Ramus, Susan J.

Abstract Background: Genome wide association studies (GWAS) have identified 20 loci associated with epithelial ovarian cancer (EOC) risk. Additional EOC risk loci await identification, and biological approaches may represent a useful strategy for overcoming sample size limitations. The ENCODE project recently concluded that only ∼1.2% of the genome encodes proteins, but at least 20% exhibits biological function and over 80% exhibits biochemical indices of function. Post-GWAS follow-up studies have firmly established that some associations are due to inter-individual differences in non-coding RNAs (ncRNAs). To estimate the magnitude of impact of variants in long non-coding RNAs (lncRNAs), we assessed enrichment of EOC-associated SNPs in lncRNA regions by comparing the density of EOC-associated loci between lncRNA regions, non-lncRNA regions, and the whole genome. Methods: The study population included ∼18,000 invasive EOC cases and 34,000 healthy controls of European ancestry from the Ovarian Cancer Association Consortium with GWAS data imputed to 1000 Genomes Project (1KGP) density. Density was compared with two measures: average chromosome length required for one EOC-associated SNP (kb/locus) and average number of tested SNPs containing one EOC-associated SNP (SNPs/locus). Coordinates and annotation for 13,870 lncRNA genes were downloaded from the publicly available GENCODE (v19) database and were used to annotate SNPs from the 1KGP imputed GWAS data, yielding 13,192 lncRNA genes with biallelic variants imputed at rsquare ≥0.25. A SNP was considered EOC-associated if it reached a significance level of P<10−5. Results: Genome-wide, 11.6% of the 15,123,646 tested SNPs fell within lncRNA regions. Of 5,294 EOC-associated SNPs that were identified, 27.7% were located within lncRNAs, a higher frequency than expected (<v:shape style = “WIDTH: 16.5pt; HEIGHT: 18pt” id = _x0000_i1026 equationxml = ‘14pχ2′ type = “#_x0000_t75”> = 9.35×10−22). Additionally, EOC-associated SNPs were located on average every 237.6 kb (or 1204 tested SNPs) in lncRNA regions versus every 657.7 kb (or 3489 SNPS) in non-lncRNA regions and every 541.5 kb (or 2857 SNPs) in the whole genome, clearly demonstrating an enrichment of EOC-associated loci in lncRNA regions. A total of 1,464 lncRNA SNPs from 53 unique lncRNAs associated with EOC risk (P<10−5); 70 of the identified lncRNA SNPs had P-values between 10−20 and 10−32, and 221 had P-values between 10−10 and 10−15, representing 21 unique regions > 500kb apart. Conclusions: These results justify efforts to integrate functional and population level genetic data on lncRNA regions to explore a new paradigm that addresses the problem of the missing heritability for cancer where restrictions in sample size and statistical power limit the ability to discover additional risk loci. Citation Format: Thomas A. Sellers, Brett M. Reid, Y. Ann Chen, Hui-Yi Lin, Edward Richards, Jamie Teer, Alvaro Monteiro, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Ellen Goode, Edwin Iverson, Leigh Pearce, Paul Pharoah, Catherine Phelan, Susan Ramus, Mary Anne Rossing, Joellen Schildkraut, Jin Cheng, Simon Gayther, Jennifer Permuth-Wey, on behalf of the Ovarian Cancer Association Consortium. Evidence that long non-coding RNA variants associate with epithelial ovarian cancer risk. [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 4633. doi:10.1158/1538-7445.AM2015-4633

Abstract Genome-wide association studies (GWAS) have identified several susceptibility regions that confer risk of two or more cancers. A region at 19p13 is associated with both breast and ovarian cancer risk in the general population as well as in BRCA1/BRCA2 mutation carriers. Using the iCOGs custom genotyping array, we analyzed 438 SNPs in this region in 7,435 ER-negative breast cancer cases and 42,599 controls from BCAC, and 15,347 ovarian cancer cases and 30,845 controls from OCAC and 15,252 BRCA1 mutation carriers. We identified two significant peaks of association. Peak 1, consisting of 13 highly correlated SNPs (r2>0.95), spans a 19.4kb region harboring the BABAM1, ANKLE1 and ABHD8 genes. Peak 1 SNPs are associated with serous ovarian cancer (top hit rs4808075, P = 9.2×10-20), ER-negative breast cancer (rs61494113, P = 1.1×10-13) and breast cancer in BRCA1 mutation carriers (rs61494113, P = 7.7×10-16). Peak 2 spans over 100kb and contains 7 SNPs associated with breast cancer in BRCA1 mutation carriers only (rs4464206, P = 8.9×10-8). Multiple assays were used to establish the putative functional roles of risk SNPs and candidate susceptibility genes in this region. Expression quantitative trait locus (eQTL) analyses identified significant genotype-gene expression correlations between genotype at the Peak 1 SNP rs480816 and ABHD8 expression in ovarian tumors (P = 3.0×10-5) and normal breast tissues (P = 2.8×10-3). The Peak 2 SNP, rs7246243, was significantly associated with BABAM1 expression (P = 5×10-3) in normal breast tissue only. Overexpression of BABAM1 in normal ovarian and breast cells did not modulate neoplastic phenotypes, whereas overexpression of ABHD8 induced a significant reduction in migration in both cell types in vitro. Differentially expressed genes in ABHD8 models, identified by RNAseq, were associated with cellular movement (P<1.82×10-44). Chromosome conformation capture (3C) identified an interaction between the ABHD8 promoter and a region containing 4 risk SNPs (rs4808075, rs10419397, rs56069439 and rs4808076) in breast and ovarian normal and cancer cells but only rs56069439 coincides with epigenetic enhancer marks in breast and ovarian cells. CRISPR/Cas9 genome editing was used to delete a 57bp region containing rs56069439 and expression of BABAM1, ANKLE1 and ABHD8 were measured. Taken together, these data suggest a common functional mechanism underlying risk of breast and ovarian cancer at this locus, mediated by rs56069439 variants differentially regulating expression of ABHD8, a gene involved in cell motility. Citation Format: Kate Lawrenson, Siddhartha Kar, Karoline Kuckenbaeker, Stacey Edwards, Qiyuan Li, Jonathan Tyrer, Jonathan Beesley, Kyriaki Michailidou, Susan Ramus, Alison Dunning, Fergus Couch, Alvaro Monteiro, Jacques Simard, Matthew Freedman, Douglas Easton, Georgia Chenevix-Trench, Paul Pharoah, Antonis Antoniou, Simon Gayther, OCAC, BCAC and CIMBA. Common functional mechanisms underlying pleiotropy at the 19p13.1 breast and ovarian cancer cusceptibility locus. [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 2783. doi:10.1158/1538-7445.AM2015-2783

Abstract Background: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. Methods: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. Cancer Epidemiol Biomarkers Prev; 24(10); 1574–84. ©2015 AACR.

Abstract Purpose: Chemotherapy resistance remains a major challenge in the treatment of ovarian cancer. We hypothesize that germline polymorphisms might be associated with clinical outcome. Experimental Design: We analyzed approximately 2.8 million genotyped and imputed SNPs from the iCOGS experiment for progression-free survival (PFS) and overall survival (OS) in 2,901 European epithelial ovarian cancer (EOC) patients who underwent first-line treatment of cytoreductive surgery and chemotherapy regardless of regimen, and in a subset of 1,098 patients treated with ≥4 cycles of paclitaxel and carboplatin at standard doses. We evaluated the top SNPs in 4,434 EOC patients, including patients from The Cancer Genome Atlas. In addition, we conducted pathway analysis of all intragenic SNPs and tested their association with PFS and OS using gene set enrichment analysis. Results: Five SNPs were significantly associated (P ≤ 1.0 × 10−5) with poorer outcomes in at least one of the four analyses, three of which, rs4910232 (11p15.3), rs2549714 (16q23), and rs6674079 (1q22), were located in long noncoding RNAs (lncRNAs) RP11-179A10.1, RP11-314O13.1, and RP11-284F21.8, respectively (P ≤ 7.1 × 10−6). ENCODE ChIP-seq data at 1q22 for normal ovary show evidence of histone modification around RP11-284F21.8, and rs6674079 is perfectly correlated with another SNP within the super-enhancer MEF2D, expression levels of which were reportedly associated with prognosis in another solid tumor. YAP1- and WWTR1 (TAZ)-stimulated gene expression and high-density lipoprotein (HDL)-mediated lipid transport pathways were associated with PFS and OS, respectively, in the cohort who had standard chemotherapy (pGSEA ≤6 × 10−3). Conclusions: We have identified SNPs in three lncRNAs that might be important targets for novel EOC therapies. Clin Cancer Res; 21(23); 5264–76. ©2015 AACR.

Abstract Background: Common genetic variants identified by genome-wide association studies and follow-up genotyping initiatives only explain a small proportion of the heritability of epithelial ovarian cancer (EOC). We hypothesized that some of the missing heritability may be explained by rare (minor allele frequency (MAF) <0.5%) and low-frequency (MAF 0.5-5%) protein-coding variants that are not well captured by genotyping arrays that focus on common variants. Methods: To examine the association between uncommon variants and EOC susceptibility, we genotyped 7,060 EOC cases and 6,712 controls from the Ovarian Cancer Association Consortium using the Affymetrix Axiom Exome Genotyping Array. This platform contains 300,785 putative functional coding variants selected from exome sequences of 12,000+ individuals representing multiple ethnicities and complex traits. After performing quality control (QC), we used unconditional logistic regression treating the number of minor alleles carried as an ordinal variable (log-additive model) to evaluate SNP-EOC risk associations. Genotype cluster plots were visually inspected for top-ranking variants to determine assay success, and allele frequencies of samples from the 1000 Genomes Project and other cohorts were evaluated for QC purposes. Results: A total of 13,318 samples (97%) passed QC, and 12,779 eligible samples (6,293 invasive serous and endometrioid cases and 6,486 controls) were included in the analyses. 280,737 (93%) of the 300,785 attempted markers were successfully genotyped and had call rates >90%. After removing 31,436 monomorphic markers, the 249,301 remaining markers were included in association analyses. We confirmed variants at previously reported EOC susceptibility loci (9p22, 3q25, 17cen-q21.3, and 8q24), with p-values between 10-5 and 10-11. Several correlated low-frequency non-synonymous variants (MAF=5%) residing in a novel EOC susceptibility gene at 3q25.31 were risk-associated. The most significant variant at 3q25.31 had an OR=1.36 and p = 5.58x10-8. Also noteworthy is a rare variant at 15q15.1-q21.1 (MAF=0.5%) that introduces a stop codon in a gene belonging to the tyrosine kinase family (OR=0.39, CI=0.26-0.58, p = 4.52x10-6). We also identified a more common synonymous coding variant in a phosphatase at 6q21.3 that was associated with increased risk (OR=1.22, CI=1.13-1.33, p = 1.84x10-6, MAF=9.6%). Population stratification and gene-based analyses are underway to further examine the impact of the newly-identified variants on EOC risk. A meta-analysis to include data from an additional 2104 EOC cases and 2516 controls genotyped with Illumina's HumanExome Beadchip rare variant array is also underway. Functional analysis of the most promising variants will follow. Conclusions: Preliminary data from this large-scale study reveals novel rare and low-frequency variants that may influence susceptibility to epithelial ovarian cancer. Citation Format: Jennifer Permuth-Wey, Y. Ann Chen, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Simon Gayther, Ellen L. Goode, Edwin Iversen, Alvaro N.A. Monteiro, Leigh Pearce, Paul D.P. Pharoah, Catherine M. Phelan, Ailith Pirie, Susan Ramus, Mary Ann Rossing, Joellen M. Schildkraut, Thomas A. Sellers, on behalf of the Ovarian Cancer Association Consortium. Exome genotyping array identifies rare and low-frequency variants that may be associated with ovarian cancer risk. [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 946. doi:10.1158/1538-7445.AM2014-946

Abstract An ovarian cancer Genome Wide Association Study (GWAS) identified 9p22.2 as a novel susceptibility locus with the most statistically significant single nucleotide polymorphisms (SNPs) located in an intergenic region near the Basonuclin 2 (BNC2) gene, which codes for a putative transcription regulator containing three pairs of zinc finger (ZF) domains. The minor alleles are protective in terms of ovarian cancer susceptibility. However, the molecular mechanisms by which these SNPs modify susceptibility remain largely unknown. The significant SNPs in the 9p22.2 locus lie in non-coding regions and therefore are hypothesized to affect the activity of regulatory elements and modify the expression of a target gene(s). In order to test this hypothesis we conducted fine mapping for the locus which delimited a ∼74kb region containing SNPs with a p-value less than 10-8. FAIRE-Seq and ChIP-Seq experiments for histone markers conducted in immortalized ovarian surface epithelial cells (IOSE) and fallopian tube epithelial cells (IFTE) were used to prioritize functional SNP candidates which overlap with regulatory elements. Luciferase assays tested the ability of these regulatory elements to activate transcription. Chromosome conformation capture (3C) experiments demonstrate a physical interaction between the BNC2 promoter and candidate regulatory elements containing risk-associated SNPs. Methylation Quantification at Trait Loci (mQTL) revealed an association between decreased methylation at the BNC2 promoter and the protective minor alleles. Expression analysis shows decreased expression of BNC2 in cancer versus normal tissue implicating tumor suppressor function of BNC2. Therefore the protective minor allele likely increases expression of BNC2 which in turn contains tumor suppressing properties that decrease ovarian cancer risk. BNC2 protein is in complex with transcriptional regulatory proteins, in particular the NURD complex components. Moreover, BNC2 acts as a transcriptional repressor in in vitro transfection assays indicating that it functions in transcriptional repression. We then used protein binding microarrays and CHIP-Seq experiments to identify its putative DNA binding motifs and its downstream target genes. Analysis of this data suggests that BNC2 functions in a regulatory transcription network that impacts on genes implicated in ovarian cancer with enrichment for genes in the TGF-beta response pathway. Citation Format: Melissa A. Buckley, Howard C. Shen, Gustavo A. Mendoza-Fandino, Nicholas T. Woods, Anxhela Gjyshi, Juliet French, Kate Lawrenson, Honglin Song, Jonathan Tyrer, Renato S. Carvalho, Alexandra Valle, Ann Chen, Sean Yoder, Gregory Bloom, Ya-Yu Tsai, Ally Yang, Timothy R. Hughes, Xiaotao Qu, Mine Cicek, Melissa Larson, Ellen Goode, Brooke Fridley, Susan Ramus, Georgia Chenevix-Trench, Paul Pharoah, Thomas A. Sellers, Simon Gayther, Alvaro N.A. Monteiro, Ovarian Cancer Association Consortium. Functional analysis of the 9p22 locus implicates the transcriptional regulation of BNC2 as a mechanism in ovarian cancer predisposition. [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 3285. doi:10.1158/1538-7445.AM2014-3285

Abstract Background Genome-wide association studies (GWAS) previously identified 8 new risk loci for all subtypes of epithelial ovarian carcinoma (EOC) and one specific to invasive serous EOC. One locus, at 2q31, was also associated with invasive mucinous EOC (mEOC) at P=7.3 x 10-7 (Nat Genet 2010:874). Here, we report new risk loci for mEOC, which is thought to develop from a borderline mucinous tumor. These loci may provide clues to the molecular basis of the disease. Methods We used genotype data from 4 GWAS of EOC and from multiple case-control studies in the Ovarian Cancer Association Consortium that had been genotyped using the iCOGS custom SNP panel (210k SNPs) developed for the Collaborative Oncological Gene-environment Study. We imputed genotypes of common variation across the genome using the 1000 Genomes Project reference panel and tested for association using log-additive unconditional regression models. Results Genotypes were available for 1,643 combined invasive and borderline mEOC and for 1,002 invasive-only mEOC of European ancestry. Three loci in new regions, and one locus in a previously published region, with minor allele frequency (MAF) > 1% and P ≤ 10-7 were found. The imputed SNP rs72831838 (imputation r2=0.67, MAF=0.15) is located at 2q13 in an intron of the PAX8 (paired box 8) gene (all mEOC OR=1.35, P=4.2 x 10-8 and invasive-only OR=1.43, P=9.6 x 10-8). PAX8 is a transcription factor and may be a Müllerian lineage marker that distinguishes carcinomas of gynecologic origin from other sites. The imputed variant at chr19:39745695 (imputation r2=0.61, MAF=0.32) is an insertion/deletion polymorphism located at 19q13.2 and falls within the MSRB1P1 (methionine sulfoxide reductase B1 pseudogene 1). This locus was associated with decreased risk (all mEOC OR=0.74, P = 2.1 x 10-9 and invasive-only OR=0.79, P = 8.1 x 10-5) and is enriched with the H3K27Ac histone mark that identifies active enhancers of gene expression. The imputed SNP rs6425050 (imputation r2=0.45, MAF=0.19) is located at 1q25 (all mEOC OR=1.38, P=4.7 x 10-8 and invasive-only OR=1.41, P=1.6x10-6). This SNP is intronic to PLA2G4A (phospholipase A2, group IVA), which encodes an enzyme that hydrolyzes membrane phospholipids for eicosanoid metabolism and signaling. None of these loci were associated with other EOC histological subtypes at P ≤ 10-7. The genotyped SNP, rs711830 (MAF=0.32), is located at 2q31.1 in the 3′ region of the HOXD3 homeobox gene (all mEOC OR=1.30, P=7.5 x 10-12 and invasive-only OR=1.26, P=7.8 x 10-7). This SNP is highly correlated (r2=0.99) with rs2072590, which is located 5.3kb upstream and previously reported by us to be associated with mEOC and invasive serous EOC (Nat Genet 2010:874). The HOXD3 locus is highly conserved and may also be a marker of Müllerian cell type origin. Conclusions The 3 new loci for mEOC require confirmation by genotyping. Fine mapping and functional analysis of all loci is needed in order to determine their likely target genes. Citation Format: Linda E. Kelemen, Jonathan Tyrer, Catherine M. Phelan, Susan J. Ramus, Andrew Berchuck, Simon A. Gayther, Ellen L. Goode, Celeste L. Pearce, Joellen M. Schildkraut, Georiga Chenevix-Trench, Alvaro N. Monteiro, Marc T. Goodman, Thomas A. Sellers, Paul PD Pharoah. GWAS identifies risk variants for mucinous ovarian carcinoma. [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 3283. doi:10.1158/1538-7445.AM2014-3283

Abstract Purpose: To analyze the effect of germline mutations in BRCA1 and BRCA2 on mortality in patients with ovarian cancer up to 10 years after diagnosis. Experimental Design: We used unpublished survival time data for 2,242 patients from two case–control studies and extended survival time data for 4,314 patients from previously reported studies. All participants had been screened for deleterious germline mutations in BRCA1 and BRCA2. Survival time was analyzed for the combined data using Cox proportional hazard models with BRCA1 and BRCA2 as time-varying covariates. Competing risks were analyzed using Fine and Gray model. Results: The combined 10-year overall survival rate was 30% [95% confidence interval (CI), 28%–31%] for non-carriers, 25% (95% CI, 22%–28%) for BRCA1 carriers, and 35% (95% CI, 30%–41%) for BRCA2 carriers. The HR for BRCA1 was 0.53 at time zero and increased over time becoming greater than one at 4.8 years. For BRCA2, the HR was 0.42 at time zero and increased over time (predicted to become greater than 1 at 10.5 years). The results were similar when restricted to 3,202 patients with high-grade serous tumors and to ovarian cancer–specific mortality. Conclusions: BRCA1/2 mutations are associated with better short-term survival, but this advantage decreases over time and in BRCA1 carriers is eventually reversed. This may have important implications for therapy of both primary and relapsed disease and for analysis of long-term survival in clinical trials of new agents, particularly those that are effective in BRCA1/2 mutation carriers. Clin Cancer Res; 21(3); 652–7. ©2014 AACR.

Abstract Tumor infiltrating regulatory T cells (Tregs) appear to play a role in survival in a number of solid tumors, including ovarian cancer. We assessed genetic variation via tag SNPs (N=749) in 25 Treg associated genes (CD28, CTLA4, FOXP3, IDO1, IL10, IL10RA, IL15, 1L17RA, IL23A, IL23R, IL2RA, IL6, IL6R, IL8, LGALS1, LGALS9, MAP3K8, STAT5A, STAT5B, TGFB1, TGFB2, TGFB3, TGFBR1, TGRBR2, and TGFBR3) in relation to ovarian cancer survival. SNPs were selected based on r2 ≥ 0.8, MAF ≥ 0.05, 5 kb upstream and downstream from the gene. We had SNP and outcome data for ovarian cancer from 10,084 combined ovarian cancer cases, including 5,248 high grade serous, 1,452 endometrioid, 661 mucinous, and 795 clear cell cases of European descent across multiple studies from the Ovarian Cancer Association Consortium (OCAC). Cox proportional hazards regression modeling was used to estimate per-allele hazard ratios (HRs) and 95% confidence intervals (CIs) for associations with overall survival, adjusting for age at diagnosis, population substructure PCs, study site, histology (for the all case analysis), tumor stage, tumor grade and oral contraceptive use. The strongest associations were found for endometrioid histologic subtype and IL2RA SNPs (maximum r2=0.67) rs11256497 [HR=1.42, 95% CI: 1.22-1.64; p=5.7 x 10−6], rs791587 [HR=1.36, 95% CI: 1.17-1.57; p=6.2 x 10−5], rs2476491 [HR=1.40, 95% CI: 1.19-1.64; p=5.6 x 10−5], and rs10795763 [HR=1.35, 95% CI: 1.17-1.57; p=7.9 x 10−5], as well as clear cell ovarian cancer and CTLA4 SNP rs231775 [HR=0.67, 95% CI: 0.54-0.82; p=9.3 x 10−5]. No other associations were observed at p<1 x 10−4. Overall, this study provided evidence that variation in genes related to Tregs, particularly IL2RA and CTLA4, influence ovarian cancer survival. Citation Format: Bridget Charbonneau, Keith Knutson, Robert A. Vierkant, Julie M. Cunningham, Zachary C. Fogarty, Kimberly R. Kalli, Matthew J. Maurer, Ann L. Oberg, Brooke L. Fridley, Claudia C. Preston, Paul D.P. Pharoah, Susan J. Ramus, Catherine M. Phelan, Kunle Odunsi, Kirsten Moysich, Ellen L. Goode. Polymorphisms in regulatory T cell related genes and ovarian cancer survival. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4844. doi:10.1158/1538-7445.AM2013-4844