Abstract 5008: Genome-wide methylation and ovarian cancer survival
Authors: Janet E. Olson, Mine S. Cicek, Brooke L. Fridley, Sebastian M. Armasu, Melissa C. Larson, Robert A. Vierkant, David L. Rider, Kimberly R. Kalli, Julie M. Cunningham, Ellen L. Goode
Journal: Cancer Research (2012)

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&amp;lt; 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