Genome-wide association studies have reported eleven regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10−5). For three cis-eQTL associations (P<1.4×10−3, FDR<0.05) at 1p36 (CDC42), 1p34 (CDCA8) and 2q31 (HOXD9), we evaluate the functional role of each candidate by perturbing expression of each gene in HGSOC precursor cells. Overexpression of HOXD9 increases anchorage-independent growth, shortens population-doubling time and reduces contact inhibition. Chromosome conformation capture identifies an interaction between rs2857532 and the HOXD9 promoter, suggesting this SNP is a leading causal variant. Transcriptomic profiling after HOXD9 overexpression reveals enrichment of HGSOC risk variants within HOXD9 target genes (P=6×10−10 for risk variants (P<10−4) within 10kb of a HOXD9 target gene in ovarian cells), suggesting a broader role for this network in genetic susceptibility to HGSOC.
Most solid tumours contain cancer-associated fibroblasts (CAFs) that support tumourigenesis and malignant progression. However the cellular origins of CAFs in epithelial ovarian cancers (EOCs) remain poorly understood, and their utility as a source of clinical biomarkers for cancer diagnosis has not been explored in great depth. Here, we report establishing in vitro and in vivo models of CAFs in ovarian cancer development. Normal ovarian fibroblasts and mesenchymal stem cells cultured in the presence of EOC cells acquired a CAF-like phenotype, and promoted EOC cell migration in vitro. CAFs also promoted ovarian cancer growth in vivo in both subcutaneous and intraperitoneal murine xenograft assays. Molecular profiling of CAFs identified gene expression signatures that were highly enriched for extracellular and secreted proteins. We identified novel candidate CAF specific biomarkers for ovarian cancer including NPPB, which was expressed in the stroma of 60% primary ovarian cancer tissues (n=145) but not in the stroma of normal ovaries (n=4). NPPB is a secreted protein that was also elevated in the blood of 50% of women with ovarian cancer (n=8). Taken together these data suggest that the tumor stroma is a novel source of biomarkers, including NPPB, that may be of clinical utility for detection of EOC.
Disruption in circadian gene expression, whether due to genetic variation or environmental factors (e.g., light at night, shiftwork), is associated with increased incidence of breast, prostate, gastrointestinal and hematologic cancers and gliomas. Circadian genes are highly expressed in the ovaries where they regulate ovulation; circadian disruption is associated with several ovarian cancer risk factors (e.g., endometriosis). However, no studies have examined variation in germline circadian genes as predictors of ovarian cancer risk and invasiveness. The goal of the current study was to examine single nucleotide polymorphisms (SNPs) in circadian genes BMAL1, CRY2, CSNK1E, NPAS2, PER3, REV1 and TIMELESS and downstream transcription factors KLF10 and SENP3 as predictors of risk of epithelial ovarian cancer (EOC) and histopathologic subtypes. The study included a test set of 3,761 EOC cases and 2,722 controls and a validation set of 44,308 samples including 18,174 (10,316 serous) cases and 26,134 controls from 43 studies participating in the Ovarian Cancer Association Consortium (OCAC). Analysis of genotype data from 36 genotyped SNPs and 4600 imputed SNPs indicated that the most significant association was rs117104877 in BMAL1 (OR = 0.79, 95% CI = 0.68–0.90, p = 5.59 × 10−4]. Functional analysis revealed a significant down regulation of BMAL1 expression following cMYC overexpression and increasing transformation in ovarian surface epithelial (OSE) cells as well as alternative splicing of BMAL1 exons in ovarian and granulosa cells. These results suggest that variation in circadian genes, and specifically BMAL1, may be associated with risk of ovarian cancer, likely through disruption of hormonal pathways.
Epithelial-mesenchymal transition (EMT) is a process whereby epithelial cells assume mesenchymal characteristics to facilitate cancer metastasis. However, EMT also contributes to the initiation and development of primary tumors. Prior studies that explored the hypothesis that EMT gene variants contribute to EOC risk have been based on small sample sizes and none have sought replication in an independent population.
We screened 1254 SNPs in 296 genes in a discovery phase using data from a genome-wide association study of EOC among women of European ancestry (1,947 cases and 2,009 controls) and identified 793 variants in 278 EMT-related genes that were nominally (p<0.05) associated with invasive EOC. These SNPs were then genotyped in a larger study of 14,525 invasive-cancer patients and 23,447 controls. A p-value <0.05 and a false discovery rate (FDR) <0.2 was considered statistically significant.
In the larger dataset, GPC6/GPC5 rs17702471 was associated with the endometrioid subtype among Caucasians (OR=1.16, 95%CI=1.07–1.25, p=0.0003, FDR=0.19), while F8 rs7053448 (OR=1.69, 95%CI=1.27–2.24, p=0.0003, FDR=0.12), F8 rs7058826 (OR=1.69, 95%CI=1.27–2.24, p=0.0003, FDR=0.12), and CAPN13 rs1983383 (OR=0.79, 95%CI=0.69–0.90, p=0.0005, FDR=0.12) were associated with combined invasive EOC among Asians. In silico functional analyses revealed that GPC6/GPC5 rs17702471 coincided with DNA regulatory elements.
These results suggest that EMT gene variants do not appear to play a significant role in the susceptibility to EOC.
ovarian cancer; epithelial-mesenchymal transition; single nucleotide polymorphisms
The homeobox A (HOXA) region of protein-coding genes impacts female reproductive system embryogenesis and ovarian carcinogenesis. The 5-prime end of HOXA includes three long non-coding RNAs (lncRNAs) (HOXA10-AS, HOXA11-AS, and HOTTIP) that are underexplored in epithelial ovarian cancer (EOC). We evaluated whether common genetic variants in these lncRNAs are associated with EOC risk and/or have functional roles in EOC development. Using genome-wide association study data from 1,201 serous EOC cases and 2,009 controls, an exonic variant within HOXA11-AS, rs17427875 (A>T), was marginally associated with reduced serous EOC risk (OR = 0.88 (95% CI: 0.78-1.01, p = 0.06). Functional studies of ectopic expression of HOXA11-AS minor allele T in EOC cells showed decreased survival, proliferation, migration, and invasion compared to common allele A expression. Additionally, stable expression of HOXA11-AS minor allele T reduced primary tumor growth in mouse xenograft models to a greater extent than common allele A. Furthermore, HOXA11-AS expression levels were significantly lower in human EOC tumors than normal ovarian tissues (p < 0.05), suggesting that HOXA11-AS has a tumor suppressor function in EOC which may be enhanced by the T allele. These findings demonstrate for the first time a role for HOXA11-AS in EOC with effects that could be modified by germline variants.
ovarian cancer; genetic susceptibility; HOX cluster; long non-coding RNAs; single nucleotide polymorphisms
Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10−5). For three cis-eQTL associations (P<1.4 × 10−3, FDR<0.05) at 1p36 (CDC42), 1p34 (CDCA8) and 2q31 (HOXD9), we evaluate the functional role of each candidate by perturbing expression of each gene in HGSOC precursor cells. Overexpression of HOXD9 increases anchorage-independent growth, shortens population-doubling time and reduces contact inhibition. Chromosome conformation capture identifies an interaction between rs2857532 and the HOXD9 promoter, suggesting this SNP is a leading causal variant. Transcriptomic profiling after HOXD9 overexpression reveals enrichment of HGSOC risk variants within HOXD9 target genes (P=6 × 10−10 for risk variants (P<10−4) within 10 kb of a HOXD9 target gene in ovarian cells), suggesting a broader role for this network in genetic susceptibility to HGSOC.
Genome-wide association studies have identified regions which confer risk of high-grade serous epithelial ovarian cancer. Here the authors use expression quantitative train locus analysis to identify candidate genes and functionally characterise them, identifying a role for HOXD9 in ovarian cancer.
The majority of trait-associated loci discovered through genome-wide association studies are located outside of known protein coding regions. Consequently, it is difficult to ascertain the mechanism underlying these variants and to pinpoint the causal alleles. Expression quantitative trait loci (eQTLs) provide an organizing principle to address both of these issues. eQTLs are genetic loci that correlate with RNA transcript levels. Large-scale data sets such as the Cancer Genome Atlas (TCGA) provide an ideal opportunity to systematically evaluate eQTLs as they have generated multiple data types on hundreds of samples. We evaluated the determinants of gene expression (germline variants and somatic copy number and methylation) and performed cis-eQTL analyses for mRNA expression and miRNA expression in five tumor types (breast, colon, kidney, lung and prostate). We next tested 149 known cancer risk loci for eQTL effects, and observed that 42 (28.2%) were significantly associated with at least one transcript. Lastly, we described a fine-mapping strategy for these 42 eQTL target–gene associations based on an integrated strategy that combines the eQTL level of significance and the regulatory potential as measured by DNaseI hypersensitivity. For each of the risk loci, our analyses suggested 1 to 81 candidate causal variants that may be prioritized for downstream functional analysis. In summary, our study provided a comprehensive landscape of the genetic determinants of gene expression in different tumor types and ranked the genes and loci for further functional assessment of known cancer risk loci.
We re-evaluated previously reported associations between variants in pathways of one-carbon (folate) transfer genes and ovarian carcinoma (OC) risk, and in related pathways of purine and pyrimidine metabolism, and assessed interactions with folate intake.
Methods and Results
Odds ratios (OR) for 446 genetic variants were estimated among 13,410 OC cases and 22,635 controls and among 2,281 cases and 3,444 controls with folate information. Following multiple testing correction, the most significant main effect associations were for DPYD variants rs11587873 (OR=0.92, P=6x10−5) and rs828054 (OR=1.06, P=1x10−4). Thirteen variants in the pyrimidine metabolism genes, DPYD, DPYS, PPAT and TYMS, also interacted significantly with folate in a multi-variant analysis (corrected P=9.9x10−6) but collectively explained only 0.2% of OC risk. Although no other associations were significant after multiple testing correction, variants in SHMT1 in one-carbon transfer, previously reported with OC, suggested lower risk at higher folate (Pinteraction=0.03-0.006).
Variation in pyrimidine metabolism genes, particularly DPYD, which was previously reported to be associated with OC, may influence risk; however, stratification by folate intake is unlikely to modify disease risk appreciably in these women. SHMT1 SNP-byfolate interactions are plausible but require further validation. Polymorphisms in selected genes in purine metabolism were not associated with OC.
case-control; DPYD; folate; polymorphism; SHMT1
The aim of this study was to estimate the contribution of deleterious mutations in BRCA1, BRCA2, MLH1, MSH2, MSH6 and PMS2 to invasive epithelial ovarian cancer (EOC) in the population. The coding sequence and splice site boundaries of all six genes were amplified in germline DNA from 2240 invasive EOC cases and 1535 controls. Barcoded fragment libraries were sequenced using the Illumina GAII or HiSeq and sequence data for each subject de-multiplexed prior to interpretation. GATK and Annovar were used for variant detection and annotation. After quality control 2222 cases (99.2%) and 1528 controls (99.5%) were included in the final analysis. We identified 193 EOC cases (8.7%) carrying a deleterious mutation in at least one gene compared with 10 controls (0.65%). Mutations were most frequent in BRCA1 and BRCA2, with 84 EOC cases (3.8%) carrying a BRCA1 mutation and 94 EOC cases (4.2%) carrying a BRCA2 mutation. The combined BRCA1 and BRCA2 mutation prevalence was 11% in high-grade serous disease. Seventeen EOC cases carried a mutation in a mismatch repair gene, including 10 MSH6 mutation carriers (0.45%) and 4 MSH2 mutation carriers (0.18%). At least 1 in 10 women with high-grade serous EOC has a BRCA1 or BRCA2 mutation. The development of next generation sequencing technologies enables rapid mutation screening for multiple susceptibility genes at once, suggesting that routine clinical testing of all incidence cases should be considered.
To analyse the effect of germline mutations in BRCA1 and BRCA2 on mortality in ovarian cancer patients up to ten years after diagnosis.
We used unpublished survival time data for 2,242 patients from two case-control studies and extended survival-time data for 4,314 patients from previously reported studies. All participants had been screened for deleterious germline mutations in BRCA1 and BRCA2. Survival time was analysed for the combined data using Cox proportional hazard models with BRCA1 and BRCA2 as time-varying covariates. Competing risks were analysed using Fine and Gray model.
The combined 10-year overall survival was 30% (95% CI, 28%-31%) for non-carriers, 25% (95% CI, 22%-28%) for BRCA1 carriers, and 35% (95% CI, 30%-41%) for BRCA2 carriers. The hazard ratio for BRCA1 was 0.53 at time zero and increased over time becoming greater than one at ·4.8 years. For BRCA2, the hazard ratio was 0.42 at time zero and increased over time (predicted to become greater than one at 10.5 years). The results were similar when restricted to 3,202 patients with high-grade serous tumors, and to ovarian cancer specific mortality.
BRCA1/2 mutations are associated with better short-term survival, but this advantage decreases over time and, in BRCA1 carriers is eventually reversed. This may have important implications for therapy of both primary and relapsed disease and for analysis of long-term survival in clinical trials of new agents, particularly those that are effective in BRCA1/2 mutation carriers.
Ovarian cancer; Epithelial ovarian cancer; BRCA1 gene; BRCA2 gene; Survival
The molecular biology and cellular origins of mixed type endometrial carcinomas (MT-ECs) are poorly understood, and a Type II component of 10 percent or less may confer poorer prognoses.
We studied 10 cases of MT-EC (containing endometrioid and serous differentiation), 5 pure low-grade endometrioid adenocarcinoma (EAC) and 5 pure uterine serous carcinoma (USC). Endometrioid and serous components of the MT-ECs were macrodissected and the expression of 60 candidate genes compared between MT-EC, pure USC and pure EAC. We found that four genes were differentially expressed when MT-ECs were compared to pure low-grade EAC: CDKN2A (P = 0.006), H19 (P = 0.010), HOMER2 (P = 0.009) and TNNT1 (P = 0.006). Also while we found that even though MT-ECs closely resembled the molecular profiles of pure USCs, they also exhibit lower expression of PAX8 compared to all pure cases combined (P = 0.035).
Our data suggest that MT-EC exhibits the closest molecular and epidemiological similarities to pure USC and supports clinical observations that suggest patients with MT-EC should receive the same treatment as patients with pure serous carcinoma. Novel specific markers of MT-EC could be of diagnostic utility and could represent novel therapeutic targets in the future.
Defective cellular transport processes can lead to aberrant accumulation of trace elements, iron, small molecules and hormones in the cell, which in turn may promote the formation of reactive oxygen species, promoting DNA damage and aberrant expression of key regulatory cancer genes. As DNA damage and uncontrolled proliferation are hallmarks of cancer, including epithelial ovarian cancer (EOC), we hypothesized that inherited variation in the cellular transport genes contributes to EOC risk.
In total, DNA samples were obtained from 14,525 case subjects with invasive EOC and from 23,447 controls from 43 sites in the Ovarian Cancer Association Consortium (OCAC). Two hundred seventy nine SNPs, representing 131 genes, were genotyped using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS). SNP analyses were conducted using unconditional logistic regression under a log-additive model, and the FDR q<0.2 was applied to adjust for multiple comparisons.
The most significant evidence of an association for all invasive cancers combined and for the serous subtype was observed for SNP rs17216603 in the iron transporter gene HEPH (invasive: OR = 0.85, P = 0.00026; serous: OR = 0.81, P = 0.00020); this SNP was also associated with the borderline/low malignant potential (LMP) tumors (P = 0.021). Other genes significantly associated with EOC histological subtypes (p<0.05) included the UGT1A (endometrioid), SLC25A45 (mucinous), SLC39A11 (low malignant potential), and SERPINA7 (clear cell carcinoma). In addition, 1785 SNPs in six genes (HEPH, MGST1, SERPINA, SLC25A45, SLC39A11 and UGT1A) were imputed from the 1000 Genomes Project and examined for association with INV EOC in white-European subjects. The most significant imputed SNP was rs117729793 in SLC39A11 (per allele, OR = 2.55, 95% CI = 1.5-4.35, p = 5.66x10-4).
These results, generated on a large cohort of women, revealed associations between inherited cellular transport gene variants and risk of EOC histologic subtypes.
Epithelial ovarian cancer (EOC) is a heterogeneous cancer with both genetic and environmental risk factors. Variants influencing the risk of developing the less-common EOC subtypes have not been fully investigated. We performed a genome-wide association study (GWAS) of EOC according to subtype by pooling genomic DNA from 545 cases and 398 controls of European descent, and testing for allelic associations. We evaluated for replication 188 variants from the GWAS (56 variants for mucinous, 55 for endometrioid and clear cell, 53 for low malignant potential (LMP) serous, and 24 for invasive serous EOC), selected using pre-defined criteria. Genotypes from 13,188 cases and 23,164 controls of European descent were used to perform unconditional logistic regression under the log-additive genetic model; odds ratios (OR) and 95% confidence intervals are reported. Nine variants tagging 6 loci were associated with subtype-specific EOC risk at P<0.05, and had an OR that agreed in direction of effect with the GWAS results. Several of these variants are in or near genes with a biological rationale for conferring EOC risk, including ZFP36L1 and RAD51B for mucinous EOC (rs17106154, OR=1.17, P=0.029, n=1,483 cases), GRB10 for endometrioid and clear cell EOC (rs2190503, P=0.014, n=2,903 cases), and C22orf26/BPIL2 for LMP serous EOC (rs9609538, OR=0.86, P=0.0043, n=892 cases). In analyses that included the 75 GWAS samples, the association between rs9609538 (OR=0.84, P=0.0007) and LMP serous EOC risk remained statistically significant at P<0.0012 adjusted for multiple testing. Replication in additional samples will be important to verify these results for the less-common EOC subtypes.
histological subtype; serous; endometrioid; clear cell; mucinous; BPIL2
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 microenvironment plays an important role in tumorigenesis. Fibroblast activation protein alpha (FAP) is overexpressed by fibroblasts present in the microenvironment of many tumors. High FAP expression is a negative prognostic factor in several malignancies, but this has not been investigated in epithelial ovarian cancer (EOC). The aim of this study is to define the value of FAP in EOC. Immunohistochemical staining using an anti-FAP antibody was performed on 338 EOC tissues. mRNA levels in cancer cell lines and FAP silencing using siRNA was also done. FAP immunoexpression by tumor stroma was a significant predictive factor for platinum resistance (p = 0.0154). In survival analysis of days to recurrence, FAP stoma+ was associated with shorter recurrence than those with FAP− stroma (p = 0.0247). In 21.8 % of tumors, FAP protein was expressed by the tumor epithelium, and FAP mRNA was more highly expressed in tumors (n = 489) than in normal tissues (n = 8) (p = 3.88 × 10−4). In vitro, addition of FAP to EOC cells induced a 10–12 % increase in cell viability both in the presence and absence of cisplatin. Conversely, siRNA silencing of FAP resulted in ~10 % reduction in EOC cell proliferation. We have shown that FAP expression in EOC is associated with poorer clinical outcomes. FAP may have novel cell-autonomous effects suggesting that targeting FAP could have pleiotropic anti-tumor effects, and anti-FAP therapy could be a highly effective novel treatment for EOC, especially in cisplatinum-resistant cases.
Epithelial ovarian cancer; Fibroblast activation protein; Platinum resistance; Disease outcome; Tumor microenvironment; Cancer-associated fibroblast
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