Survival in epithelial ovarian cancer (EOC) is influenced by the host immune response, yet the key genetic determinants of inflammation and immunity that impact prognosis are not known. The nuclear factor-kappa B (NF-κB) transcription factor family plays an important role in many immune and inflammatory responses, including the response to cancer. We studied common inherited variation in 210 genes in the NF-κB family in 10,084 patients with invasive EOC (5,248 high grade serous, 1,452 endometrioid, 795 clear cell, and 661 mucinous) from the Ovarian Cancer Association Consortium. Associations between genotype and overall survival were assessed using Cox regression for all patients and by major histology, adjusting for known prognostic factors and correcting for multiple testing (threshold for statistical significance—p < 2.5×10−5). Results were statistically significant when assessed for patients of a single histology. Key associations were with CARD11 (caspase recruitment domain family, member 11) rs41324349 in patients with mucinous EOC (HR 1.82, 95% CI 1.41-2.35, p=4.13×10−6) and TNFRSF13B (tumor necrosis factor receptor superfamily, member 13B) rs7501462 in patients with endometrioid EOC (HR 0.68, 95% CI 0.56-0.82, p=2.33×10−5). Other associations of note included TRAF2 (TNF receptor-associated factor 2) rs17250239 in patients with high-grade serous EOC (HR 0.84, 95% CI 0.77-0.92, p=6.49×10−5) and PLCG1 (phospholipase C, gamma 1) rs11696662 in patients with clear cell EOC (HR 0.43, 95% CI 0.26-0.73, p=4.56×10−4). These associations highlight the potential importance of genes associated with host inflammation and immunity in modulating clinical outcomes in distinct EOC histologies.
single nucleotide polymorphism; recurrence; survival; ovarian neoplasms
Survival in epithelial ovarian cancer (EOC) is influenced by the host immune response, yet the key genetic determinants of inflammation and immunity that impact prognosis are not known. The nuclear factor-kappa B (NF-κB) transcription factor family plays an important role in many immune and inflammatory responses, including the response to cancer. We studied common inherited variation in 210 genes in the NF-κB family in 10,084 patients with invasive EOC (5,248 high grade serous, 1,452 endometrioid, 795 clear cell, and 661 mucinous) from the Ovarian Cancer Association Consortium. Associations between genotype and overall survival were assessed using Cox regression for all patients and by major histology, adjusting for known prognostic factors and correcting for multiple testing (threshold for statistical significance—p < 2.5×10−5). Results were statistically significant when assessed for patients of a single histology. Key associations were with CARD11 (caspase recruitment domain family, member 11) rs41324349 in patients with mucinous EOC (HR 1.82, 95% CI 1.41–2.35, p=4.13×10−6) and TNFRSF13B (tumor necrosis factor receptor superfamily, member 13B) rs7501462 in patients with endometrioid EOC (HR 0.68, 95% CI 0.56–0.82, p=2.33×10−5). Other associations of note included TRAF2 (TNF receptor-associated factor 2) rs17250239 in patients with high-grade serous EOC (HR 0.84, 95% CI 0.77–0.92, p=6.49×10−5) and PLCG1 (phospholipase C, gamma 1) rs11696662 in patients with clear cell EOC (HR 0.43, 95% CI 0.26–0.73, p=4.56×10−4). These associations highlight the potential importance of genes associated with host inflammation and immunity in modulating clinical outcomes in distinct EOC histologies.
single nucleotide polymorphism; recurrence; survival; ovarian neoplasms
The presence of regulatory T cells (Tregs) 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 SNPs 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% 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 appear to play a role in ovarian cancer survival, particularly in patients with clear cell and endometrioid EOC.
clear cell; endometrioid; gynecologic neoplasms; single nucleotide polymorphism
The presence of regulatory T cells (Tregs) 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 SNPs 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% 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: 1.191.64; 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 appear to play a role in ovarian cancer survival, particularly in patients with clear cell and endometrioid EOC.
clear cell; endometrioid; gynecologic neoplasms; single nucleotide polymorphism
Ovarian carcinoma is composed of five major histological types which associate with outcome and predict therapeutic response. Our aim was to evaluate histological type assessments across centres participating in the Ovarian Tumor Tissue Analysis (OTTA) consortium using an immunohistochemical (IHC) prediction model.
Tissue microarrays (TMAs) and clinical data were available for 524 pathologically confirmed ovarian carcinomas. Centralized IHC was performed for ARID1A, CDKN2A, DKK1, HNF1B, MDM2, PGR, TP53, TFF3, VIM, and WT1, and three histological type assessments were compared: the original pathologic type, an IHC-based calculated type (termed TB_COSPv2), and a WT1-assisted TMA core review.
The concordance between TB_COSPv2 type and original type was 73%. Applying WT1-assisted core review, the remaining 27% discordant cases subdivided into unclassifiable (6%), TB_COSPv2 error (6%), and original type error (15%). The largest discordant subgroup was classified as endometrioid carcinoma (EC) by original type and as high-grade serous carcinoma (HGSC) by TB_COSPv2. When TB_COSPv2 classification was used, the difference in overall survival of EC compared to HGSC became significant (RR 0.60, 95% CI 0.37–0.93, p=0.021), consistent with previous reports. In addition, 71 cases with unclear original type could be histologically classified by TB_COSPv2.
Research cohorts, particularly those across different centres within consortia, show significant variability in original histological type diagnosis. Our IHC-based reclassification produced more homogeneous types with respect to outcome than original type.
Biomarker-based classification of ovarian carcinomas is feasible, improves comparability of results across research studies, and can reclassify cases which lack reliable original pathology.
ovarian cancer; type; biomarker; immunohistochemistry; typing
The majority of previous studies have observed an increased risk of mucinous ovarian tumors associated with cigarette smoking, but the association with other histological types is unclear. In a large pooled analysis, we examined the risk of epithelial ovarian cancer associated with multiple measures of cigarette smoking with a focus on characterizing risks according to tumor behavior and histology.
We used data from 21 case–control studies of ovarian cancer (19,066 controls, 11,972 invasive and 2,752 borderline cases). Study-specific odds ratios (OR) and 95 % confidence intervals (CI) were obtained from logistic regression models and combined into a pooled odds ratio using a random effects model.
Current cigarette smoking increased the risk of invasive mucinous (OR = 1.31; 95 % CI: 1.03–1.65) and borderline mucinous ovarian tumors (OR = 1.83; 95 % CI: 1.39–2.41), while former smoking increased the risk of borderline serous ovarian tumors (OR = 1.30; 95 % CI: 1.12–1.50). For these histological types, consistent dose– response associations were observed. No convincing associations between smoking and risk of invasive serous and endometrioid ovarian cancer were observed, while our results provided some evidence of a decreased risk of invasive clear cell ovarian cancer.
Our results revealed marked differences in the risk profiles of histological types of ovarian cancer with regard to cigarette smoking, although the magnitude of the observed associations was modest. Our findings, which may reflect different etiologies of the histological types, add to the fact that ovarian cancer is a heterogeneous disease.
Case–control studies; Histological type; Ovarian neoplasms; Smoking
Ovarian cancer is a lethal disease comprised of distinct histopathological types. There are few established biomarkers of ovarian cancer prognosis, in part because subtype-specific associations may have been obscured in studies combining all subtypes. We examined whether progesterone receptor (PR) and estrogen receptor (ER) protein expression were associated with subtype-specific survival in the international Ovarian Tumor Tissue Analysis (OTTA) consortium.
PR and ER were assessed by central immunohistochemical analysis of tissue microarrays for 2933 women with invasive epithelial ovarian cancer from 12 study sites. Negative, weak, and strong expression were defined as positive staining in <1%, 1–50%, and ≥50% of tumor cell nuclei, respectively. Hazard ratios (HRs) for ovarian cancer death were estimated using Cox regression stratified by site and adjusted for age, stage, and grade.
PR expression was associated with improved survival for endometrioid (EC; p<0·0001) and high-grade serous carcinoma (HGSC; p=0·0006), and ER expression was associated with improved EC survival (p<0·0001); no significant associations were found for mucinous, clear cell, or low-grade serous carcinoma. EC patients with hormone receptor (PR and/or ER) positive (weak or strong) versus negative tumors had significantly reduced risk of dying from their disease, independent of clinical factors (HR, 0·33; 95% CI, 0·21–0·51; p<0·0001). HGSC patients with strong versus weak or negative tumor PR expression had significantly reduced risk of dying from their disease, independent of clinical factors (HR, 0·71; 95% CI, 0·55–0·91; p=0·0061).
PR and ER are prognostic biomarkers for endometrioid and high-grade serous ovarian cancers. Clinical trials, stratified by subtype and biomarker status, are needed to determine whether hormone receptor status predicts response to endocrine therapy, and can guide personalized treatment for ovarian cancer.
Carraressi Foundation, US National Institutes of Health, National Health and Medical Research Council of Australia, UK National Institute for Health Research, and others.
There are several well-established environmental risk factors for ovarian cancer, and recent genome-wide association studies have also identified six variants that influence disease risk. However, the interplay between such risk factors and susceptibility loci has not been studied.
Data from 14 ovarian cancer case-control studies were pooled, and stratified analyses by each environmental risk factor with tests for heterogeneity were conducted to determine the presence of interactions for all histological subtypes. A genetic “risk score” was created to consider the effects of all six variants simultaneously. A multivariate model was fit to examine the association between all environmental risk factors and genetic risk score on ovarian cancer risk.
Among 7,374 controls and 5,566 cases, there was no statistical evidence of interaction between the six SNPs or genetic risk score and the environmental risk factors on ovarian cancer risk. In a main effects model, women in the highest genetic risk score quartile had a 65% increased risk of ovarian cancer compared to women in the lowest (95% CI 1.48-1.84). Analyses by histological subtype yielded risk differences across subtype for endometriosis (phet<0.001), parity (phet<0.01), and tubal ligation (phet=0.041).
The lack of interactions suggests that a multiplicative model is the best fit for these data. Under such a model, we provide a robust estimate of each risk factor's effect, which sets the stage for absolute risk prediction modeling that considers both environmental and genetic risk factors. Further research into the observed differences in risk across histological subtype is warranted.
Gene-environment interactions; ovarian cancer; epidemiology; histological subtype; pooled analysis
Endometriosis is characterized by the presence of functional endometrial tissue outside of the uterine cavity. It affects 1 in 10 women of reproductive age. This chronic condition commonly leads to consequences such as pelvic pain, dysmenorrhea, infertility and an elevated risk of epithelial ovarian cancer. Despite the prevalence of endometriosis and its impact on women’s lives, there are relatively few in vitro and in vivo models available for studying the complex disease biology, pathophysiology, and for use in the preclinical development of novel therapies. The goal of this study was to develop a novel three-dimensional (3D) cell culture model of ovarian endometriosis and to test whether it is more reflective of endometriosis biology than traditional two dimensional (2D) monolayer cultures.
A novel ovarian endometriosis epithelial cell line (EEC16) was isolated from a 34-year old female with severe endometriosis. After characterization of cells using in vitro assays, western blotting and RNA-sequencing, this cell line and a second, already well characterized endometriosis cell line, EEC12Z, were established as in vitro 3D spheroid models. We compared biological features of 3D spheroids to 2D cultures and human endometriosis lesions using immunohistochemistry and real-time semi-quantitative PCR.
In comparison to normal ovarian epithelial cells, EEC16 displayed features of neoplastic transformation in in vitro assays. When cultured in 3D, EEC16 and EEC12Z showed differential expression of endometriosis-associated genes compared to 2D monolayer cultures, and more closely mimicked the molecular and histological features of human endometriosis lesions.
To our knowledge, this represents the first report of an in vitro spheroid model of endometriosis. 3D endometriosis models represent valuable experimental tools for studying EEC biology and the development of novel therapeutic approaches.
Ovary; Endometriosis; Cell culture; Three-dimensional in vitro modeling; Real-time semi-quantitative PCR; RNA sequencing
Although single-locus approaches have been widely applied to identify disease-associated single-nucleotide polymorphisms (SNPs), complex diseases are thought to be the product of multiple interactions between loci. This has led to the recent development of statistical methods for detecting statistical interactions between two loci. Canonical correlation analysis (CCA) has previously been proposed to detect gene–gene coassociation. However, this approach is limited to detecting linear relations and can only be applied when the number of observations exceeds the number of SNPs in a gene. This limitation is particularly important for next-generation sequencing, which could yield a large number of novel variants on a limited number of subjects. To overcome these limitations, we propose an approach to detect gene–gene interactions on the basis of a kernelized version of CCA (KCCA). Our simulation studies showed that KCCA controls the Type-I error, and is more powerful than leading gene-based approaches under a disease model with negligible marginal effects. To demonstrate the utility of our approach, we also applied KCCA to assess interactions between 200 genes in the NF-κB pathway in relation to ovarian cancer risk in 3869 cases and 3276 controls. We identified 13 significant gene pairs relevant to ovarian cancer risk (local false discovery rate <0.05). Finally, we discuss the advantages of KCCA in gene–gene interaction analysis and its future role in genetic association studies.
association studies; canonical correlation; gene–gene interaction; kernel methods
Whilst previous studies have reported that higher body-mass index (BMI)
increases a woman’s risk of developing ovarian cancer, associations for
the different histological subtypes have not been well defined. As the
prevalence of obesity has increased dramatically, and classification of ovarian
histology has improved in the last decade, we sought to examine the association
in a pooled analysis of recent studies participating in the Ovarian Cancer
Association Consortium. We evaluated the association between BMI (recent,
maximum, and in young adulthood) and ovarian cancer risk using original data
from 15 case-control studies (13,548 cases, 17,913 controls). We combined
study-specific adjusted odds ratios (ORs) using a random–effects model.
We further examined the associations by histological subtype, menopausal status
and post-menopausal hormone use. High BMI (all time-points) was associated with
increased risk. This was most pronounced for borderline serous (recent BMI:
pooled OR=1.24 per 5kg/m2; 95%CI 1.18–1.30),
invasive endometrioid (1.17; 1.11–1.23) and invasive mucinous (1.19;
1.06–1.32) tumours. There was no association with serous invasive cancer
overall (0.98; 0.94–1.02), but increased risks for low grade serous
invasive tumours (1.13, 1.03–1.25) and in pre-menopausal women (1.11;
1.04–1.18). Among post–menopausal women, the associations did
not differ between HRT users and non–users. Whilst obesity appears to
increase risk of the less common histological subtypes of ovarian cancer, it
does not increase risk of high grade invasive serous cancers, and reducing BMI
is therefore unlikely to prevent the majority of ovarian cancer deaths. Other
modifiable factors must be identified to control this disease.
ovarian cancer; obesity; body mass index
HNF1B is overexpressed in clear cell epithelial ovarian cancer, and we observed epigenetic silencing in serous epithelial ovarian cancer, leading us to hypothesize that variation in this gene differentially associates with epithelial ovarian cancer risk according to histological subtype. Here we comprehensively map variation in HNF1B with respect to epithelial ovarian cancer risk and analyse DNA methylation and expression profiles across histological subtypes. Different single-nucleotide polymorphisms associate with invasive serous (rs7405776 odds ratio (OR) = 1.13, P = 3.1 × 10−10) and clear cell (rs11651755 OR = 0.77, P = 1.6 × 10−8) epithelial ovarian cancer. Risk alleles for the serous subtype associate with higher HNF1B-promoter methylation in these tumours. Unmethylated, expressed HNF1B, primarily present in clear cell tumours, coincides with a CpG island methylator phenotype affecting numerous other promoters throughout the genome. Different variants in HNF1B associate with risk of serous and clear cell epithelial ovarian cancer; DNA methylation and expression patterns are also notably distinct between these subtypes. These findings underscore distinct mechanisms driving different epithelial ovarian cancer histological subtypes.
Previous studies have examined the association between ABO blood group and ovarian cancer risk, with inconclusive results.
In 8 studies participating in the Ovarian Cancer Association Consortium (OCAC), we determined ABO blood groups and diplotypes by genotyping 3 SNPs in the ABO locus. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated in each study using logistic regression; individual study results were combined using random effects meta-analysis.
Compared to blood group O, the A blood group was associated with a modestly increased ovarian cancer risk: (OR: 1.09; 95% CI: 1.01–1.18; p=0.03). In diplotype analysis, the AO, but not the AA diplotype was associated with increased risk (AO: OR: 1.11; 95% CI: 1.01–1.22; p=0.03; AA: OR: 1.03; 95% CI: 0.87–1.21; p=0.76). Neither AB nor the B blood groups were associated with risk. Results were similar across ovarian cancer histologic subtypes.
Consistent with most previous reports, the A blood type was associated modestly with increased ovarian cancer risk in this large analysis of multiple studies of ovarian cancer. Future studies investigating potential biologic mechanisms are warranted.
ovarian cancer; ABO blood group; Ovarian Cancer Association Consortium (OCAC); genetic epidemiology
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 (SNPs) previously associated with ovarian cancer recurrence or survival, specifically in angiogenesis, inflammation, mitosis, and drug disposition genes.
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.
We observed no association between genotype and ovarian cancer recurrence or survival for any of the SNPs examined.
These results refute prior associations between these SNPs and ovarian cancer outcome and underscore the importance of maximally powered genetic association studies.
These variants should not be used in prognostic models. Alternate approaches to uncovering inherited prognostic factors, if they exist, are needed.
Genome wide association studies (GWAS) have identified four susceptibility loci for epithelial ovarian cancer (EOC) with another two loci being close to genome-wide significance. We pooled data from a GWAS conducted in North America with another GWAS from the United Kingdom. We selected the top 24,551 SNPs for inclusion on the iCOGS custom genotyping array. Follow-up genotyping was carried out in 18,174 cases and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. We validated the two loci at 3q25 and 17q21 previously near genome-wide significance and identified three novel loci associated with risk; two loci associated with all EOC subtypes, at 8q21 (rs11782652, P=5.5×10-9) and 10p12 (rs1243180; P=1.8×10-8), and another locus specific to the serous subtype at 17q12 (rs757210; P=8.1×10-10). An integrated molecular analysis of genes and regulatory regions at these loci provided evidence for functional mechanisms underlying susceptibility that implicates CHMP4C in the pathogenesis of ovarian cancer.
Recent genome-wide association studies (GWAS) have identified four low-penetrance ovarian cancer susceptibility loci. We hypothesized that further moderate or low penetrance variants exist among the subset of SNPs not well tagged by the genotyping arrays used in the previous studies which would account for some of the remaining risk. We therefore conducted a time- and cost-effective stage 1 GWAS on 342 invasive serous cases and 643 controls genotyped on pooled DNA using the high density Illumina 1M-Duo array. We followed up 20 of the most significantly associated SNPs, which are not well tagged by the lower density arrays used by the published GWAS, and genotyping them on individual DNA. Most of the top 20 SNPs were clearly validated by individually genotyping the samples used in the pools. However, none of the 20 SNPs replicated when tested for association in a much larger stage 2 set of 4,651 cases and 6,966 controls from the Ovarian Cancer Association Consortium. Given that most of the top 20 SNPs from pooling were validated in the same samples by individual genotyping, the lack of replication is likely to be due to the relatively small sample size in our stage 1 GWAS rather than due to problems with the pooling approach. We conclude that there are unlikely to be any moderate or large effects on ovarian cancer risk untagged by the less dense arrays. However our study lacked power to make clear statements on the existence of hitherto untagged small effect variants.
Fallopian tube secretory epithelial cells (FTSECs) have been implicated as a cell-of-origin for high-grade serous epithelial ovarian cancer. However, there are relatively few in vitro models of this tissue type available for use in studies of FTSEC biology and malignant transformation. In vitro three-dimensional (3D) cell culture models aim to recreate the architecture and geometry of tissues in vivo and restore the complex network of cell-cell/cell-matrix interactions that occur throughout the surface of the cell membrane.
We have established and characterized 3D spheroid culture models of primary FTSECs. FTSEC spheroids contain central cores of hyaline matrix surrounded by mono- or multi-layer epithelial sheets. We found that 3D culturing alters the molecular characteristics of FTSECs compared to 2D cultures of the same cells. Gene expression profiling identified more than a thousand differentially expressed genes between 3D and 2D cultures of the same FTSEC lines. Pathways significantly under-represented in 3D FTSEC cultures were associated with cell cycle progression and DNA replication. This was also reflected in the reduced proliferative indices observed in 3D spheroids stained for the proliferation marker MIB1. Comparisons with gene expression profiles of fresh fallopian tube tissues revealed that 2D FTSEC cultures clustered with follicular phase tubal epithelium, whereas 3D FTSEC cultures clustered with luteal phase samples.
This 3D model of fallopian tube secretory epithelial cells will advance our ability to study the underlying biology and etiology of fallopian tube tissues and the pathogenesis of high-grade serous epithelial ovarian cancer.
Fallopian tube secretory epithelial cells; Gene expression microarray; Three-dimensional in vitro models; Tissue microenvironment; Ovarian cancer
Approximately 10 percent of women with invasive epithelial ovarian cancer (EOC) carry deleterious germline mutations in BRCA1 or BRCA2. A recent report suggested that BRCA2 related EOC was associated with an improved prognosis, but the effect of BRCA1 remains unclear.
To characterize the survival of BRCA carriers with EOC compared to non-carriers and to determine whether BRCA1 and BRCA2 carriers show similar survival patterns.
Design, Setting, and Participants
We pooled data from 26 studies on the survival of women with ovarian cancer. This included data on 1,213 EOC cases with pathogenic germline mutations in BRCA1 (909) or BRCA2 (304) and 2,666 non-carriers recruited and followed for variable times between 1987 and 2010; the median year of diagnosis was 1998.
Main Outcome Measures
Five year overall mortality.
The five-year overall survival was 36 percent (95% CI: 34–38) for non-carriers, 44 percent (95% CI: 40–48) for BRCA1 carriers and 52 percent (95% CI: 46–58) for BRCA2 carriers. After adjusting for study and year of diagnosis, BRCA1 and BRCA2 carriers showed a more favorable survival than non-carriers (BRCA1, HR=0.78; 95% CI=0.68–0.89, P=2×10−4; BRCA2, HR = 0.61; 95% CI=0.50–0.76, P=6×10−6). These survival differences remained after additional adjustment for stage, grade, histology and age at diagnosis (BRCA1, HR=0.73, 95% CI=0.64–0.84, P=2×10−5; BRCA2, HR = 0.49, 95% CI=0.39–0.61, P=3×10−10).
Among patients with invasive epithelial ovarian cancer, having a germline mutation in BRCA1 or BRCA2 was associated with improved 5-year overall survival.
Epithelial ovarian cancer (EOC) has a heritable component that remains to be fully characterized. Most identified common susceptibility variants lie in non-protein-coding sequences. We hypothesized that variants in the 3′ untranslated region at putative microRNA (miRNA) binding sites represent functional targets that influence EOC susceptibility. Here, we evaluate the association between 767 miRNA binding site single nucleotide polymorphisms (miRSNPs) and EOC risk in 18,174 EOC cases and 26,134 controls from 43 studies genotyped through the Collaborative Oncological Gene-environment Study. We identify several miRSNPs associated with invasive serous EOC risk (OR=1.12, P=10−8) mapping to an inversion polymorphism at 17q21.31. Additional genotyping of non-miRSNPs at 17q21.31 reveals stronger signals outside the inversion (P=10−10). Variation at 17q21.31 associates with neurological diseases, and our collaboration is the first to report an association with EOC susceptibility. An integrated molecular analysis in this region provides evidence for ARHGAP27 and PLEKHM1 as candidate EOC susceptibility genes.
Mammographic density adjusted for age and body mass index (BMI) is a heritable marker of breast cancer susceptibility. Little is known about the biological mechanisms underlying the association between mammographic density and breast cancer risk. We examined whether common low-penetrance breast cancer susceptibility variants contribute to inter-individual differences in mammographic density measures.
We established an international consortium (DENSNP) of 19 studies from 10 countries, comprising 16,895 Caucasian women, to conduct a pooled cross-sectional analysis of common breast cancer susceptibility variants in 14 independent loci and mammographic density measures. Dense and non-dense areas, and percent density, were measured using interactive-thresholding techniques. Mixed linear models were used to assess the association between genetic variants and the square roots of mammographic density measures adjusted for study, age, case status, body mass index (BMI) and menopausal status.
Consistent with their breast cancer associations, the C-allele of rs3817198 in LSP1 was positively associated with both adjusted dense area (p=0.00005) and adjusted percent density (p=0.001) whereas the A-allele of rs10483813 in RAD51L1 was inversely associated with adjusted percent density (p=0.003), but not with adjusted dense area (p=0.07).
We identified two common breast cancer susceptibility variants associated with mammographic measures of radio-dense tissue in the breast gland.
We examined the association of 14 established breast cancer susceptibility loci with mammographic density phenotypes within a large genetic consortium and identified two breast cancer susceptibility variants, LSP1-rs3817198 and RAD51L1-rs10483813, associated with mammographic measures and in the same direction as the breast cancer association.
breast density; breast cancer; genetics; biomarkers; mammography
Although ovarian cancer is the most lethal of gynecologic malignancies, wide variation in outcome following conventional therapy continues to exist. The presence of tumor-infiltrating regulatory T cells (Tregs) has a role in outcome of this disease, and a growing body of data supports the existence of inherited prognostic factors. However, the role of inherited variants in genes encoding Treg-related immune molecules has not been fully explored. We analyzed expression quantitative trait loci (eQTL) and sequence-based tagging single nucleotide polymorphisms (tagSNPs) for 54 genes associated with Tregs in 3,662 invasive ovarian cancer cases. With adjustment for known prognostic factors, suggestive results were observed among rarer histological subtypes; poorer survival was associated with minor alleles at SNPs in RGS1 (clear cell, rs10921202, p = 2.7×10−5), LRRC32 and TNFRSF18/TNFRSF4 (mucinous, rs3781699, p = 4.5×10−4, and rs3753348, p = 9.0×10−4, respectively), and CD80 (endometrioid, rs13071247, p = 8.0×10−4). Fo0r the latter, correlative data support a CD80 rs13071247 genotype association with CD80 tumor RNA expression (p = 0.006). An additional eQTL SNP in CD80 was associated with shorter survival (rs7804190, p = 8.1×10−4) among all cases combined. As the products of these genes are known to affect induction, trafficking, or immunosuppressive function of Tregs, these results suggest the need for follow-up phenotypic studies.
Mutations in the BRCA1 gene substantially increase a woman's lifetime risk of breast cancer. However, there is great variation in this increase in risk with several genetic and non-genetic modifiers identified. The BRCA1 protein plays a central role in DNA repair, a mechanism that is particularly instrumental in safeguarding cells against tumorigenesis. We hypothesized that polymorphisms that alter the expression and/or function of BRCA1 carried on the wild-type (non-mutated) copy of the BRCA1 gene would modify the risk of breast cancer in carriers of BRCA1 mutations. A total of 9874 BRCA1 mutation carriers were available in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) for haplotype analyses of BRCA1. Women carrying the rare allele of single nucleotide polymorphism rs16942 on the wild-type copy of BRCA1 were at decreased risk of breast cancer (hazard ratio 0.86, 95% confidence interval 0.77–0.95, P = 0.003). Promoter in vitro assays of the major BRCA1 haplotypes showed that common polymorphisms in the regulatory region alter its activity and that this effect may be attributed to the differential binding affinity of nuclear proteins. In conclusion, variants on the wild-type copy of BRCA1 modify risk of breast cancer among carriers of BRCA1 mutations, possibly by altering the efficiency of BRCA1 transcription.
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).
Genotyping data for 12,599 BRCA1 and 7,132 BRCA2 mutation carriers from 40 studies were combined.
We confirmed associations between rs8170 at 19p13.1 and breast cancer risk for BRCA1 mutation carriers (hazard ratio (HR)=1.17; 95%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).
19p13.1 and ZNF365 are susceptibility loci for ovarian cancer and ER subtypes of breast cancer among BRCA1 and BRCA2 mutation carriers.
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.
BRCA1; BRCA2; breast cancer risk; ovarian cancer risk; 19p13.1; ZNF365
Germline mutations in BRCA1 and BRCA2 are associated with increased risks of breast and ovarian cancer. A genome-wide association study (GWAS) identified six alleles associated with risk of ovarian cancer for women in the general population. We evaluated four of these loci as potential modifiers of ovarian cancer risk for BRCA1 and BRCA2 mutation carriers. Four single-nucleotide polymorphisms (SNPs), rs10088218 (at 8q24), rs2665390 (at 3q25), rs717852 (at 2q31), and rs9303542 (at 17q21), were genotyped in 12,599 BRCA1 and 7,132 BRCA2 carriers, including 2,678 ovarian cancer cases. Associations were evaluated within a retrospective cohort approach. All four loci were associated with ovarian cancer risk in BRCA2 carriers; rs10088218 per-allele hazard ratio (HR) = 0.81 (95% CI: 0.67–0.98) P-trend = 0.033, rs2665390 HR = 1.48 (95% CI: 1.21–1.83) P-trend = 1.8 × 10−4, rs717852 HR = 1.25 (95% CI: 1.10–1.42) P-trend = 6.6 × 10−4, rs9303542 HR = 1.16 (95% CI: 1.02–1.33) P-trend = 0.026. Two loci were associated with ovarian cancer risk in BRCA1 carriers; rs10088218 per-allele HR = 0.89 (95% CI: 0.81–0.99) P-trend = 0.029, rs2665390 HR = 1.25 (95% CI: 1.10–1.42) P-trend = 6.1 × 10−4. The HR estimates for the remaining loci were consistent with odds ratio estimates for the general population. The identification of multiple loci modifying ovarian cancer risk may be useful for counseling women with BRCA1 and BRCA2 mutations regarding their risk of ovarian cancer.
ovarian cancer; BRCA1; BRCA2; association; SNP
The importance of inflammation pathways to the development of many human cancers prompted us to examine the associations between single-nucleotide polymorphisms (SNPs) in inflammation-related genes and risk of ovarian cancer. In a multi-site case-control study, we genotyped SNPs in a large panel of inflammatory genes in 930 epithelial ovarian cancer cases and 1,037 controls using a custom array and analyzed by logistic regression. SNPs with p<0.10 were evaluated among 3,143 cases and 2,102 controls from the Follow-up of Ovarian Cancer Genetic Association and Interaction Studies (FOCI) collaboration. Combined analysis revealed association with SNPs rs17561 and rs4848300 in the interleukin gene IL1A which varied by histologic subtype (heterogeneity p=0.03). For example, IL1A rs17561, which correlates with numerous inflammatory phenotypes, was associated with decreased risk of clear cell, mucinous, and endometrioid subtype, but not with the most common serous subtype. Genotype at rs1864414 in the arachidonate 5-lipoxygenase ALOX5 was also associated with decreased risk. Thus, inherited variation in IL1A and ALOX5 appears to affect ovarian cancer risk which, for IL1A, is limited to rarer subtypes. Given the importance of inflammation in tumorigenesis and growing evidence of subtype-specific features in ovarian cancer, functional investigations will be important to help clarify the importance of inherited variation related to inflammation in ovarian carcinogenesis.