Cicek, Mine S.

Abstract Background Ovarian cancer is the fifth most common cause of cancer death in women in the US; approximately 15,000 women will die from this disease in 2011 (ACS, 2011). The 5 year survival rate for stage IV disease is only 18%. Only a handful of independent significant prognostic factors are known, including tumor stage at surgery, size of residual tumor at the end of primary surgery, and age at diagnosis. Understanding how the variation of cytosine methylation in the context of cytosine-guanine dinucleotides (CpGs) affects complex disease etiology and survival is the current focus of many ongoing research studies. We conducted an epigenome-wide study of methylation in ovarian cancer cases to evaluate whether variation in methylation of CpG sites in genomic DNA may be associated with ovarian cancer survival. Methods Subjects included cases from an ongoing case-control study. The Mayo Clinic Ovarian Cancer Study is a clinic-based study that recruits ovarian cancer cases within 12 months of diagnosis. Pre-treatment, germline DNA from lymphocytes from 137 cases was bisulfite-modified, amplified and genotyped on the Illumina 450K methylation chip and included in these analyses. Quality control (QC) analyses include the elimination of all methylation probes with a single nucleotide polymorphism (SNP) or insertion/deletion (in/del) at the same location; removal of non-specific probes; and estimation of bisulfite conversion rates using embedded control probes. Planned analyses include assessment of clinical covariates (age, stage, extent of surgical debulking, grade, presence of ascites) to determine which are associated with overall survival in our data. Additional analyses will assess the age- and multi-variate-adjusted association of each methylation probe with overall survival using Cox proportional hazards regression models with each methylation probe modeled as a continuous variable. Data will be summarized using Manhattan plots. These analyses will be repeated using ‘time to recurrence’ as the outcome variable, with recurrence defined as time to ovarian cancer recurrence/progression or death. Results Bioinformatics analyses suggest that 36,659 probes were located at the site of a SNP or in/del and should be removed from future analyses. Another 448 probes had a detection rate of p< 0.01 and 6630 probes had signals for the negative control samples; all were removed from analyses. A total of 43,802 probes were removed. In addition, ten cases were excluded due to either poor bisulfite conversion (N=9) or extremely low raw methylation values across all probes (N=1). This leaves a total of 127 cases for analyses. Results from planned analyses will be presented, including estimation of the association of methylation probes with both overall survival and time to recurrence. Conclusions Data to be presented will describe whether there is any evidence that methylation of genomic DNA in ovarian cancer cases is associated with outcome of ovarian cancer. 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 5008. doi:1538-7445.AM2012-5008

Abstract Ovarian cancer is the leading cause of death in gynecologic malignancies in the United States with most patients presenting with late stage disease; patients receive the same treatment regardless of histology or tumor characteristics. The mismatch repair (MMR) molecular pathway is well-defined and known to be involved in up to 20% of ovarian cancers; however, association of deficient v proficient MMR status (dMMR v pMMR status) with risk factors and outcome is not well understood. We are conducting extensive molecular testing of the MMR genes MLH1, MSH2, MSH3, MSH6, and PMS2 on Mayo Clinic invasive epithelial ovarian cancer cases. First, the prevalence of dMMR tumors will be estimated in ovarian cancer cases (n=496) based on loss of expression of MLH1, MSH2, MSH3, MSH6, and PMS2 determined by immunohistochemistry staining of primary antibodies using negative and positive controls. Staining of tissue microarrays (TMAs) is complete; triplicate cores will be scored independently for presence or loss of protein expression by a board-certified pathologist. Second, for those dMMR cases, the possible cause of MMR deficiency will be evaluated considering germline and somatic mutations. The loss of expression of each protein will be characterized as germline if a deleterious mutation is present in peripheral blood or somatic if the pathogenic mutation is only present in tumor tissue. In cases with MLH1 loss somatic hypermethylation will also be considered. Analysis of germline mutation data will include all 496 cases and somatic mutations data will include a subset of cases tested with frozen tumor DNA (n=292) using Fluidigm access array targeted resequencing. Third, the clinical features of dMMR disease will be compared to those of pMMR; in particular, age at diagnosis, histopathology, and disease outcome. Among cases in this analysis, the majority have high-grade serous disease with a mean age at diagnosis of 61 years, about half had recurrence or progression (n=243) of which two-thirds (n=167) are deceased. Finally, known and suspected ovarian cancer risk factors (family history, smoking, body mass index, parity, use of hormone therapy, and genetic variation in susceptibility loci at 2q31, 3q25, 8q24, 9p22, 17q21, and 19p13) will be analyzed by MMR phenotype. Risk factor questionnaire data is available on 462 cases (93%), as well as 737 population controls with germline genome-wide genotype data. About half of the cases (n=231) report a 1st or 2nd degree family member with breast or ovarian cancer. Given the limited knowledge about ovarian cancer etiology and the poor prognosis of advanced disease, it is very important to study risk factors with this molecular subtype. The ovarian cancer dMMR phenotype may have distinct clinicopathological features that could guide risk stratification and be useful in diagnostics and therapeutics. This is the largest study characterizing MMR in an ovarian cancer population to date. 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 2619. doi:1538-7445.AM2012-2619

Abstract As pathways of the immune system play an important role in multiple malignancies, we assessed the association between single-nucleotide polymorphisms (SNPs) in inflammation-related genes and risk of ovarian cancer in a multi-site case-control study. Using a custom array, we genotyped 930 epithelial ovarian cancer cases and 1,037 controls for SNPs in ALOX12, ALOX15, ALOX5, CCL11, CCL2, CCL3, CCR3, CRP, CXCL16, IL10, IL15RA, IL18, IL1A, IL1B, IL1RN, IL4R, IL6, IL6R, IL7R, IL8RA, IL8RB, IL9, NOS3, PTGS1, PTGS2, TLR2, and TNF. After analysis by logistic regression, SNPs with p<0.10 were evaluated in an independent data set of 3,143 cases and 2,102 controls from the Follow-up of Ovarian Cancer Genetic Association and Interaction Studies (FOCI) collaboration. Combined analysis revealed association with interleukin 1, alpha (IL1A) SNPs (rs17561 and rs4848300, r2=0.990, p=0.005) which varied by histological subtype (heterogeneity p=0.03). For example, IL1A rs17561, which results in a missense change in amino acid at position 114 and correlates with multiple inflammatory phenotypes, was inversely associated with risk of clear cell, mucinous, and endometrioid subtypes, but not with the serous subtype (Table 1). Additional data on IL1A rs17561 in an even larger collection of ovarian cancer cases and controls are pending and will be analyzed soon. We also found that genotype at rs1864414 in ALOX5 (arachidonate 5-lipoxygenase) was associated with decreased risk combined across subtypes (OR 0.86, 95% CI 0.78-0.95; p=0.002). Thus, inherited variation in IL1A and ALOX5 appears to have a role in ovarian cancer risk, though it is limited to rarer subtypes for IL1A. These data add to existing literature on the importance of inflammation in tumorigenesis and growing evidence of subtype-specific traits in ovarian cancer and may provide important clues on prevention. 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 2603. doi:1538-7445.AM2012-2603

Abstract Ovarian carcinoma is a significant cause of cancer mortality in women in the United States. Increasing evidence has demonstrated that differential methylation status in lymphocyte DNA may be linked to risk of carcinogenesis. We are investigating the differential DNA methylation in germline DNA obtained from pre-treatment ovarian cancer cases (n=256) and individually-age matched controls (n=274) using the Illumina Infinium Human Methylation 27K BeadChip. We are first studying methylation and the common moderate-risk alleles for ovarian cancer on chromosomes 2q31, 3q25, 8q24, 9p22, 17q21, and 19p13. Within each locus, we correlated single nucleotide polymorphism (SNP) genotypes with methylation values at relevant nearby CpG sites. Preliminary results are available on the first set of 84 cases and 90 controls. At 2q31, cases with TG or TT genotype at rs2072590 were hypomethylated at HOXD1 (a homeobox transcription factor) compared to cases with GG genotype (mean beta TG/TT=0.08, GG=0.09, p=0.034); and at 17q21, cases with AG or GG genotype at rs9303542 were hypomethylated at SKAP1 (a T-cell adaptor protein) compared to cases with AA genotype (mean beta AG/GG=0.14, AA=0.16, p=0.045). At these two loci, similar trends were seen among controls. Logistic regression adjusted for age and methylation chip was then used to assess the association between SNP genotype and ovarian cancer risk, with and without inclusion of the relevant methylation value. At HOXD1 rs2072590, the per-allele ovarian cancer risk of 1.34 attenuated to 1.25 with inclusion of the HOXD1 methylation value as a covariate, suggesting that the disease association may be mediated in part through methylation. Though based on preliminary data, results are consistent with a role for inherited variation on germline methylation at HOXD1 and SKAP1. Analysis of methylation on additional genotyped cases and controls is underway. Finally, because, trans effects may also exist, we are assessing relationships between genotype and methylation at other loci throughout the genome. Such correlative molecular studies have the potential to help elucidate mechanisms underlying associations from genome-wide association studies. 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 5616. doi:10.1158/1538-7445.AM2011-5616

Abstract The importance of inflammation pathways to the development of many human cancers prompted us to examine the associations between single-nucleotide polymorphisms (SNP) in inflammation-related genes and risk of ovarian cancer. In a multisite case–control study, we genotyped SNPs in a large panel of inflammatory genes in 930 epithelial ovarian cancer cases and 1,037 controls using a custom array and analyzed by logistic regression. SNPs with P < 0.10 were evaluated among 3,143 cases and 2,102 controls from the Follow-up of Ovarian Cancer Genetic Association and Interaction Studies (FOCI) post-GWAS collaboration. Combined analysis revealed association with SNPs rs17561 and rs4848300 in the interleukin gene IL1A which varied by histologic subtype (Pheterogeneity = 0.03). For example, IL1A rs17561, which correlates with numerous inflammatory phenotypes, was associated with decreased risk of clear cell, mucinous, and endometrioid subtype, but not with the most common serous subtype. Genotype at rs1864414 in the arachidonate 5-lipoxygenase ALOX5 was also associated with decreased risk. Thus, inherited variation in IL1A and ALOX5 seems to affect ovarian cancer risk which, for IL1A, is limited to rarer subtypes. Given the importance of inflammation in tumorigenesis and growing evidence of subtype-specific features in ovarian cancer, functional investigations will be important to help clarify the importance of inherited variation related to inflammation in ovarian carcinogenesis. Cancer Res; 72(5); 1064–9. ©2012 AACR.

AbstractPrevious studies suggest that enzymes involved in the androgen metabolic pathway are susceptibility factors for prostate cancer. Estrogen metabolites functioning as genotoxins have also been proposed as risk factors. In this study, we systematically tested the hypothesis that common genetic variations for those enzymes involved in the androgen and estrogen metabolic pathways increase risk for sporadic and familial prostate cancer. From these two pathways, 46 polymorphisms (34 single nucleotide polymorphisms, 10 short tandem repeat polymorphisms, and 2 null alleles) in 25 genes were tested for possible associations. Those genes tested included PRL, LHB, CYP11A1, HSD3B1, HSD3B2, HSD17B2, CYP17, SRD5A2, AKR1C3, UGT2B15, AR, SHBG, and KLK3 from the androgen pathway and CYP19, HSD17B1, CYP1A1, CYP1A2, CYP1B1, COMT, GSTP1, GSTT1, GSTM1, NQO1, ESR1, and ESR2 from the estrogen pathway. A case-control study design was used with two sets of cases: familial cases with a strong prostate cancer family history (n = 438 from 178 families) and sporadic cases with a negative prostate cancer family history (n = 499). The controls (n = 493) were derived from a population-based collection. Our results provide suggestive findings for an association with either familial or sporadic prostate cancer with polymorphisms in four genes: AKR1C3, HSD17B1, NQO1, and GSTT1. Additional suggestive findings for an association with clinical variables (disease stage, grade, and/or node status) were observed for single nucleotide polymorphisms in eight genes: HSD3B2, SRD5A2, SHBG, ESR1, CYP1A1, CYP1B1, GSTT1, and NQO1. However, none of the findings were statistically significant after appropriate corrections for multiple comparisons. Given that the point estimates for the odds ratio for each of these polymorphisms are <2.0, much larger sample sizes will be required for confirmation. (Cancer Epidemiol Biomarkers Prev 2007;16(5):969–78)