian cancer in 39,000 women: Results of a Mendelian randomization study. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 881. doi:10.1158/1538-7445.AM2015-881

Introduction: In 2008 The International Agency for Research on Cancer concluded that combined oral contraceptives (OCs) are a cause of cancer of the breast and cervix but decrease the risk of ovarian and endometrial cancer. They also concluded that estrogen-only hormone replacement therapy (HRT) increases the risk of both endometrial and ovarian cancer, while use of estrogen plus progestogen (combined) HRT increases the risks of breast cancer. The level of risk associated with each cancer type varies by duration and recency of use of hormones. Our aim was to calculate the proportion of breast and gynecological cancers arising in Australian women (population attributable fractions - PAF) that could be attributed to these commonly used hormonal medications. Methods: We calculated PAFs using the standard formula, which requires an estimate of the relative risk for each exposure-cancer association and the prevalence of the causal factor in the population. Relative risks were obtained from published pooled or meta-analyses of the associations and prevalence estimates were derived from Australian National Health Survey estimates or other large national studies. For factors inversely associated with cancer we calculated the “prevented fraction” and estimated the number of cancers that were prevented due to exposure to the factor. Results: The estimated PAFs suggested that fewer than 5% of breast and gynecological cancers in Australia in 2010 could be attributed to oral contraceptive use and estimates were similar for HRT use. However, the calculated preventive fractions for oral contraceptives suggested that the numbers of endometrial and ovarian cancers may have been 46% and 24% higher respectively if no Australian women had used OCs. Given combined HRT increases breast cancer risk and breast cancer is much more common than endometrial or ovarian cancer we also assessed the likely effect if all women taking combined HRT instead took estrogen-only HRT. Under this scenario, we estimate the absolute numbers of ovarian and endometrial cancers would increase slightly but the number of breast cancers attributable to HRT use would decrease substantially. Conclusions: Our analyses suggest that the use of combined OCs confers more benefit than harm with respect to cancer incidence, with a small increase in breast/cervical cancer diagnoses weighed against a much larger decrease in numbers of endometrial and ovarian cancers. In contrast, our results indicate that there would be fewer cancers overall if women did not use HRT. When HRT is required, most guidelines recommend that women with a uterus take combined HRT to prevent endometrial cancer. However, our findings suggest that, in terms of total cancer burden, it might be safer for women to avoid progestogens and use estrogen-only HRT for symptom relief. Future studies should examine this possibility. Citation Format: Susan J. Jordan, Louise Wilson, David Whiteman, Penelope Webb, PAF Project Group. The proportion of breast and gynecological cancers in Australian women that can be attributed to the use of oral contraceptives and hormone replacement therapy. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 866. doi:10.1158/1538-7445.AM2015-866

Excess body weight is a known risk factor for endometrial cancer but whether it differentially affects histological subtypes of endometrial cancer is unclear. The two proposed main subtypes are the “estrogen-dependent Type I” and “non estrogen-dependent and clinically aggressive Type II”. Little is known about risk factors for Type II tumors mainly because most epidemiologic studies lack sufficient cases to study these rare tumors separately. Here we examined the association between recent adult body mass index (BMI) and endometrial tumor subtypes in a pooled analysis of 25 studies in the Epidemiology of Endometrial Cancer Consortium (E2C2). Individual-level data from 10 cohort studies and 15 case-control studies provided a total of 14,409 endometrial cancer cases and 35,950 controls for this analysis. Cohort studies were analyzed using a nested case-control design. The majority of women were white (86%) and postmenopausal (83%). Endometrial cancer cases were classified into two subtypes: Type I (endometrioid adenocarcinomas, adenocarcinoma tubular, papillary adenocarcinomas, mucinous adenocarcinomas, adenocarcinomas with squamous metaplasia, n=13,286) and Type II (serous, squamous cell, small cell, mixed cell, n=1,123). The associations of BMI with the risk of tumor subtypes were evaluated by calculating odds ratios (OR) and 95% confidence intervals (95% CI) using polytomous logistic regression models. Potential confounders included in the analysis were age, race, parity, age at menarche, oral contraceptive (OC) use, menopausal hormone (PMH) use, and smoking status. BMI was positively associated with both Type I and Type II tumors, but the association was stronger for Type I than for Type II tumors (P value for the difference in OR between Type I and Type II was 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 1029. doi:1538-7445.AM2012-1029

Proteases such as the matrix metalloproteinase (MMP) family of proteases have emerged as being important to cancer aetiology and progression. Differences in gene and protein expression have been reported to be associated with many cancers and increased MMP expression is frequently reported to be associated with poor prognostic features. Although no MMP SNPs have been identified to be associated with cancer in all genome-wide association studies published to date, this is not be surprising given the extremely poor coverage of these gene families (1-38% for individual genes), and the knowledge that virtually all study designs to date have been underpowered to detect the small effect sizes expected for common SNPs. We have embarked on a study to assess the relevance of MMP expression and their SNPs in predisposition and prognosis of endometrial cancer, a largely hormonally driven cancer. An extensive literature review revealed that 62/69 studies reported overexpression of MMPs to be associated with poor prognostic features (grade, stage or survival) of hormone-related cancers, including endometrial cancer. Analysis of endometrial tumour MMP gene expression data from 18 different publications was undertaken to identify differentially expressed MMPs (>2-fold) associated with tumour predisposition and/or prognosis, based preferably on raw expression data but otherwise on reported gene lists. Although coverage of the MMP gene family was incomplete for the different expression platforms, this exercise prioritized 14 MMPs for further study in relation to risk and/or prognosis of endometrial cancer. We then mined the stage 1 results for the genome-wide association study we are undertaking to identify novel genetic variants associated with endometrial cancer risk, which involves comparison of 1285 Australian and British endometrial cancer cases of endometrioid subtype reporting Caucasian ethnicity scanned with the Illumina 610K BeadChip, and existing genome-wide scan control data available from the Wellcome Trust Case Control Consortium. A SNP falling in a prioritized MMP with only 19% coverage was found to be significant at P=0.002 (trend test). This SNP has been selected for confirmation in replication sample sets from 9 studies for association with endometrial cancer predisposition, and will be analyzed with SNPs from other prioritized MMP genes for association with prognostic indicators such as grade. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2842.

Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC Introduction: Alterations in components of the stromal tissue that underlie the epithelium can initiate, promote or inhibit epithelial tumorigenesis. Decorin (DCN) and lumican (LUM) are stromal genes with reduced expression in serous ovarian cancer. We hypothesized that single nucleotide polymorphisms (SNPs) in these genes may influence susceptibility to serous ovarian cancer. Methods: To test this hypothesis, we compared genotype frequencies of 11 tagSNPs in DCN and LUM between 397 Caucasian cases with primary serous ovarian cancer and 920 Caucasian controls in two studies conducted at Mayo Clinic and Duke University (discovery set). Associations were evaluated further in a third Caucasian population of 436 cases and 1,098 controls in Australia (replication set). TagSNPs were selected from unrelated Caucasian samples within HapMap based on the following criteria: (i) minor allele frequency ≥ 0.05, (ii) pairwise linkage disequilibrium (LD) of r2 ≥ 0.8, and (iii) location within, and 5kb upstream and downstream of, each gene region. Genotyping was performed using the Illumina GoldenGate™ assay and associations between SNPs and serous cancer were evaluated using unconditional logistic regression to estimate per allele odds ratios (OR) and 95% confidence intervals (95%CI). Untyped genotypes for DCN rs13312816 in the discovery set, and for DCN rs3138165 and LUM rs17018765 in the replication set, were imputed using the MACH software. Results: In the discovery set, we observed inverse associations between DCN rs3138165 (OR=0.7; 95%CI=0.5-1.0), DCN rs13312816 (OR=0.7; 95%CI=0.5-1.0), DCN [rs516115][1] (OR=0.8; 95%CI=0.7-1.0) and LUM rs17018765 (OR=0.7; 95%CI=0.5-1.0) and risk of serous ovarian cancers (all Ptrend=0.06). Associations were confirmed in the replication set for DCN rs3138165 (OR=0.6; 95%CI=0.4-0.9; Ptrend=0.009), DCN rs13312816 (OR=0.7; 95%CI=0.5-0.9; Ptrend=0.01) and LUM rs17018765 (OR=0.6; 95%CI=0.4-0.9; Ptrend=0.008), but not for DCN [rs516115][1] (Ptrend=0.20). To increase statistical power, data from the discovery and replication sets were combined (833 cases and 2,013 controls) following confirmation of no statistical heterogeneity in the ORs between study sites. In the combined sample, associations were strengthened for DCN rs3138165 (OR=0.7; 95%CI=0.5-0.9; Ptrend=0.002), DCN rs13312816 (OR=0.7; 95%CI=0.5-0.9; Ptrend=0.002), DCN [rs516115][1] (OR=0.9; 95%CI=0.8-1.0; Ptrend=0.03) and LUM rs17018765 (OR=0.6; 95%CI=0.5-0.8; Ptrend=0.001). All four SNPs were in the same LD block on chromosome 12, suggesting that serous ovarian cancer susceptibility may be driven by a single, correlated variant in the region. Conclusion: The findings of this study suggest that genetic variation in DCN and LUM may influence susceptibility to serous ovarian cancer and contribute to the mounting evidence that supports the role of the stroma in epithelial ovarian cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2854. [1]: /lookup/external-ref?link_type=GEN&access_num=rs516115&atom=%2Fcanres%2F70%2F8_Supplement%2F2854.atom