Citations

Abstract The presence of regulatory T cells (Treg) in solid tumors is known to play a role in patient survival in ovarian cancer and other malignancies. We assessed inherited genetic variations via 749 tag single-nucleotide polymorphisms (SNP) 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. We analyzed genotype and overall survival in 10,084 women with invasive epithelial ovarian cancer, including 5,248 high-grade serous, 1,452 endometrioid, 795 clear cell, and 661 mucinous carcinoma cases of European descent across 28 studies from the Ovarian Cancer Association Consortium (OCAC). The strongest associations were found for endometrioid carcinoma and IL2RA SNPs rs11256497 [HR, 1.42; 95% confidence interval (CI), 1.22–1.64; P = 5.7 × 10−6], rs791587 (HR, 1.36; 95% CI, 1.17–1.57; P = 6.2 × 10−5), rs2476491 (HR, = 1.40; 95% CI, 1.19–1.64; P = 5.6 × 10−5), and rs10795763 (HR, 1.35; 95% CI, 1.17–1.57; P = 7.9 × 10−5), and for clear cell carcinoma and CTLA4 SNP rs231775 (HR, 0.67; 95% CI, 0.54–0.82; P = 9.3 × 10−5) after adjustment for age, study site, population stratification, stage, grade, and oral contraceptive use. The rs231775 allele associated with improved survival in our study also results in an amino acid change in CTLA4 and previously has been reported to be associated with autoimmune conditions. Thus, we found evidence that SNPs in genes related to Tregs seem to play a role in ovarian cancer survival, particularly in patients with clear cell and endometrioid epithelial ovarian cancer. Cancer Immunol Res; 2(4); 332–40. ©2014 AACR.

Abstract Purpose: Ovarian cancer has a high recurrence and mortality rate. A barrier to improved outcomes includes a lack of accurate models for preclinical testing of novel therapeutics. Experimental Design: Clinically relevant, patient-derived tumorgraft models were generated from sequential patients and the first 168 engrafted models are described. Fresh ovarian, primary peritoneal, and fallopian tube carcinomas were collected at the time of debulking surgery and injected intraperitoneally into severe combined immunodeficient mice. Results: Tumorgrafts demonstrated a 74% engraftment rate with microscopic fidelity of primary tumor characteristics. Low-passage tumorgrafts also showed comparable genomic aberrations with the corresponding primary tumor and exhibit gene set enrichment of multiple ovarian cancer molecular subtypes, similar to patient tumors. Importantly, each of these tumorgraft models is annotated with clinical data and for those that have been tested, response to platinum chemotherapy correlates with the source patient. Conclusions: Presented herein is the largest known living tumor bank of patient-derived, ovarian tumorgraft models that can be applied to the development of personalized cancer treatment. Clin Cancer Res; 20(5); 1288–97. ©2014 AACR.

Abstract A missense single-nucleotide polymorphism (SNP) in the immune modulatory gene IL1A has been associated with ovarian cancer risk (rs17561). Although the exact mechanism through which this SNP alters risk of ovarian cancer is not clearly understood, rs17561 has also been associated with risk of endometriosis, an epidemiologic risk factor for ovarian cancer. Interleukin-1α (IL1A) is both regulated by and able to activate NF-κB, a transcription factor family that induces transcription of many proinflammatory genes and may be an important mediator in carcinogenesis. We therefore tagged SNPs in more than 200 genes in the NF-κB pathway for a total of 2,282 SNPs (including rs17561) for genotype analysis of 15,604 cases of ovarian cancer in patients of European descent, including 6,179 of high-grade serous (HGS), 2,100 endometrioid, 1,591 mucinous, 1,034 clear cell, and 1,016 low-grade serous, including 23,235 control cases spanning 40 studies in the Ovarian Cancer Association Consortium. In this large population, we confirmed the association between rs17561 and clear cell ovarian cancer [OR, 0.84; 95% confidence interval (CI), 0.76–0.93; P = 0.00075], which remained intact even after excluding participants in the prior study (OR, 0.85; 95% CI, 0.75–0.95; P = 0.006). Considering a multiple-testing–corrected significance threshold of P < 2.5 × 10−5, only one other variant, the TNFSF10 SNP rs6785617, was associated significantly with a risk of ovarian cancer (low malignant potential tumors OR, 0.85; 95% CI, 0.79–0.91; P = 0.00002). Our results extend the evidence that borderline tumors may have a distinct genetic etiology. Further investigation of how these SNPs might modify ovarian cancer associations with other inflammation-related risk factors is warranted. Cancer Res; 74(3); 852–61. ©2013 AACR.

Abstract Background: Ovarian cancer is a leading cause of cancer-related death among women. In an effort to understand contributors to disease outcome, we evaluated single-nucleotide polymorphisms (SNP) previously associated with ovarian cancer recurrence or survival, specifically in angiogenesis, inflammation, mitosis, and drug disposition genes. Methods: Twenty-seven SNPs in VHL, HGF, IL18, PRKACB, ABCB1, CYP2C8, ERCC2, and ERCC1 previously associated with ovarian cancer outcome were genotyped in 10,084 invasive cases from 28 studies from the Ovarian Cancer Association Consortium with over 37,000-observed person-years and 4,478 deaths. Cox proportional hazards models were used to examine the association between candidate SNPs and ovarian cancer recurrence or survival with and without adjustment for key covariates. Results: We observed no association between genotype and ovarian cancer recurrence or survival for any of the SNPs examined. Conclusions: These results refute prior associations between these SNPs and ovarian cancer outcome and underscore the importance of maximally powered genetic association studies. Impact: These variants should not be used in prognostic models. Alternate approaches to uncovering inherited prognostic factors, if they exist, are needed. Cancer Epidemiol Biomarkers Prev; 22(5); 987–. ©2013 AACR.

Abstract Rare germline mutations in the breast and ovarian cancer predisposition genes BRCA1 and BRCA2 are present in roughly 5 percent of ovarian cancer patients. Both genes play key roles in DNA damage repair but appear to have distinct, although often complementary, functions. The risks of breast and ovarian cancer have been shown to differ between BRCA1 and BRCA2 carriers, and mutation-specific effects have also been suggested for both groups. Published reports comparing the survival of ovarian cancer patients with and without BRCA1/2 mutations generally show a survival advantage among mutation carriers. This is thought to be related to an improved response of carriers to platinum-based therapies. Since it is not known whether BRCA1 and BRCA2 carriers show similar survival patterns, we have performed a large, multicenter study to investigate the impact of germline BRCA1 and BRCA2 mutations on ovarian cancer survival. 3,531 invasive epithelial ovarian cancer cases (1,178 BRCA1, 367 BRCA2 and 1,986 BRCA-negative) with survival time data from twenty-four studies in the U.S.A, Europe, Israel and Asia were included. In our main analysis, we excluded patients who were known or who were likely to have not received platinum-based therapy. Compared to non-carriers, BRCA1 and BRCA2 carriers were more likely to present with advanced stage (BRCA1; p=2×10−4, BRCA2; p=4×10−6), high grade (BRCA1; p=4×10−9, BRCA2; p=1×10−4), serous disease (BRCA1; p=3×10−6, BRCA2; p=0.003). BRCA1 carriers were younger at diagnosis (p=2×10−9) and BRCA2 slightly older at diagnosis (p=0.002) than non-carriers. BRCA1 and BRCA2 carriers did not differ in terms of tumor stage, grade or histology but did show differences in the age at diagnosis (p=2×10−14). In an unadjusted analysis, neither BRCA1 nor BRCA2 carriers differed from non-carriers in overall survival (BRCA1: HR=1.02, p=0.77, BRCA2: HR=0.89, p=0.36). After adjusting for stage, grade, histology and age at diagnosis, BRCA1 carriers showed a modest, non-significant, survival advantage (HR=0.84, p=0.12) while BRCA2 carriers showed a marked improvement (HR=0.57, p=6×10−4) compared to non-carriers. This survival advantage was also seen when comparing BRCA2 carriers to BRCA1 carriers after adjustment for age at diagnosis (HR=0.69, p=5×10−4). Similar results were obtained when we restricted the analysis to high grade, advanced stage, serous cases. The survival differences we observed between BRCA1 and BRCA2 carriers could be related to differences in tumor biology or chemo-sensitivity. Additional analyses investigating the later will be presented in addition to mutation-specific effects within BRCA1 and BRCA2. In this study, we provide strong evidence for genetic heterogeneity of survival effects in ovarian cancer patients with BRCA mutations. This could be applied to both clinical prediction and to aid our understanding of the complex biology of BRCA mutations. 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 2752. doi:10.1158/1538-7445.AM2011-2752

Abstract Background: Genome-wide association studies (GWAS) identified variants at 19p13.1 and ZNF365 (10q21.2) as risk factors for breast cancer among BRCA1 and BRCA2 mutation carriers, respectively. We explored associations with ovarian cancer and with breast cancer by tumor histopathology for these variants in mutation carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Methods: Genotyping data for 12,599 BRCA1 and 7,132 BRCA2 mutation carriers from 40 studies were combined. Results: We confirmed associations between rs8170 at 19p13.1 and breast cancer risk for BRCA1 mutation carriers [HR, 1.17; 95% confidence interval (CI), 1.07–1.27; P = 7.42 × 10−4] and between rs16917302 at ZNF365 (HR, 0.84; 95% CI, 0.73–0.97; P = 0.017) but not rs311499 at 20q13.3 (HR, 1.11; 95% CI, 0.94–1.31; P = 0.22) and breast cancer risk for BRCA2 mutation carriers. Analyses based on tumor histopathology showed that 19p13 variants were predominantly associated with estrogen receptor (ER)-negative breast cancer for both BRCA1 and BRCA2 mutation carriers, whereas rs16917302 at ZNF365 was mainly associated with ER-positive breast cancer for both BRCA1 and BRCA2 mutation carriers. We also found for the first time that rs67397200 at 19p13.1 was associated with an increased risk of ovarian cancer for BRCA1 (HR, 1.16; 95% CI, 1.05–1.29; P = 3.8 × 10−4) and BRCA2 mutation carriers (HR, 1.30; 95% CI, 1.10–1.52; P = 1.8 × 10−3). Conclusions: 19p13.1 and ZNF365 are susceptibility loci for ovarian cancer and ER subtypes of breast cancer among BRCA1 and BRCA2 mutation carriers. Impact: These findings can lead to an improved understanding of tumor development and may prove useful for breast and ovarian cancer risk prediction for BRCA1 and BRCA2 mutation carriers. Cancer Epidemiol Biomarkers Prev; 21(4); 645–57. ©2012 AACR.

Abstract Background: Invasive ovarian cancer is a significant cause of gynecologic cancer mortality. Methods: We examined whether this mortality was associated with inherited variation in approximately 170 candidate genes/regions [993 single-nucleotide polymorphisms (SNPs)] in a multistage analysis based initially on 312 Mayo Clinic cases (172 deaths). Additional analyses used The Cancer Genome Atlas (TCGA; 127 cases, 62 deaths). For the most compelling gene, we immunostained Mayo Clinic tissue microarrays (TMA, 326 cases) and conducted consortium-based SNP replication analysis (2,560 cases, 1,046 deaths). Results: The strongest initial mortality association was in HGF (hepatocyte growth factor) at rs1800793 (HR = 1.7, 95% CI = 1.3–2.2, P = 2.0 × 10−5) and with overall variation in HGF (gene-level test, P = 3.7 × 10−4). Analysis of TCGA data revealed consistent associations [e.g., rs5745709 (r2 = 0.96 with rs1800793): TCGA HR = 2.4, CI = 1.4–4.1, P = 2.2 × 10−3; Mayo Clinic + TCGA HR = 1.6, CI = 1.3–1.9, P = 7.0 × 10−5] and suggested genotype correlation with reduced HGF mRNA levels (P = 0.01). In Mayo Clinic TMAs, protein levels of HGF, its receptor MET (C-MET), and phospho-MET were not associated with genotype and did not serve as an intermediate phenotype; however, phospho-MET was associated with reduced mortality (P = 0.01) likely due to higher expression in early-stage disease. In eight additional ovarian cancer case series, HGF rs5745709 was not associated with mortality (HR = 1.0, CI = 0.9–1.1, P = 0.87). Conclusions: We conclude that although HGF signaling is critical to migration, invasion, and apoptosis, it is unlikely that HGF genetic variation plays a major role in ovarian cancer mortality. Furthermore, any minor role is not related to genetically-determined expression. Impact: Our study shows the utility of multiple data types and multiple data sets in observational studies. Cancer Epidemiol Biomarkers Prev; 20(8); 1638–48. ©2011 AACR.

Abstract Purpose: Cell-based approaches were used to identify genetic markers predictive of patients' risk for poor response prior to chemotherapy. Experimental Design: We conducted genome-wide association studies (GWAS) to identify single-nucleotide polymorphisms (SNP) associated with cellular sensitivity to carboplatin through their effects on mRNA expression using International HapMap lymphoblastoid cell lines (LCL) and replicated them in additional LCLs. SNPs passing both stages of the cell-based study were tested for association with progression-free survival (PFS) in patients. Phase 1 validation was based on 377 ovarian cancer patients receiving at least four cycles of carboplatin and paclitaxel from the Australian Ovarian Cancer Study (AOCS). Positive associations were then assessed in phase 2 validation analysis of 1,326 patients from the Ovarian Cancer Association Consortium and The Cancer Genome Atlas. Results: In the initial GWAS, 342 SNPs were associated with carboplatin-induced cytotoxicity, of which 18 unique SNPs were retained after assessing their association with gene expression. One SNP (rs1649942) was replicated in an independent LCL set (Bonferroni adjusted P < 0.05). It was found to be significantly associated with decreased PFS in phase 1 AOCS patients (Pper-allele = 2 × 10−2), with a stronger effect in the subset of women with optimally debulked tumors (Pper-allele = 4 × 10−3). rs1649942 was also associated with poorer overall survival in women with optimally debulked tumors (Pper-allele = 9 × 10−3). However, this SNP was not significant in phase 2 validation analysis with patients from numerous cohorts. Conclusion: This study shows the potential of cell-based, genome-wide approaches to identify germline predictors of treatment outcome and highlights the need for extensive validation in patients to assess their clinical effect. Clin Cancer Res; 17(16); 5490–500. ©2011 AACR.

Purpose Identify features on preoperative computed tomography (CT) scans to predict suboptimal primary cytoreduction in patients treated for advanced ovarian cancer in institution A. Reciprocally cross validate the predictors identified with those from two previously published cohorts from institutions B and C. Patients and Methods Preoperative CT scans from patients with stage III/IV epithelial ovarian cancer who underwent primary cytoreduction in institution A between 1999 and 2005 were retrospectively reviewed by radiologists blinded to surgical outcome. Fourteen criteria were assessed. Crossvalidation was performed by applying predictive model A to the patients from cohorts B and C, and reciprocally applying predictive models B and C to cohort A. Results Sixty-five patients from institution A were included. The rate of optimal cytoreduction (≤ 1 cm residual disease) was 78%. Diaphragm disease and large bowel mesentery implants were the only CT predictors of suboptimal cytoreduction on univariate (P < .02) and multivariate analysis (P < .02). In combination (model A), these predictors had a sensitivity of 79%, a specificity of 75%, and an accuracy of 77% for suboptimal cytoreduction. When model A was applied to cohorts B and C, accuracy rates dropped to 34% and 64%, respectively. Reciprocally, models B and C had accuracy rates of 93% and 79% in their original cohorts, which fell to 74% and 48% in cohort A. Conclusion The high accuracy rates of CT predictors of suboptimal cytoreduction in the original cohorts could not be confirmed in the cross validation. Preoperative CT predictors should be used with caution when deciding between surgical cytoreduction and neoadjuvant chemotherapy.