Variation in NF-κB signaling pathways and survival in invasive epithelial ovarian cancer

Survival in epithelial ovarian cancer (EOC) is influenced by the host immune response, yet the key genetic determinants of inflammation and immunity that affect prognosis are not known. The nuclear factor-κB (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 caspase recruitment domain family, member 11 (CARD11) rs41324349 in patients with mucinous EOC [HR, 1.82; 95% confidence interval (CI), 1.41-2.35; P = 4.13 × 10(-6)] and tumor necrosis factor receptor superfamily, member 13B (TNFRSF13B) 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 TNF receptor-associated factor 2 (TRAF2) rs17250239 in patients with high-grade serous EOC (HR, 0.84; 95% CI, 0.77-0.92; P = 6.49 × 10(-5)) and phospholipase C, gamma 1 (PLCG1) 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.

Genome-wide association study of subtype-specific epithelial ovarian cancer risk alleles using pooled DNA

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 six 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.

Assessing the goodness of fit of personal risk models

We describe a flexible family of tests for evaluating the goodness of fit (calibration) of a pre-specified personal risk model to the outcomes observed in a longitudinal cohort. Such evaluation involves using the risk model to assign each subject an absolute risk of developing the outcome within a given time from cohort entry and comparing subjects' assigned risks with their observed outcomes. This comparison involves several issues. For example, subjects followed only for part of the risk period have unknown outcomes. Moreover, existing tests do not reveal the reasons for poor model fit when it occurs, which can reflect misspecification of the model's hazards for the competing risks of outcome development and death. To address these issues, we extend the model-specified hazards for outcome and death, and use score statistics to test the null hypothesis that the extensions are unnecessary. Simulated cohort data applied to risk models whose outcome and mortality hazards agreed and disagreed with those generating the data show that the tests are sensitive to poor model fit, provide insight into the reasons for poor fit, and accommodate a wide range of model misspecification. We illustrate the methods by examining the calibration of two breast cancer risk models as applied to a cohort of participants in the Breast Cancer Family Registry. The methods can be implemented using the Risk Model Assessment Program, an R package freely available at http://stanford.edu/~ggong/rmap/.

A genome-wide association study of early-onset breast cancer identifies PFKM as a novel breast cancer gene and supports a common genetic spectrum for breast cancer at any age

Early-onset breast cancer (EOBC) causes substantial loss of life and productivity, creating a major burden among women worldwide. We analyzed 1,265,548 Hapmap3 single-nucleotide polymorphisms (SNP) among a discovery set of 3,523 EOBC incident cases and 2,702 population control women ages ≤ 51 years. The SNPs with smallest P values were examined in a replication set of 3,470 EOBC cases and 5,475 control women. We also tested EOBC association with 19,684 genes by annotating each gene with putative functional SNPs, and then combining their P values to obtain a gene-based P value. We examined the gene with smallest P value for replication in 1,145 breast cancer cases and 1,142 control women. The combined discovery and replication sets identified 72 new SNPs associated with EOBC (P < 4 × 10(-8)) located in six genomic regions previously reported to contain SNPs associated largely with later-onset breast cancer (LOBC). SNP rs2229882 and 10 other SNPs on chromosome 5q11.2 remained associated (P < 6 × 10(-4)) after adjustment for the strongest published SNPs in the region. Thirty-two of the 82 currently known LOBC SNPs were associated with EOBC (P < 0.05). Low power is likely responsible for the remaining 50 unassociated known LOBC SNPs. The gene-based analysis identified an association between breast cancer and the phosphofructokinase-muscle (PFKM) gene on chromosome 12q13.11 that met the genome-wide gene-based threshold of 2.5 × 10(-6). In conclusion, EOBC and LOBC seem to have similar genetic etiologies; the 5q11.2 region may contain multiple distinct breast cancer loci; and the PFKM gene region is worthy of further investigation. These findings should enhance our understanding of the etiology of breast cancer.

DNA glycosylases involved in base excision repair may be associated with cancer risk in BRCA1 and BRCA2 mutation carriers

Single Nucleotide Polymorphisms (SNPs) in genes involved in the DNA Base Excision Repair (BER) pathway could be associated with cancer risk in carriers of mutations in the high-penetrance susceptibility genes BRCA1 and BRCA2, given the relation of synthetic lethality that exists between one of the components of the BER pathway, PARP1 (poly ADP ribose polymerase), and both BRCA1 and BRCA2. In the present study, we have performed a comprehensive analysis of 18 genes involved in BER using a tagging SNP approach in a large series of BRCA1 and BRCA2 mutation carriers. 144 SNPs were analyzed in a two stage study involving 23,463 carriers from the CIMBA consortium (the Consortium of Investigators of Modifiers of BRCA1 and BRCA2). Eleven SNPs showed evidence of association with breast and/or ovarian cancer at p<0.05 in the combined analysis. Four of the five genes for which strongest evidence of association was observed were DNA glycosylases. The strongest evidence was for rs1466785 in the NEIL2 (endonuclease VIII-like 2) gene (HR: 1.09, 95% CI (1.03-1.16), p = 2.7 × 10(-3)) for association with breast cancer risk in BRCA2 mutation carriers, and rs2304277 in the OGG1 (8-guanine DNA glycosylase) gene, with ovarian cancer risk in BRCA1 mutation carriers (HR: 1.12 95%CI: 1.03-1.21, p = 4.8 × 10(-3)). DNA glycosylases involved in the first steps of the BER pathway may be associated with cancer risk in BRCA1/2 mutation carriers and should be more comprehensively studied.

Large-scale evaluation of common variation in regulatory T cell-related genes and ovarian cancer outcome

The presence of regulatory T cells (Treg) in solid tumors is known to play a role in patient survival in ovarian cancer and other malignancies. We assessed inherited genetic variations via 749 tag single-nucleotide polymorphisms (SNP) in 25 Treg-associated genes (CD28, CTLA4, FOXP3, IDO1, IL10, IL10RA, IL15, 1L17RA, IL23A, IL23R, IL2RA, IL6, IL6R, IL8, LGALS1, LGALS9, MAP3K8, STAT5A, STAT5B, TGFB1, TGFB2, TGFB3, TGFBR1, TGRBR2, and TGFBR3) in relation to ovarian cancer survival. We analyzed genotype and overall survival in 10,084 women with invasive epithelial ovarian cancer, including 5,248 high-grade serous, 1,452 endometrioid, 795 clear cell, and 661 mucinous carcinoma cases of European descent across 28 studies from the Ovarian Cancer Association Consortium (OCAC). The strongest associations were found for endometrioid carcinoma and IL2RA SNPs rs11256497 [HR, 1.42; 95% confidence interval (CI), 1.22-1.64; P = 5.7 × 10(-6)], rs791587 (HR, 1.36; 95% CI, 1.17-1.57; P = 6.2 × 10(-5)), rs2476491 (HR, = 1.40; 95% CI, 1.19-1.64; P = 5.6 × 10(-5)), and rs10795763 (HR, 1.35; 95% CI, 1.17-1.57; P = 7.9 × 10(-5)), and for clear cell carcinoma and CTLA4 SNP rs231775 (HR, 0.67; 95% CI, 0.54-0.82; P = 9.3 × 10(-5)) after adjustment for age, study site, population stratification, stage, grade, and oral contraceptive use. The rs231775 allele associated with improved survival in our study also results in an amino acid change in CTLA4 and previously has been reported to be associated with autoimmune conditions. Thus, we found evidence that SNPs in genes related to Tregs seem to play a role in ovarian cancer survival, particularly in patients with clear cell and endometrioid epithelial ovarian cancer.

Association analysis of 9,560 prostate cancer cases from the International Consortium of Prostate Cancer Genetics confirms the role of reported prostate cancer associated SNPs for familial disease

Previous GWAS studies have reported significant associations between various common SNPs and prostate cancer risk using cases unselected for family history. How these variants influence risk in familial prostate cancer is not well studied. Here, we analyzed 25 previously reported SNPs across 14 loci from prior prostate cancer GWAS. The International Consortium for Prostate Cancer Genetics (ICPCG) previously validated some of these using a family-based association method (FBAT). However, this approach suffered reduced power due to the conditional statistics implemented in FBAT. Here, we use a case-control design with an empirical analysis strategy to analyze the ICPCG resource for association between these 25 SNPs and familial prostate cancer risk. Fourteen sites contributed 12,506 samples (9,560 prostate cancer cases, 3,368 with aggressive disease, and 2,946 controls from 2,283 pedigrees). We performed association analysis with Genie software which accounts for relationships. We analyzed all familial prostate cancer cases and the subset of aggressive cases. For the familial prostate cancer phenotype, 20 of the 25 SNPs were at least nominally associated with prostate cancer and 16 remained significant after multiple testing correction (p ≤ 1E (-3)) occurring on chromosomal bands 6q25, 7p15, 8q24, 10q11, 11q13, 17q12, 17q24, and Xp11. For aggressive disease, 16 of the SNPs had at least nominal evidence and 8 were statistically significant including 2p15. The results indicate that the majority of common, low-risk alleles identified in GWAS studies for all prostate cancer also contribute risk for familial prostate cancer, and that some may contribute risk to aggressive disease.

Risk of ovarian cancer and the NF-κB pathway: genetic association with IL1A and TNFSF10

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

The impact of body mass index on treatment recommendations for patients with intermediate risk prostate cancer

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Background: To evaluate the clinical utility of body mass index (BMI) in predicting adverse pathologic outcomes, hence the need for radiation therapy (RT) following radical prostatectomy (RP) for men with organ-confined prostate cancer. Methods: We compared BMI and preoperative risk factors to adverse pathologic risk factors (RP-risk) that dictate the use of RT following RP. Multivariate analysis was used to determine whether BMI provides clinically relevant information in predicting RP-risk for additional RT as well as biochemical outcome. Results: Patients with elevated BMI had higher RP-risk (p=0.002). Specifically, extraprostatic extension, p less than 0.001; positive surgical margins, p=0.005; and a trend towards worse seminal vesicle invasion, p=0.08. Elevated BMI did not correlate with preoperative risk groupings (p=0.38). However, in patients with intermediate-risk disease BMI greater than 29kg/m2 was strongly associated with higher RP-risk (p=0.03) and higher rate of pathologic upgrading of tumors (p<0.004). Intermediate risk patients with BMI greater than 29kg/m2had a two-fold increased risk of requiring RT following RP based on greater than or equal to two adverse pathologic factors (15% vs. 34%). After controlling for known preoperative risk factors, BMI was an independent predictor of RP-risk for additional RT (p=0.006) and biochemical recurrence (p=0.03). Conclusions: BMI of greater than 29kg/m2 is an independent predictor of adverse RP-risk requiring additional RT, particularly in patients with intermediate risk disease. This select group of patients may be best treated with definitive radiation therapy to prevent the additional toxicity from adjuvant or salvage RT following RP. We propose including BMI in clinical decision-making for appropriate treatment recommendation for patients with intermediate risk prostate cancer.

Evaluation of a cancer gene sequencing panel in a hereditary risk assessment clinic

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Background: Multiple-gene sequencing panels are entering clinical practice. We report on research testing with a custom sequencing panel comprising 43 genes and 32 cancer-associated variants among patients referred for assessment of hereditary breast and ovarian cancer risk. Methods: Patients referred to the Stanford Cancer Genetics Program for clinical BRCA1 and BRCA2 (BRCA1/2) mutation testing from 2002-2012 were invited to donate a blood sample for research on an Institutional Review Board-approved protocol. Blood samples were frozen at -80 degrees, and DNA extracted after <1-10 years. The entire coding region, exon-intron boundaries (+/- 10bp) and all known pathogenic variants in other regions were sequenced for 43 genes that have published associations with risk of breast, ovarian and other cancers. An additional 32 cancer-associated variants were also sequenced. Clinically significant results were disclosed to patients. Results: Germline DNA samples were sequenced from 199 women: 141 had breast cancer, and 57 carried known BRCA1/2 mutations. Analytic results for BRCA1/2 sequencing and pathogenicity interpretations were concordant with prior clinical testing for all patients. Twenty variants designated as pathogenic, either based on published literature or due to a novel truncating or splice donor/acceptor effect, were observed in genes other than BRCA1/2, including ATM, BLM, CDH1, CDKN2A, MUTYH, MLH1, NBN, PRSS1, and SLX4. Thirteen patients had pathogenic variants warranting a change in cancer screening or risk reduction based on practice guidelines; they were invited for confirmatory clinical testing and counseling. One 53-year old patient with a personal history of breast and endometrial cancers was found to carry a pathogenic MLH1 mutation; she underwent risk-reducing salpingo-oophorectomy and colonoscopy, with removal of a tubular adenoma. Conclusions: Among patients referred for BRCA1/2 mutation testing, a comprehensive sequencing assay identified 20 [10.1%, 95% confidence interval (CI) 6.5%-15.1%] pathogenic mutations in other genes, of which 13 (6.5%, CI 3.8%-11%) prompted a change in care. Disclosure of research results to participants was feasible and well-tolerated.

Hormone-receptor expression and ovarian cancer survival: an Ovarian Tumor Tissue Analysis consortium study

BACKGROUND

Few biomarkers of ovarian cancer prognosis have been established, partly because subtype-specific associations might be obscured in studies combining all histopathological subtypes. We examined whether tumour expression of the progesterone receptor (PR) and oestrogen receptor (ER) was associated with subtype-specific survival.

METHODS

12 studies participating in the Ovarian Tumor Tissue Analysis consortium contributed tissue microarray sections and clinical data to our study. Participants included in our analysis had been diagnosed with invasive serous, mucinous, endometrioid, or clear-cell carcinomas of the ovary. For a patient to be eligible, tissue microarrays, clinical follow-up data, age at diagnosis, and tumour grade and stage had to be available. Clinical data were obtained from medical records, cancer registries, death certificates, pathology reports, and review of histological slides. PR and ER statuses were assessed by central immunohistochemistry analysis done by masked pathologists. PR and ER staining was defined as negative (<1% tumour cell nuclei), weak (1 to <50%), or strong (≥50%). Associations with disease-specific survival were assessed.

FINDINGS

2933 women with invasive epithelial ovarian cancer were included: 1742 with high-grade serous carcinoma, 110 with low-grade serous carcinoma, 207 with mucinous carcinoma, 484 with endometrioid carcinoma, and 390 with clear-cell carcinoma. PR expression was associated with improved disease-specific survival in endometrioid carcinoma (log-rank p<0·0001) and high-grade serous carcinoma (log-rank p=0·0006), and ER expression was associated with improved disease-specific survival in endometrioid carcinoma (log-rank p<0·0001). We recorded no significant associations for mucinous, clear-cell, or low-grade serous carcinoma. Positive hormone-receptor expression (weak or strong staining for PR or ER, or both) was associated with significantly improved disease-specific survival in endometrioid carcinoma compared with negative hormone-receptor expression, independent of study site, age, stage, and grade (hazard ratio 0·33, 95% CI 0·21-0·51; p<0·0001). Strong PR expression was independently associated with improved disease-specific survival in high-grade serous carcinoma (0·71, 0·55-0·91; p=0·0080), but weak PR expression was not (1·02, 0·89-1·18; p=0·74).

INTERPRETATION

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 establish whether hormone-receptor status predicts response to endocrine treatment, and whether it could guide personalised treatment for ovarian cancer.

FUNDING

Carraresi Foundation and others.

Diagnostic chest X-rays and breast cancer risk before age 50 years for BRCA1 and BRCA2 mutation carriers

BACKGROUND

The effects of low-dose medical radiation on breast cancer risk are uncertain, and few studies have included genetically susceptible women, such as those who carry germline BRCA1 and BRCA2 mutations.

METHODS

We studied 454 BRCA1 and 273 BRCA2 mutation carriers ages younger than 50 years from three breast cancer family registries in the United States, Canada, and Australia/New Zealand. We estimated breast cancer risk associated with diagnostic chest X-rays by comparing mutation carriers with breast cancer (cases) with those without breast cancer (controls). Exposure to chest X-rays was self-reported. Mammograms were not considered in the analysis.

RESULTS

After adjusting for known risk factors for breast cancer, the ORs for a history of diagnostic chest X-rays, excluding those for tuberculosis or pneumonia, were 1.16 [95% confidence interval (CI), 0.64-2.11] for BRCA1 mutations carriers and 1.22 (95% CI, 0.62-2.42) for BRCA2 mutations carriers. The OR was statistically elevated for BRCA2 mutation carriers with three to five diagnostic chest X-rays (P = 0.01) but not for those with six or more chest X-rays. Few women reported chest fluoroscopy for tuberculosis or chest X-rays for pneumonia; the OR estimates were elevated, but not statistically significant, for BRCA1 mutation carriers.

CONCLUSIONS

Our findings do not support a positive association between diagnostic chest X-rays and breast cancer risk before the ages of 50 years for BRCA1 or BRCA2 mutation carriers.

IMPACT

Given the increasing use of diagnostic imaging involving higher ionizing radiation doses, further studies of genetically predisposed women are warranted.

Decreased TGFBR1 signaling and breast cancer

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Background: We previously identified TGFBR1*6A (rs11466445), a hypomorphic TGF-beta type 1 receptor variant that is associated with cancer risk, has impaired TGF-beta signaling capability, and enhances the migration and invasion of breast cancer cells (Cancer Res 2008, 68:1319). Two recent large meta-analyses of case control studies have found a significant association between TGFBR1*6A and risk of breast cancer (Mol Biol Rep 2010 37:3227; PLoS One 2012,7(8). Rs7034462 is a single nucleotide polymorphism (SNP) in a noncoding region more than 9 kilobases upstream of TGFBR1 exon 1, which has been shown to be associated with decreased TGFBR1 expression similar to TGFBR1*6A (J Exp Clin Cancer Res 2010, 29:57). In this study we tested the hypothesis that rs7034462 may be associated with breast cancer risk. Methods: rs7034462 was genotyped in DNA obtained from patients with breast cancer and their unaffected sisters recruited by the Breast Cancer Family Registry (B-CFR). Results: The median age of cases and controls was 48.8 and 47.6 years, respectively. Using a simple case-control genetic association analysis for this family-matched population, rs7034462 was found to be associated with breast cancer risk. Conclusions: TGFBR1 rs7034462 is emerging as a low penetrance breast cancer susceptibility allele suggesting that two distinct TGFBR1 SNPs, each associated with decreased TGFBR1 expression, may modulate breast cancer risk. [Table: see text]

Cigarette smoking and risk of ovarian cancer: a pooled analysis of 21 case-control studies

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Analysis of over 10,000 Cases finds no association between previously reported candidate polymorphisms and ovarian cancer outcome

BACKGROUND

Ovarian cancer is a leading cause of cancer-related death among women. In an effort to understand contributors to disease outcome, we evaluated single-nucleotide polymorphisms (SNP) previously associated with ovarian cancer recurrence or survival, specifically in angiogenesis, inflammation, mitosis, and drug disposition genes.

METHODS

Twenty-seven SNPs in VHL, HGF, IL18, PRKACB, ABCB1, CYP2C8, ERCC2, and ERCC1 previously associated with ovarian cancer outcome were genotyped in 10,084 invasive cases from 28 studies from the Ovarian Cancer Association Consortium with over 37,000-observed person-years and 4,478 deaths. Cox proportional hazards models were used to examine the association between candidate SNPs and ovarian cancer recurrence or survival with and without adjustment for key covariates.

RESULTS

We observed no association between genotype and ovarian cancer recurrence or survival for any of the SNPs examined.

CONCLUSIONS

These results refute prior associations between these SNPs and ovarian cancer outcome and underscore the importance of maximally powered genetic association studies.

IMPACT

These variants should not be used in prognostic models. Alternate approaches to uncovering inherited prognostic factors, if they exist, are needed.

Two-stage sampling designs for external validation of personal risk models

We propose a cost-effective sampling design and estimating procedure for validating personal risk models using right-censored cohort data. Validation involves using each subject's covariates, as ascertained at cohort entry, in a risk model (specified independently of the data) to assign him/her a probability of an adverse outcome within a future time period. Subjects are then grouped according to the magnitudes of their assigned risks, and within each group, the mean assigned risk is compared with the probability of outcome occurrence as estimated using the follow-up data. Such validation presents two complications. First, in the presence of right-censoring, estimating the probability of developing the outcomes before death requires competing risk analysis. Second, for rare outcomes, validation using the full cohort requires assembling covariates and assigning risks to thousands of subjects. This can be costly when some covariates involve analyzing biological specimens. A two-stage sampling design addresses this problem by assembling covariates and assigning risks only to those subjects most informative for estimating key parameters. We use this design to estimate the outcome probabilities needed to evaluate model performance and we provide theoretical and bootstrap estimates of their variances. We also describe how to choose two-stage designs with minimal efficiency loss for a parameter of interest when the quantities determining optimality are unknown at the time of design. We illustrate these methods by using subjects in the California Teachers Study to validate ovarian cancer risk models. We find that a design with optimal efficiency for one performance parameter need not be so for others, and trade-offs will be required. A two-stage design that samples all outcome-positive subjects and more outcome-negative than censored subjects will perform well in most circumstances. The methods are implemented in Risk Model Assessment Program, an R program freely available at http://med.stanford.edu/epidemiology/two-stage.html.

Abstract 4856: Association between breast cancer and constitutively decreased TGFBR1 signaling

Background: We previously identified a hypomorphic TGF-β type 1 receptor variant (TGFBR1*6A) that is associated with cancer risk, has impaired TGF-β signaling capability and enhances the migration and invasion of breast cancer cells. Two recent large meta-analyses of case control studies have found a significant association between TGFBR1*6A and risk of breast cancer (ORs 1.16,1.01-1.34; 1.15,1.01-1.31). Rs7034462 is a single nucleotide polymorphism (SNP) in a noncoding region more than 9 kilobases upstream of TGFBR1 exon 1, which has been shown to be associated with decreased TGFBR1 expression. In this study we tested the hypothesis that rs7034462 may be associated with breast cancer risk.

Methods: rs7034462 was genotyped in DNA obtained from patients with breast cancer and healthy controls recruited by the Breast Cancer Family Registry. The samples in this multinational cohort were primarily from younger patients (average age 49.4 and 48.1 years for cases and controls, respectively, at time of interview).

Results: Using the Cockerham model, rs7034462 was found to be associated with breast cancer risk under the dominance genetic effect but, unexpectedly, there was a significant decreased association with breast cancer for this SNP under the additive genetic effect for this model.

SNP Cases Controls Cockerham Model Genetic Effect Odds Ratio 95% CI P rs7034462 (n = 2,934) 1509 1425 Additive 0.60 0.38-0.93 0.020 Dominance 2.09 1.29-3.38 0.002

Conclusion: rs7034462 heterozygotes have an increased risk of breast cancer but rare homozygotes have a decreased risk. This is the first evidence in humans that constitutively decreased TGFBR1-mediated TGF-β signaling is associated with breast cancer risk.

Citation Format: John C. Henegan, Lakisha Moore-Smith, Nengjun Yi, Kui Zhang, Habibul Ahsan, Alice S. Whittemore, Boris Pasche, BCFR Co-Investigators. Association between breast cancer and constitutively decreased TGFBR1 signaling. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4856. doi:10.1158/1538-7445.AM2013-4856

GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer

Genome-wide association studies (GWAS) have identified four susceptibility loci for epithelial ovarian cancer (EOC), with another two suggestive loci reaching near genome-wide significance. We pooled data from a GWAS conducted in North America with another GWAS from the UK. We selected the top 24,551 SNPs for inclusion on the iCOGS custom genotyping array. We performed follow-up genotyping in 18,174 individuals with EOC (cases) and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. We validated the two loci at 3q25 and 17q21 that were previously found to have associations close to genome-wide significance and identified three loci newly 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 and implicated CHMP4C in the pathogenesis of ovarian cancer.

Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer

TERT-locus SNPs and leukocyte telomere measures are reportedly associated with risks of multiple cancers. Using the Illumina custom genotyping array iCOGs, we analyzed ∼480 SNPs at the TERT locus in breast (n = 103,991), ovarian (n = 39,774) and BRCA1 mutation carrier (n = 11,705) cancer cases and controls. Leukocyte telomere measurements were also available for 53,724 participants. Most associations cluster into three independent peaks. The minor allele at the peak 1 SNP rs2736108 associates with longer telomeres (P = 5.8 × 10(-7)), lower risks for estrogen receptor (ER)-negative (P = 1.0 × 10(-8)) and BRCA1 mutation carrier (P = 1.1 × 10(-5)) breast cancers and altered promoter assay signal. The minor allele at the peak 2 SNP rs7705526 associates with longer telomeres (P = 2.3 × 10(-14)), higher risk of low-malignant-potential ovarian cancer (P = 1.3 × 10(-15)) and greater promoter activity. The minor alleles at the peak 3 SNPs rs10069690 and rs2242652 increase ER-negative (P = 1.2 × 10(-12)) and BRCA1 mutation carrier (P = 1.6 × 10(-14)) breast and invasive ovarian (P = 1.3 × 10(-11)) cancer risks but not via altered telomere length. The cancer risk alleles of rs2242652 and rs10069690, respectively, increase silencing and generate a truncated TERT splice variant.

Tubal ligation and risk of ovarian cancer subtypes: a pooled analysis of case-control studies

BACKGROUND

Tubal ligation is a protective factor for ovarian cancer, but it is unknown whether this protection extends to all invasive histological subtypes or borderline tumors. We undertook an international collaborative study to examine the association between tubal ligation and ovarian cancer subtypes.

METHODS

We pooled primary data from 13 population-based case-control studies, including 10,157 patients with ovarian cancer (7942 invasive; 2215 borderline) and 13,904 control women. Invasive cases were analysed by histological type, grade and stage, and borderline cases were analysed by histological type. Pooled odds ratios were estimated using conditional logistic regression to match on site, race/ethnicity and age categories, and to adjust for age, oral contraceptive use duration and number of full-term births.

RESULTS

Tubal ligation was associated with significantly reduced risks of invasive serous (OR, 0.81; 95% CI, 0.74-0.89; P < 0.001), endometrioid (OR, 0.48; 95% CI, 0.40-0.59; P < 0.001), clear cell (OR, 0.52; 95% CI, 0.40-0.67; P < 0.001) and mucinous (OR, 0.68; 95% CI, 0.52-0.89; P = 0.005) cancers. The magnitude of risk reduction was significantly greater for invasive endometrioid (P < 0.0001) and clear cell (P = 0.0018) than for serous cancer. No significant associations were found with borderline serous or mucinous tumours.

CONCLUSIONS

We found that the protective effects of tubal ligation on ovarian cancer risk were subtype-specific. These findings provide insights into distinct aetiologies of ovarian cancer subtypes and mechanisms underlying the protective effects of tubal ligation.

Identification and molecular characterization of a new ovarian cancer susceptibility locus at 17q21.31

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-related 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 (odds ratio=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 is associated 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.

HOXB13 is a susceptibility gene for prostate cancer: results from the International Consortium for Prostate Cancer Genetics (ICPCG)

Prostate cancer has a strong familial component but uncovering the molecular basis for inherited susceptibility for this disease has been challenging. Recently, a rare, recurrent mutation (G84E) in HOXB13 was reported to be associated with prostate cancer risk. Confirmation and characterization of this finding is necessary to potentially translate this information to the clinic. To examine this finding in a large international sample of prostate cancer families, we genotyped this mutation and 14 other SNPs in or flanking HOXB13 in 2,443 prostate cancer families recruited by the International Consortium for Prostate Cancer Genetics (ICPCG). At least one mutation carrier was found in 112 prostate cancer families (4.6 %), all of European descent. Within carrier families, the G84E mutation was more common in men with a diagnosis of prostate cancer (194 of 382, 51 %) than those without (42 of 137, 30 %), P = 9.9 × 10(-8) [odds ratio 4.42 (95 % confidence interval 2.56-7.64)]. A family-based association test found G84E to be significantly over-transmitted from parents to affected offspring (P = 6.5 × 10(-6)). Analysis of markers flanking the G84E mutation indicates that it resides in the same haplotype in 95 % of carriers, consistent with a founder effect. Clinical characteristics of cancers in mutation carriers included features of high-risk disease. These findings demonstrate that the HOXB13 G84E mutation is present in ~5 % of prostate cancer families, predominantly of European descent, and confirm its association with prostate cancer risk. While future studies are needed to more fully define the clinical utility of this observation, this allele and others like it could form the basis for early, targeted screening of men at elevated risk for this common, clinically heterogeneous cancer.

Epigenetic analysis leads to identification of HNF1B as a subtype-specific susceptibility gene for ovarian cancer

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.

Breast cancer risk assessment across the risk continuum: genetic and nongenetic risk factors contributing to differential model performance

Introduction

Clinicians use different breast cancer risk models for patients considered at average and above-average risk, based largely on their family histories and genetic factors. We used longitudinal cohort data from women whose breast cancer risks span the full spectrum to determine the genetic and nongenetic covariates that differentiate the performance of two commonly used models that include nongenetic factors - BCRAT, also called Gail model, generally used for patients with average risk and IBIS, also called Tyrer Cuzick model, generally used for patients with above-average risk.

Methods

We evaluated the performance of the BCRAT and IBIS models as currently applied in clinical settings for 10-year absolute risk of breast cancer, using prospective data from 1,857 women over a mean follow-up length of 8.1 years, of whom 83 developed cancer. This cohort spans the continuum of breast cancer risk, with some subjects at lower than average population risk. Therefore, the wide variation in individual risk makes it an interesting population to examine model performance across subgroups of women. For model calibration, we divided the cohort into quartiles of model-assigned risk and compared differences between assigned and observed risks using the Hosmer-Lemeshow (HL) chi-squared statistic. For model discrimination, we computed the area under the receiver operator curve (AUC) and the case risk percentiles (CRPs).

Results

The 10-year risks assigned by BCRAT and IBIS differed (range of difference 0.001 to 79.5). The mean BCRAT- and IBIS-assigned risks of 3.18% and 5.49%, respectively, were lower than the cohort's 10-year cumulative probability of developing breast cancer (6.25%; 95% confidence interval (CI) = 5.0 to 7.8%). Agreement between assigned and observed risks was better for IBIS (HL X₄² = 7.2, P value 0.13) than BCRAT (HL X₄² = 22.0, P value <0.001). The IBIS model also showed better discrimination (AUC = 69.5%, CI = 63.8% to 75.2%) than did the BCRAT model (AUC = 63.2%, CI = 57.6% to 68.9%). In almost all covariate-specific subgroups, BCRAT mean risks were significantly lower than the observed risks, while IBIS risks showed generally good agreement with observed risks, even in the subgroups of women considered at average risk (for example, no family history of breast cancer, BRCA1/2 mutation negative).

Conclusions

Models developed using extended family history and genetic data, such as the IBIS model, also perform well in women considered at average risk (for example, no family history of breast cancer, BRCA1/2 mutation negative). Extending such models to include additional nongenetic information may improve performance in women across the breast cancer risk continuum.

Abstract PR-02: Breast Cancer Risk Assessment: Genetic and Non-Genetic Risk Factors contributing to Differential Model Performance

Introduction: Clinicians use different breast cancer risk models for patients considered at average and above-average risk, based largely on their family histories and genetic factors. To explore the feasibility of a single model appropriate for all women, we used longitudinal cohort data from women whose breast cancer risks span the full spectrum to determine the covariates that differentiate the performance of two commonly used models, BCRAT, or also called GAIL model, (used for patients with average risk) and IBIS, or also called Tyrer Cuzick model, (for patients with above-average risk).

Methods: We evaluated the performance of BCRAT and IBIS for ten-year absolute risk of breast cancer, using prospective data from 1,857 women over a mean follow-up length of 8.1 years, of whom 83 developed cancer. This cohort spans the continuum of breast cancer risk, with some subjects at lower than average population risk. Therefore, the wide-variation in individual risk makes it an interesting population to examine model performance across subgroups of women. For model calibration, we divided the cohort into quartiles of model-assigned risk and comparing differences between assigned and observed risks using the Hosmer-Lemeshow (HL) chi-squared statistic. For model discrimination, we computed the area under the receiver operator curve (AUC) and the case risk percentiles (CRPs).

Results: The ten-year risks assigned by BCRAT and IBIS differed (range of difference 0.001 to 79.5). The mean BCRAT- and IBIS-assigned risks of 3.18% and 5.59%, respectively, were lower than the cohort's 10-year cumulative probability of developing breast cancer (6.25%; 95% confidence interval (CI) = 5.0-7.8%). Agreement between assigned and observed risks was better for IBIS (HL X42 =7.2, P-value 0.13) than BCRAT (HL X42 = 22.0, P-value &lt; 0.001). The IBIS model also showed better discrimination (AUC = 69.5%, CI = 63.8% - 75.2%) than did the BCRAT model (AUC = 63.2%, CI = 57.6% - 68.9%). In almost all covariate-specific subgroups, BCRAT mean risks were significantly lower than the observed risks, while IBIS risks showed generally good agreement with observed risks, even in the subgroups of women considered at average risk (e.g., no family history of breast cancer, BRCA1/2 mutation negative). Conclusions: Models developed using extended family history and genetic data, such as the IBIS model, also perform well in women considered at average risk (e.g. no family history of breast cancer, BRCA1/2 mutation negative). Extending such models to include nongenetic information (e.g., breast biopsy history and race/ethnicity) may improve their performance among all women across the breast cancer risk continuum.

This abstract is also presented as Poster A109.

Citation Format: Anne S. Quante, Alice S. Whittemore, Mary Beth Terry. Breast cancer risk assessment: Genetic and nongenetic risk factors contributing to differential model performance. [abstract]. In: Proceedings of the Eleventh Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2012 Oct 16-19; Anaheim, CA. Philadelphia (PA): AACR; Cancer Prev Res 2012;5(11 Suppl):Abstract nr PR-02.