Abstract Primary and acquired chemotherapy resistance remains a major challenge in the treatment of ovarian cancer. We hypothesize that heritable polymorphisms might be associated with clinical outcome. Through the Ovarian Cancer Association Consortium, we have collected detailed clinical data from a large number of ovarian cancer patients. We have conducted association analyses of progression-free survival (PFS) and overall survival (OS) for 2,901 European women with ovarian carcinoma for ∼8 million imputed SNPs with minor allele frequency ≥ 0.02 and good imputation quality (imputation r2 ≥ 0.3) from the iCOGS experiment (Pharoah et al Nat Genet. 2013). Cox regression models adjusted for known prognostic factors were used to assess the log-additive effects of SNPs on PFS and OS in 2,825 patients who underwent cytoreductive surgery and received any chemotherapy (‘all chemo’) and in the subset of 1,098 patients who underwent cytoreductive surgery followed by ≥ 4 cycles of carboplatin AUC 5 or 6 and paclitaxel 175 or 135 mg/m2 intravenously (‘standard chemo’). We identified five SNPs at four loci that were significantly associated with outcome (p ≤ 10-7) in at least one of four analyses (Table). Analysis of expression data for genes within a 1Mb region flanking each lead SNP indicates significant associations between nearby genes and ovarian cancer survival. Of particular interest is the heat shock protein crystalline αB (CRYAB) at 11q23.1. We have also identified significant associations with KIAA1598 and RAVER2. Further analysis of these loci in a larger genotyped sample is necessary to definitively identify SNP(s) associated with outcome. Our study adds to the growing evidence that genetic variants are associated with ovarian cancer prognosis. Table: SNPs associated with ovarian cancer outcome and gene expression Overall Survival (P)*Progression-Free Survival (P)*Lead SNPChromosome LocusImputation R²Expression AnalysisAll chemoStandard chemoAll chemoStandard chemors1429768671p31.30.742.14E-0512.69E-044.68E-055.11E-073.64E-09rs559375217q32.30.600.198.58E-082.32E-052.80E-031.85E-03rs7885346210q26.110.602.23E-0724.57E-036.57E-081.65E-016.85E-03rs1089121911q23.10.841.53E-0531.51E-059.50E-081.50E-042.32E-04rs3579103211q23.10.811.53E-0531.66E-055.88E-086.46E-051.87E-04*P-values are adjusted for known confounders of ovarian cancer outcomes; FIGO stage, grade, histology, residual disease, and additionally for age at diagnosis for OS.1 RAVER2; 2 KIAA1598; 3 CRYAB Citation Format: Sharon E. Johnatty, Jonathan Tyrer, Jonathan Beesley, Bo Gao, Yi Lu, Stuart MacGregor, Anna deFazio, Paul Pharoah, Ellen Goode, Georgia Chenevix-Trench. Identification of genetic loci associated with ovarian cancer prognosis. [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 3286. doi:10.1158/1538-7445.AM2014-3286
Abstract 4679: A multi-stage genome-wide association study on response to chemotherapy in ovarian cancer
Abstract We performed a multi-stage genome-wide association study (GWAS) for drug response in ovarian cancer. We selected 313 chemotherapy treated patients from the Australian Ovarian Cancer Study (AOCS). Patients were treated with paclitaxel/carboplatin and the trait of interest was Progression Free Survival (PFS). We maximized power for a fixed genotyping budget by genotyping individuals from the tails of the distribution: 94 with good survival and 94 with poor survival, taking into account extent of residual disease following surgery. Patients were genotyped on Illumina HumanOmni1-Quad arrays (1140419 loci).Two further cohorts with measures of PFS and whole genome data available; 134 ovarian patients from the Mayo clinic (genotyped on Illumina HumanHap 610 arrays, 620901 loci) and 68 patients from The Cancer Genome Atlas ovarian cancer set (genotyped on Illumina Human1M arrays, 1199187 loci) were meta-analyzed with the AOCS set (stage 1). We have imputed all the stage 1 samples with reference of the 1000 Genome data to allow more direct comparison of SNPs not common to all of the arrays used (up to 6 million SNPs with good imputation quality). Based on the chemotherapy treatment received by each patient, we assigned the patients into primary and secondary analysis, with primary analysis using a more strictly defined treatment subgroup. We followed up the stage 1 findings by genotyping 26 SNPs in more than 3,000 samples collected from 8 study sites of Ovarian Cancer Association Consortium (OCAC). These 26 SNPs were mainly genotyped SNPs, chosen from 23 distinct regions showing the strongest association with chemotherapy response from either primary or secondary analysis. 2 SNPs showed nominal significance in the replication sample (chr 12: rs1861932, chr 22: rs708444). We are currently genotyping more regions to seek replication of the initial findings. In summary, we sought to identify genes that underlie individual differences in chemoresistance. In the future, typing variations in these genes will be important for personalizing drug regimes for patients. 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 4679. doi:10.1158/1538-7445.AM2011-4679
Platinum Sensitivity–Related Germline Polymorphism Discovered via a Cell-Based Approach and Analysis of Its Association with Outcome in Ovarian Cancer Patients