Citations

Abstract Background: Epithelial Ovarian Cancer (EOC) is a lethal gynecologic malignancy. Mitochondria are cellular organelles that regulate energy metabolism and are the primary source of reactive oxygen species (ROS), which damage both the nuclear and mitochondria DNA (mtDNA), contributing to the pathogenesis of EOC. Previously, we identified statistically significant EOC risk associations with 54 single nucleotide polymorphisms (SNPs) from 11 mitochondria-related genes in a study of 1815 EOC cases and 1900 controls. In this replication study we expand our investigation of mitochondrial metabolism genetic variants and associations with EOC risk and overall survival (OS). Methods: In a discovery set of 3761 EOC cases and 2722 controls, we investigated risk associations in 4200 SNPs from 130 mitochondrial metabolism genes. We genotyped 431 of the most significant SNPs from 86 genes in 14,525 EOC cases and 23,447 controls (of European ancestry) from 43 studies in OCAC using an Illumina Infinium iSelect BeadChip. Risk analyses were conducted using unconditional logistic regression under a log-additive model and adjusted for study site and the first five principal components of population substructure. Both invasive cancers combined and the four main histological subtypes were analyzed. Survival analyses were conducted on the same SNPs using Cox hazards models to estimate hazard ratios (HRs) and 95% CIs considering overall survival in 10,084 cases from 28 OCAC studies. We adjusted for multiple tests using False Discovery Rate q<20%. Results: The strongest evidence of an association for risk of invasive cancers combined and the serous subtype was SNP rs3096 in the pyridoxamine 5'-phosphate oxidase (PNPO) gene (OR=1.08, p=2.8x10-6). In clear cell carcinoma, the strongest association was a missense coding SNP rs28379632 (Ile421Met) in the MT-CYB gene (OR=4.0, p=0.003). For endometrioid cancer rs9330440 in the UNQ6494 gene was most significant (OR=0.89, p=0.001) while rs10267797 in the dihydrolipoamide dehydrogenase (DLD) gene was most significant in the mucinous subtype (OR=1.15, p=0.004). The strongest association with overall survival was mitochondrial transcription termination factor 1 (MTERF) rs2540571 (HR=0.92, p= 0.00011). Conclusion: These results suggest that mitochondrial metabolism gene variants appear to be associated with EOC risk and survival. Citation Format: Ganna Chornokur, Hui-Yi Lin, Alvaro Monteiro, Joellen Schildkraut, Ellen L. Goode, Paul DP Pharoah, Simon A. Gayther, Susan Ramus, Thomas A. Sellers, Catherine M. Phelan. Mitochondrial metabolism gene variants are associated with risk and survival in epithelial ovarian cancer (EOC). [abstract]. In: Proceedings of the AACR Special Conference: Metabolism and Cancer; Jun 7-10, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(1_Suppl):Abstract nr A50.

Abstract Background: Epithelial Ovarian Cancer (EOC) is a lethal gynecologic malignancy and the fifth cause of cancer mortality in women in the US. Normal ovarian physiology is intricately connected to tightly regulated small GTP binding proteins of the Ras superfamily (Ras, Rac, Rho, Rab, Arf, and Ran) which regulate key cellular processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. These proteins function in a highly coordinated manner through signaling cascades and feedback loops within and among the small GTPase subfamilies. We hypothesized that single nucleotide polymorphisms (SNPs) in small GTPase genes are associated with epithelial ovarian cancer (EOC) risk and aberrant expression of these genes correlates with tumor characteristics including overall survival (OS). Methods: In a discovery set of 7931 EOC cases and 9206 controls we investigated 9,356 SNPs from 112 genes, 657 of which showed associations up to the significance level of p<0.05. We genotyped 407 of the most significant SNPs from 112 genes in a combined dataset (discovery and replication) which consisted of 18,736 EOC cases and 23,448 controls (of European ancestry) from 43 studies in the Ovarian Cancer Association Consortium (OCAC), using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS). Odds ratios and 95% confidence intervals were calculated using unconditional logistic regression under log-additive models. A False Discovery Rate (FDR) q<0.2 was applied. Pearson's correlation tests were performed on the expression of genes with tumor characteristics and OS in 561 ovarian tumors: serous (n=464); endometrioid (n=52); clear cell carcinoma (n=28) and mucinous (n=17) subtypes. Results: The most significantly associated SNP associations with EOC were: AKAP6 rs1955513, (OR=0.9, p=3.3x10-4) in all invasive; ARGHEF10L rs10788679, (OR=1.05, p=2.6x10-4) in serous; RAB31 rs1166373, (OR=1.25, p=4.0x10-3) in endometrioid; KRAS rs4963872, (OR=1.35, P=4.5x10-4) in mucinous EOC and TNIK rs6780532, (OR=0.88, p=7.7x10-3) in clear cell carcinoma. Increased expression of AKAP6 and TNIK was marginally correlated with advanced EOC stage (p<0.05) while high KRAS expression was correlated with OS (HR=1.18, p=0.038). Conclusions: Genetic variation in the small GTPase genes appears to be associated with ovarian cancer risk and aberrant expression of these genes correlates with tumor characteristics and OS. Citation Format: Hui-Yi Lin, Yin Xiong, Jonathan Tyrer, Douglas C. Marchion, Alvaro NA Monteiro, Andrew Berchuck, Joellen M. Schildkraut, Ellen L. Goode, Susan J. Ramus, Simon A. Gayther, Paul DP Pharoah, Steven A. Narod, Thomas A. Sellers, Catherine M. Phelan. Investigation of small GTPase genes in epithelial ovarian cancer. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: Exploiting Vulnerabilities; Oct 17-20, 2015; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(2 Suppl):Abstract nr B27.

Background BRCA1 interacting protein C-terminal helicase 1 (BRIP1) is one of the Fanconi Anaemia Complementation (FANC) group family of DNA repair proteins. Biallelic mutations in BRIP1 are responsible for FANC group J, and previous studies have also suggested that rare protein truncating variants in BRIP1 are associated with an increased risk of breast cancer. These studies have led to inclusion of BRIP1 on targeted sequencing panels for breast cancer risk prediction. Methods We evaluated a truncating variant, p.Arg798Ter (rs137852986), and 10 missense variants of BRIP1, in 48 144 cases and 43 607 controls of European origin, drawn from 41 studies participating in the Breast Cancer Association Consortium (BCAC). Additionally, we sequenced the coding regions of BRIP1 in 13 213 cases and 5242 controls from the UK, 1313 cases and 1123 controls from three population-based studies as part of the Breast Cancer Family Registry, and 1853 familial cases and 2001 controls from Australia. Results The rare truncating allele of rs137852986 was observed in 23 cases and 18 controls in Europeans in BCAC (OR 1.09, 95% CI 0.58 to 2.03, p=0.79). Truncating variants were found in the sequencing studies in 34 cases (0.21%) and 19 controls (0.23%) (combined OR 0.90, 95% CI 0.48 to 1.70, p=0.75). Conclusions These results suggest that truncating variants in BRIP1, and in particular p.Arg798Ter, are not associated with a substantial increase in breast cancer risk. Such observations have important implications for the reporting of results from breast cancer screening panels.

Abstract Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103–14. ©2016 AACR.

Previous genome‐wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. A fine‐mapping study across 2.06 Mb (chr8:127,561,724–129,624,067, hg19) in 55,540 breast cancer cases and 51,168 controls within the Breast Cancer Association Consortium was conducted. Three additional independent association signals in women of European ancestry, represented by rs35961416 (OR = 0.95, 95% CI = 0.93–0.97, conditional p = 5.8 × 10−6), rs7815245 (OR = 0.94, 95% CI = 0.91–0.96, conditional p = 1.1 × 10−6) and rs2033101 (OR = 1.05, 95% CI = 1.02–1.07, conditional p = 1.1 × 10−4) were found. Integrative analysis using functional genomic data from the Roadmap Epigenomics, the Encyclopedia of DNA Elements project, the Cancer Genome Atlas and other public resources implied that SNPs rs7815245 in Signal 3, and rs1121948 in Signal 5 (in linkage disequilibrium with rs11780156, r2 = 0.77), were putatively functional variants for two of the five independent association signals. The results highlighted multiple 8q24 variants associated with breast cancer susceptibility in women of European ancestry.

Abstract Background: Many epithelial ovarian cancer (EOC) risk factors relate to hormone exposure and elevated estrogen levels are associated with obesity in postmenopausal women. Therefore, we hypothesized that gene–environment interactions related to hormone-related risk factors could differ between obese and non-obese women. Methods: We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy, and estrogen use) and assessed whether these interactions differed between obese and non-obese women. Interactions were assessed using logistic regression models and data from 14 case–control studies (6,247 cases; 10,379 controls). Histotype-specific analyses were also completed. Results: SNPs in the following candidate genes showed notable interaction: IGF1R (rs41497346, estrogen plus progesterone hormone therapy, histology = all, P = 4.9 × 10−6) and ESR1 (rs12661437, endometriosis, histology = all, P = 1.5 × 10−5). The most notable obesity–gene–hormone risk factor interaction was within INSR (rs113759408, parity, histology = endometrioid, P = 8.8 × 10−6). Conclusions: We have demonstrated the feasibility of assessing multifactor interactions in large genetic epidemiology studies. Follow-up studies are necessary to assess the robustness of our findings for ESR1, CYP11A1, IGF1R, CYP11B1, INSR, and IGFBP2. Future work is needed to develop powerful statistical methods able to detect these complex interactions. Impact: Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC susceptibility. Cancer Epidemiol Biomarkers Prev; 25(5); 780–90. ©2016 AACR.

AbstractAutomated methods are needed to facilitate high‐throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large‐scale studies. To address this need, we developed an automated protocol for Ki67 scoring and evaluated its performance in studies from the Breast Cancer Association Consortium. We utilized 166 TMAs containing 16,953 tumour cores representing 9,059 breast cancer cases, from 13 studies, with information on other clinical and pathological characteristics. TMAs were stained for Ki67 using standard immunohistochemical procedures, and scanned and digitized using the Ariol system. An automated algorithm was developed for the scoring of Ki67, and scores were compared to computer assisted visual (CAV) scores in a subset of 15 TMAs in a training set. We also assessed the correlation between automated Ki67 scores and other clinical and pathological characteristics. Overall, we observed good discriminatory accuracy (AUC = 85%) and good agreement (kappa = 0.64) between the automated and CAV scoring methods in the training set. The performance of the automated method varied by TMA (kappa range= 0.37–0.87) and study (kappa range = 0.39–0.69). The automated method performed better in satisfactory cores (kappa = 0.68) than suboptimal (kappa = 0.51) cores (p‐value for comparison = 0.005); and among cores with higher total nuclei counted by the machine (4,000–4,500 cells: kappa = 0.78) than those with lower counts (50–500 cells: kappa = 0.41; p‐value = 0.010). Among the 9,059 cases in this study, the correlations between automated Ki67 and clinical and pathological characteristics were found to be in the expected directions. Our findings indicate that automated scoring of Ki67 can be an efficient method to obtain good quality data across large numbers of TMAs from multicentre studies. However, robust algorithm development and rigorous pre‐ and post‐analytical quality control procedures are necessary in order to ensure satisfactory performance.

Abstract Background: While numerous susceptibility loci for epithelial ovarian cancer (EOC) have been identified, few associations have been reported with overall survival. In the absence of common prognostic genetic markers, we hypothesize that rare coding variants may be associated with overall EOC survival and assessed their contribution in two exome-based genotyping projects of the Ovarian Cancer Association Consortium (OCAC). Methods: The primary patient set (Set 1) included 14 independent EOC studies (4,293 patients) and 227,892 variants, and a secondary patient set (Set 2) included six additional EOC studies (1,744 patients) and 114,620 variants. Because power to detect rare variants individually is reduced, gene-level tests were conducted. Sets were analyzed separately at individual variants and by gene, and then combined with meta-analyses (73,203 variants and 13,163 genes overlapped). Results: No individual variant reached genome-wide statistical significance. A SNP previously implicated to be associated with EOC risk and, to a lesser extent, survival, rs8170, showed the strongest evidence of association with survival and similar effect size estimates across sets (Pmeta = 1.1E−6, HRSet1 = 1.17, HRSet2 = 1.14). Rare variants in ATG2B, an autophagy gene important for apoptosis, were significantly associated with survival after multiple testing correction (Pmeta = 1.1E−6; Pcorrected = 0.01). Conclusions: Common variant rs8170 and rare variants in ATG2B may be associated with EOC overall survival, although further study is needed. Impact: This study represents the first exome-wide association study of EOC survival to include rare variant analyses, and suggests that complementary single variant and gene-level analyses in large studies are needed to identify rare variants that warrant follow-up study. Cancer Epidemiol Biomarkers Prev; 25(3); 446–54. ©2016 AACR.