Goode, Ellen L.

AbstractMediation analysis has been a useful tool for investigating the effect of mediators that lie in the path from the independent variable to the outcome. With the increasing dimensionality of mediators such as in (epi)genomics studies, high-dimensional mediation model is needed. In this work, we focus on epigenetic studies with the goal to identify important DNA methylations that act as mediators between an exposure disease outcome. Specifically, we focus on gene-based high-dimensional mediation analysis implemented with kernel principal component analysis to capture potential nonlinear mediation effect. We first review the current high-dimensional mediation models and then propose two gene-based analytical approaches: gene-based high-dimensional mediation analysis based on linearity assumption between mediators and outcome (gHMA-L) and gene-based high-dimensional mediation analysis based on nonlinearity assumption (gHMA-NL). Since the underlying true mediation relationship is unknown in practice, we further propose an omnibus test of gene-based high-dimensional mediation analysis (gHMA-O) by combing gHMA-L and gHMA-NL. Extensive simulation studies show that gHMA-L performs better under the model linear assumption and gHMA-NL does better under the model nonlinear assumption, while gHMA-O is a more powerful and robust method by combining the two. We apply the proposed methods to two datasets to investigate genes whose methylation levels act as important mediators in the relationship: (1) between alcohol consumption and epithelial ovarian cancer risk using data from the Mayo Clinic Ovarian Cancer Case-Control Study and (2) between childhood maltreatment and comorbid post-traumatic stress disorder and depression in adulthood using data from the Gray Trauma Project.

AbstractBackgroundBRCA1 methylation has been associated with homologous recombination deficiency, a biomarker of platinum sensitivity. Studies evaluating BRCA1-methylated tubal and ovarian cancer (OC) do not consistently support improved survival following platinum chemotherapy. We examine the characteristics of BRCA1-methylated OC in a meta-analysis of individual participant data.MethodsData of 2636 participants across 15 studies were analyzed. BRCA1-methylated tumors were defined according to their original study. Associations between BRCA1 methylation and clinicopathological characteristics were evaluated. The effects of methylation on overall survival (OS) and progression-free survival (PFS) were examined using mixed-effects models. All statistical tests were 2-sided.Results430 (16.3%) tumors were BRCA1-methylated. BRCA1 methylation was associated with younger age and advanced-stage, high-grade serous OC. There were no survival differences between BRCA1-methylated and non–BRCA1-methylated OC (median PFS = 20.0 vs 18.5 months, hazard ratio [HR] = 1.01, 95% CI = 0.87 to 1.16; P = .98; median OS = 46.6 vs 48.0 months, HR = 1.02, 95% CI = 0.87 to 1.18; P = .96). Where BRCA1/2 mutations were evaluated (n = 1248), BRCA1 methylation displayed no survival advantage over BRCA1/2-intact (BRCA1/2 wild-type non–BRCA1-methylated) OC. Studies used different methods to define BRCA1 methylation. Where BRCA1 methylation was determined using methylation-specific polymerase chain reaction and gel electrophoresis (n = 834), it was associated with improved survival (PFS: HR = 0.80, 95% CI = 0.66 to 0.97; P = .02; OS: HR = 0.80, 95% CI = 0.63 to 1.00; P = .05) on mixed-effects modeling.ConclusionBRCA1-methylated OC displays similar clinicopathological features to BRCA1-mutated OC but is not associated with survival. Heterogeneity within BRCA1 methylation assays influences associations. Refining these assays may better identify cases with silenced BRCA1 function and improved patient outcomes.

5510 Background: Transcriptional profiling of ovarian cancers has proven to be complex. As such it has been difficult to validate existing signatures across studies. Cancer Genome Atlas (TCGA) researchers have identified four molecular subtypes of high-grade serous ovarian cancer (HGSOC). However, survival duration did not differ significantly for the TCGA subtypes. Potential limitations of the TCGA data include short clinical follow-up (45% were alive at the time of last follow-up) and the need to unify gene expression measures from multiple platforms. Methods: Clinically annotated stage-II–IV HGSOC samples (n = 175) with >70% tumor cell content were profiled using the Agilent Whole Human Genome 4 x 44K chip. To identify subtypes non-negative matrix factorization (NMF) of mRNA expression was performed using ~2000 genes with the highest variability across patients. In parallel differentially expressed genes were identified using the Rosetta Similarity Search Tool as well as analysis of variance based on genes known to be involved in epithelial to mesenchymal transition. Results: Median follow-up time was 35 months (range, 0–202 months, 12% were alive at the time of last follow-up). NMF clustering confirmed four HGSOC subtypes (immunoreactive, differentiated, proliferative, and mesenchymal) on the basis of gene content in the clusters. Pathway signatures with therapeutic potential were identified for individual or multiple subtypes. Survival differed significantly between the four molecular subgroups in univariate (Hazard Ratio [HR] 2.4, 95% CI 1.5-4.1, p = 0.007) and multivariate (HR 2.3, 95% CI 1.3-4.0, p = 0.003) analyses when accounting for age, stage, grade, and postoperative residual tumor. Using the supervised clustering approach two distinct molecular subtypes of HGSOC based on epithelial and mesenchymal gene expression signatures were identified with significantly different survival outcomes. Conclusions: Here we independently validate and expand upon the molecular TCGA classification of HGSOC. The potential of these two prognostic classifiers may lie in their ability to recognize categories of patients that are more likely to respond to particular therapies.

5077 Background: A standard of care (SOC) for the adjuvant treatment of ovarian and primary peritoneal cancer is a platinum-based intravenous (IV) chemotherapy doublet. Intraperitoneal (IP) chemotherapy is also a SOC, but the high incidence of grade 3/4 adverse events has limited its acceptance among clinicians. To identify genetic markers for completion of IP chemotherapy, we analyzed SNPs in four genes known to play a role in metabolism of platinum or taxane drugs. Methods: Patients diagnosed with primary or recurrent stage III or IV epithelial ovarian or primary peritoneal cancer who had primary or secondary debulking surgery at Mayo Clinic (Rochester, MN) between January 2007 and February 2009 followed by IP chemotherapy were included in this study. A cycle was defined as IV paclitaxel (135mg/m2) on day one, IP cisplatin (100mg/ m2) on day two, and IP paclitaxel (60mg/ m2) on day eight. With prior consent from the patient, peripheral blood was obtained before treatment for extraction of germline DNA. Using a custom Illumina BeadXpress 96-plex panel, SNPs in GSTM1 (N=7), ABCB1 (N=57), CYP3A4 (N=7), and CYP2C8 (N=25) were genotyped. The association between SNPs in these subsets of genes and completion of IP chemotherapy was analyzed using linear regression. Results: Thirty-seven patients were included in this study and 16 (43.2%) completed IP chemotherapy. Twenty-two out of the fifty-seven ABCB1 SNP’s were associated with the number of cycles (p<0.15). There were no significant associations for GSTM1, CYP3A4 and CYP2C8 SNP’s. The minor A allele at missense SNP rs2229109 in the ABCB1 gene was present in five (31.2%) who completed treatment and only one (4.8%) who did not (p<0.007). However, the later was due to catheter complication. There was no association between rs2229109 and overall or progression-free survival. Conclusions: Our findings suggest that SNP rs2229109 in ABCB1 gene is associated with completion of IP chemotherapy, and potentially, less toxicity from chemotherapy. Thus, these patients may be optimal candidates for IP chemotherapy. Further studies in a larger population are needed.

PURPOSETo estimate age-specific relative and absolute cancer risks of breast cancer and to estimate risks of ovarian, pancreatic, male breast, prostate, and colorectal cancers associated with germline PALB2 pathogenic variants (PVs) because these risks have not been extensively characterized.METHODSWe analyzed data from 524 families with PALB2 PVs from 21 countries. Complex segregation analysis was used to estimate relative risks (RRs; relative to country-specific population incidences) and absolute risks of cancers. The models allowed for residual familial aggregation of breast and ovarian cancer and were adjusted for the family-specific ascertainment schemes.RESULTSWe found associations between PALB2 PVs and risk of female breast cancer (RR, 7.18; 95% CI, 5.82 to 8.85; P = 6.5 × 10−76), ovarian cancer (RR, 2.91; 95% CI, 1.40 to 6.04; P = 4.1 × 10−3), pancreatic cancer (RR, 2.37; 95% CI, 1.24 to 4.50; P = 8.7 × 10−3), and male breast cancer (RR, 7.34; 95% CI, 1.28 to 42.18; P = 2.6 × 10−2). There was no evidence for increased risks of prostate or colorectal cancer. The breast cancer RRs declined with age ( P for trend = 2.0 × 10−3). After adjusting for family ascertainment, breast cancer risk estimates on the basis of multiple case families were similar to the estimates from families ascertained through population-based studies ( P for difference = .41). On the basis of the combined data, the estimated risks to age 80 years were 53% (95% CI, 44% to 63%) for female breast cancer, 5% (95% CI, 2% to 10%) for ovarian cancer, 2%-3% (95% CI females, 1% to 4%; 95% CI males, 2% to 5%) for pancreatic cancer, and 1% (95% CI, 0.2% to 5%) for male breast cancer.CONCLUSIONThese results confirm PALB2 as a major breast cancer susceptibility gene and establish substantial associations between germline PALB2 PVs and ovarian, pancreatic, and male breast cancers. These findings will facilitate incorporation of PALB2 into risk prediction models and optimize the clinical cancer risk management of PALB2 PV carriers.

Abstract Epithelial ovarian cancer (EOC) is the most common gynecological cancer, and ranks fifth in cancer deaths among women in the United States. Previous studies have identified several circulating proteins biomarkers for EOC risk, such as CA125 antigen and insulin-like growth factor-1 (IGF-1). However, previous studies on protein biomarkers for EOC were limited with small sample sizes, and only a few proteins investigated. In this study, we integrated genomics and proteomics data to search for novel circulating protein biomarkers for EOC risk. We constructed study instruments using genetic variants for protein quantitative trait loci (pQTL) for over 1,400 circulating proteins. Beta coefficients and standard errors of the selected pQTL variants in relation to EOC risk were obtained from 25,509 EOC cases and 40,941 controls from the Ovarian Cancer Association Consortium (OCAC). An inverse-variance weighted method was used to evaluate the association of these genetically predicted protein levels and risk of overall and serous EOC. We identified 35 protein biomarkers, for which their genetically predicted levels were significantly associated with the risk of either overall or serous EOC (false discovery rate &lt;0.05). There are 25 proteins showing significant associations with both overall and serous EOC; most of the associations were stronger for serous EOC than overall EOC. The association for 31 proteins could be attributed, in part, to variants at ABO 9q34.2, a known ovarian cancer susceptibility locus. Five ABO locus-related proteins are in the PI3K-Akt signaling pathway, including insulin-like growth factor 1 receptor, hepatocyte growth factor receptor, interleukin-3 receptor subunit alpha, insulin receptor, and vascular endothelial growth factor receptor 2. Four of these proteins are also in the Rap1 and Ras signaling pathway. These five proteins are all inversely associated with the risk of overall EOC, with odds ratios ranging from 0.64 to 0.93 per unit increase in genetic risk scores (p values: 7.55×10-7 to 5.66×10-2). Four EOC associated proteins which were not influenced by variants in 9q34.2 are microfibrillar-associated protein 2, protein delta homolog 1, semenogelin-2, and netrin-G1, all of which showed significant associations with overall EOC, but not the serous subtype. Our study identifies potential novel biomarkers for ovarian cancer and suggests that genetic variants at locus 9q34.2 may play a role in the relation between levels of these proteins and risk of ovarian cancer. Citation Format: Guochong Jia, Xiang Shu, Xiao-Ou Shu, Jirong Long, Qiuyin Cai, Kirsten B. Moysich, Ellen L. Goode, Thomas A. Sellers, Wei Zheng. Genetically predicted concentration of circulating proteins and epithelial ovarian cancer risk [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 598.

Abstract Purpose: The majority of patients with high-grade serous ovarian cancer (HGSC) develop progressive disease following primary treatment, with a five-year survival rate of ~30%. However, a subset of patients have an extraordinary response to treatment and ~15% survive more than ten years (long-term survivors). The Multidisciplinary Ovarian Cancer Outcomes Group (MOCOG) aims to uncover factors that influence long-term survival of HGSC patients. Here, we investigated the genomic and immunologic determinants of exceptional survival of this deadly disease. Experimental Design: Patient characteristics and clinical histories were evaluated to identify patients diagnosed with advanced stage (Stage IIIC/IV) and histopathologically confirmed HGSC with greater than 10-year overall survival. Whole-genome sequencing (WGS) was performed on primary tumors (median 78x coverage) and germline samples (median 39x coverage) of 55 long-term survivors. Primary tumor samples were also characterised by RNA sequencing, DNA methylation profiling and immunohistochemistry. Results: A total 38 (69%) of long-term surviving patients had residual disease following surgery, suggestive of highly chemo-sensitive disease. Most patients (41, 75%) were alive at last follow-up and 26 (47%) were progression-free. Somatic mutation burden was higher in primary tumors of long-term survivors relative to controls (316 unselected HGSC patients in The Cancer Genome Atlas). Genome-wide mutational signatures were predominantly Signature 3 (associated with homologous recombination deficiency), Signature 1 (age related) and Signatures 5, 8 and 16 (unknown etiology). Inactivation of the tumor suppressor RB1 by structural rearrangements or homozygous deletion was frequent in long-term survivors, with 33% of tumors showing associated loss of RB1 protein expression by immunohistochemistry compared to 13% of unselected HGSC controls (n=207; P = 0.001). Staining of adjacent tumor tissue revealed that RB1 loss was associated with increased numbers of PD-1+ tumor-infiltrating lymphocytes (P = 0.015) and MHC class I on tumor cells (P = 0.002). In an independent HGSC cohort (n=847), RB1 protein loss was associated with prolonged survival (HR: 0.75, P &lt; 0.001) compared to patients with RB1 positive tumors. Furthermore, co-occurrence of germline mutations in BRCA1 or BRCA2 and RB1 loss was associated with a significantly longer overall survival compared to patients with retained RB1 protein expression and no germline BRCA mutation (HR: 0.44, P &lt; 0.001). Conclusions: This study delineates the full landscape of genomic alterations in HGSC of long-term survivors. Our findings indicate that specific mutations might be associated with enhanced host immune responses and long-term survival. Citation Format: Dale W. Garsed, Ahwan Pandey, Sian Fereday, Kathryn Alsop, Maartje C. Wouters, Flurina Saner, Jessica A. Beach, Katy Milne, Catherine J. Kennedy, Joy Hendley, Nadia Traficante, Celeste L. Pearce, Malcolm C. Pike, Multidisciplinary Ovarian Cancer Outcomes Group, Susan J. Ramus, Martin Köbel, Brad H. Nelson, Ellen L. Goode, Anna deFazio, David D. Bowtell. The genomic landscape of high-grade serous ovarian cancer in long-term survivors [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 2722.

AbstractAn association between genetic variants in the vitamin D receptor (VDR) gene and epithelial ovarian cancer (EOC) was previously reported in women of African ancestry (AA). We sought to examine associations between genetic variants in VDR and additional genes from vitamin D biosynthesis and pathway targets (EGFR, UGT1A, UGT2A1/2, UGT2B, CYP3A4/5, CYP2R1, CYP27B1, CYP24A1, CYP11A1, and GC). Genotyping was performed using the custom‐designed 533,631 SNP Illumina OncoArray with imputation to the 1,000 Genomes Phase 3 v5 reference set in 755 EOC cases, including 537 high‐grade serous (HGSOC), and 1,235 controls. All subjects are of African ancestry (AA). Logistic regression was performed to estimate odds ratios (OR) and 95% confidence intervals (CI). We further evaluated statistical significance of selected SNPs using the Bayesian False Discovery Probability (BFDP). A significant association with EOC was identified in the UGT2A1/2 region for the SNP rs10017134 (per allele OR = 1.4, 95% CI = 1.2‐1.7, P = 1.2 × 10−6, BFDP = 0.02); and an association with HGSOC was identified in the EGFR region for the SNP rs114972508 (per allele OR = 2.3, 95% CI = 1.6‐3.4, P = 1.6 × 10−5, BFDP = 0.29) and in the UGT2A1/2 region again for rs1017134 (per allele OR = 1.4, 95% CI = 1.2‐1.7, P = 2.3 × 10−5, BFDP = 0.23). Genetic variants in the EGFR and UGT2A1/2 may increase susceptibility of EOC in AA women. Future studies to validate these findings are warranted. Alterations in EGFR and UGT2A1/2 could perturb enzyme efficacy, proliferation in ovaries, impact and mark susceptibility to EOC.

AbstractBackground:Germline DNA copy number variation (CNV) is a ubiquitous source of genetic variation and remains largely unexplored in association with epithelial ovarian cancer (EOC) risk.Methods:CNV was quantified in the DNA of approximately 3,500 cases and controls genotyped with the Illumina 610k and HumanOmni2.5M arrays. We performed a genome-wide association study of common (&gt;1%) CNV regions (CNVRs) with EOC and high-grade serous (HGSOC) risk and, using The Cancer Genome Atlas (TCGA), performed in silico analyses of tumor-gene expression.Results:Three CNVRs were associated (P &lt; 0.01) with EOC risk: two large (∼100 kb) regions within the 610k set and one small (&lt;5 kb) region with the higher resolution 2.5M data. Large CNVRs included a duplication at LILRA6 (OR = 2.57; P = 0.001) and a deletion at CYP2A7 (OR = 1.90; P = 0.007) that were strongly associated with HGSOC risk (OR = 3.02; P = 8.98 × 10−5). Somatic CYP2A7 alterations correlated with EGLN2 expression in tumors (P = 2.94 × 10−47). An intronic ERBB4/HER4 deletion was associated with reduced EOC risk (OR = 0.33; P = 9.5 × 10−2), and somatic deletions correlated with ERBB4 downregulation (P = 7.05 × 10−5). Five CNVRs were associated with HGSOC, including two reduced-risk deletions: one at 1p36.33 (OR = 0.28; P = 0.001) that correlated with lower CDKIIA expression in TCGA tumors (P = 2.7 × 10−7), and another at 8p21.2 (OR = 0.52; P = 0.002) that was present somatically where it correlated with lower GNRH1 expression (P = 5.9 × 10−5).Conclusions:Though CNV appears to not contribute largely to EOC susceptibility, a number of low-to-common frequency variants may influence the risk of EOC and tumor-gene expression.Impact:Further research on CNV and EOC susceptibility is warranted, particularly with CNVs estimated from high-density arrays.