METHODS AND FINDINGS: Genetic instruments to proxy 12 risk factors were constructed by identifying single nucleotide polymorphisms (SNPs) that were robustly (P < 5 × 10-8) and independently associated with each respective risk factor in previously reported genome-wide association studies. These risk factors included genetic liability to 3 factors (endometriosis, polycystic ovary syndrome, type 2 diabetes) scaled to reflect a 50% higher odds liability to disease. We obtained summary statistics for the association of these SNPs with risk of overall and histotype-specific invasive epithelial ovarian cancer (22,406 cases; 40,941 controls) and low malignant potential tumours (3,103 cases; 40,941 controls) from the Ovarian Cancer Association Consortium (OCAC). The OCAC dataset comprises 63 genotyping project/case-control sets with participants of European ancestry recruited from 14 countries (US, Australia, Belarus, Germany, Belgium, Denmark, Finland, Norway, Canada, Poland, UK, Spain, Netherlands, and Sweden). SNPs were combined into multi-allelic inverse-variance-weighted fixed or random effects models to generate effect estimates and 95% confidence intervals (CIs). Three complementary sensitivity analyses were performed to examine violations of MR assumptions: MR-Egger regression and weighted median and mode estimators. A Bonferroni-corrected P value threshold was used to establish strong evidence (P < 0.0042) and suggestive evidence (0.0042 < P < 0.05) for associations. In MR analyses, there was strong or suggestive evidence that 2 of the 12 risk factors were associated with invasive epithelial ovarian cancer and 8 of the 12 were associated with 1 or more invasive epithelial ovarian cancer histotypes. There was strong evidence that genetic liability to endometriosis was associated with an increased risk of invasive epithelial ovarian cancer (odds ratio [OR] per 50% higher odds liability: 1.10, 95% CI 1.06-1.15; P = 6.94 × 10-7) and suggestive evidence that lifetime smoking exposure was associated with an increased risk of invasive epithelial ovarian cancer (OR per unit increase in smoking score: 1.36, 95% CI 1.04-1.78; P = 0.02). In analyses examining histotypes and low malignant potential tumours, the strongest associations found were between height and clear cell carcinoma (OR per SD increase: 1.36, 95% CI 1.15-1.61; P = 0.0003); age at natural menopause and endometrioid carcinoma (OR per year later onset: 1.09, 95% CI 1.02-1.16; P = 0.007); and genetic liability to polycystic ovary syndrome and endometrioid carcinoma (OR per 50% higher odds liability: 0.89, 95% CI 0.82-0.96; P = 0.002). There was little evidence for an association of genetic liability to type 2 diabetes, parity, or circulating levels of 25-hydroxyvitamin D and sex hormone binding globulin with ovarian cancer or its subtypes. The primary limitations of this analysis include the modest statistical power for analyses of risk factors in relation to some less common ovarian cancer histotypes (low grade serous, mucinous, and clear cell carcinomas), the inability to directly examine the association of some ovarian cancer risk factors that did not have robust genetic variants available to serve as proxies (e.g., oral contraceptive use, hormone replacement therapy), and the assumption of linear relationships between risk factors and ovarian cancer risk.
CONCLUSIONS: Our comprehensive examination of possible aetiological drivers of ovarian carcinogenesis using germline genetic variants to proxy risk factors supports a role for few of these factors in invasive epithelial ovarian cancer overall and suggests distinct aetiologies across histotypes. The identification of novel risk factors remains an important priority for the prevention of epithelial ovarian cancer.
METHODS: We conducted a large agnostic pathway-based meta-analysis of GWAS data using the summary-based adaptive rank truncated product method to identify gene sets and pathways associated with pancreatic ductal adenocarcinoma (PDAC) in 9040 cases and 12 496 controls. We performed expression quantitative trait loci (eQTL) analysis and functional annotation of the top SNPs in genes contributing to the top associated pathways and gene sets. All statistical tests were two-sided.
RESULTS: We identified 14 pathways and gene sets associated with PDAC at a false discovery rate of less than 0.05. After Bonferroni correction (P ≤ 1.3 × 10-5), the strongest associations were detected in five pathways and gene sets, including maturity-onset diabetes of the young, regulation of beta-cell development, role of epidermal growth factor (EGF) receptor transactivation by G protein-coupled receptors in cardiac hypertrophy pathways, and the Nikolsky breast cancer chr17q11-q21 amplicon and Pujana ATM Pearson correlation coefficient (PCC) network gene sets. We identified and validated rs876493 and three correlating SNPs (PGAP3) and rs3124737 (CASP7) from the Pujana ATM PCC gene set as eQTLs in two normal derived pancreas tissue datasets.
CONCLUSION: Our agnostic pathway and gene set analysis integrated with functional annotation and eQTL analysis provides insight into genes and pathways that may be biologically relevant for risk of PDAC, including those not previously identified.
Objective: To evaluate mainstream genetic testing using cancer-based criteria in patients with cancer.
Design, Setting, and Participants: A quality improvement study and cost-effectiveness analysis of different BRCA testing selection criteria and access procedures to evaluate feasibility, acceptability, and mutation detection performance was conducted at the Royal Marsden National Health Service Foundation Trust as part of the Mainstreaming Cancer Genetics (MCG) Programme. Participants included 1184 patients with cancer who were undergoing genetic testing between September 1, 2013, and February 28, 2017.
Main Outcomes and Measures: Mutation rates, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios were the primary outcomes.
Results: Of the 1184 patients (1158 women [97.8%]) meeting simple cancer-based criteria, 117 had a BRCA mutation (9.9%). The mutation rate was similar in retrospective United Kingdom (10.2% [235 of 2294]) and prospective Malaysian (9.7% [103 of 1061]) breast cancer studies. If traditional family history criteria had been used, more than 50% of the mutation-positive individuals would have been missed. Of the 117 mutation-positive individuals, 115 people (98.3%) attended their genetics appointment and cascade to relatives is underway in all appropriate families (85 of 85). Combining with the equivalent ovarian cancer study provides 5 simple cancer-based criteria for BRCA testing with a 10% mutation rate: (1) ovarian cancer; (2) breast cancer diagnosed when patients are 45 years or younger; (3) 2 primary breast cancers, both diagnosed when patients are 60 years or younger; (4) triple-negative breast cancer; and (5) male breast cancer. A sixth criterion-breast cancer plus a parent, sibling, or child with any of the other criteria-can be added to address family history. Criteria 1 through 5 are considered the MCG criteria, and criteria 1 through 6 are considered the MCGplus criteria. Testing using MCG or MCGplus criteria is cost-effective with cost-effectiveness ratios of $1330 per discounted QALYs and $1225 per discounted QALYs, respectively, and appears to lead to cancer and mortality reductions (MCG: 804 cancers, 161 deaths; MCGplus: 1020 cancers, 204 deaths per year over 50 years). Use of MCG or MCGplus criteria might allow detection of all BRCA mutations in patients with breast cancer in the United Kingdom through testing one-third of patients. Feedback questionnaires from 259 patients and 23 cancer team members (12 oncologists, 8 surgeons, and 3 nurse specialists) showed acceptability of the process with 100% of patients pleased they had genetic testing and 100% of cancer team members confident to approve patients for genetic testing. Use of MCGplus criteria also appeared to be time and resource efficient, requiring 95% fewer genetic consultations than the traditional process.
Conclusions and Relevance: This study suggests that mainstream testing using simple, cancer-based criteria might be able to efficiently deliver consistent, cost-effective, patient-centered BRCA testing.
METHODS: Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations.
RESULTS: At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10-9) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10-9). SNP rs6902488 at 6p25.2 (r2 = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP <10%). At chromosome 20q11.22, rs74272064 was associated with HGSOC risk (OR = 1.27, P = 9.0 × 10-8). Overall EOC risk was associated with rs10260419 at chromosome 7p21.3 (OR = 1.33, P = 1.2 × 10-7) and rs74917072 at chromosome 2q37.3 (OR = 1.25, P = 4.7 × 10-7). At 2q37.3, expression quantitative trait locus analysis in 404 HGSOC tissues identified ESPNL as a putative candidate susceptibility gene (P = 1.2 × 10-7).
CONCLUSION: While some risk loci were shared between East Asian and European populations, others were population-specific, indicating that the landscape of EOC risk in Asian women has both shared and unique features compared to women of European ancestry.
METHODS: We used Mendelian randomization approaches to evaluate the association of height and BMI on breast cancer risk, using data from the Consortium of Investigators of Modifiers of BRCA1/2 with 14 676 BRCA1 and 7912 BRCA2 mutation carriers, including 11 451 cases of breast cancer. We created a height genetic score using 586 height-associated variants and a BMI genetic score using 93 BMI-associated variants. We examined both observed and genetically determined height and BMI with breast cancer risk using weighted Cox models. All statistical tests were two-sided.
RESULTS: Observed height was positively associated with breast cancer risk (HR = 1.09 per 10 cm increase, 95% confidence interval [CI] = 1.0 to 1.17; P = 1.17). Height genetic score was positively associated with breast cancer, although this was not statistically significant (per 10 cm increase in genetically predicted height, HR = 1.04, 95% CI = 0.93 to 1.17; P = .47). Observed BMI was inversely associated with breast cancer risk (per 5 kg/m2 increase, HR = 0.94, 95% CI = 0.90 to 0.98; P = .007). BMI genetic score was also inversely associated with breast cancer risk (per 5 kg/m2 increase in genetically predicted BMI, HR = 0.87, 95% CI = 0.76 to 0.98; P = .02). BMI was primarily associated with premenopausal breast cancer.
CONCLUSION: Height is associated with overall breast cancer and BMI is associated with premenopausal breast cancer in BRCA1/2 mutation carriers. Incorporating height and BMI, particularly genetic score, into risk assessment may improve cancer management.
METHODS: To understand the contribution of the X chromosome in NPC susceptibility, we conducted an X chromosome-wide association analysis on 1615 NPC patients and 1025 healthy controls of Guangdong Chinese, followed by two validation analyses in Taiwan Chinese (n = 562) and Malaysian Chinese (n = 716).
RESULTS: Firstly, the proportion of variance of X-linked loci over phenotypic variance was estimated in the discovery samples, which revealed that the phenotypic variance explained by X chromosome polymorphisms was estimated to be 12.63% (non-dosage compensation model) in males, as compared with 0.0001% in females. This suggested that the contribution of X chromosome to the genetic variance of NPC should not be neglected. Secondly, association analysis revealed that rs5927056 in DMD gene achieved X chromosome-wide association significance in the discovery sample (OR = 0.81, 95% CI 0.73-0.89, P = 1.49 × 10-5). Combined analysis revealed rs5927056 for DMD gene with suggestive significance (P = 9.44 × 10-5). Moreover, the female-specific association of rs5933886 in ARHGAP6 gene (OR = 0.62, 95%CI: 0.47-0.81, P = 4.37 × 10-4) was successfully replicated in Taiwan Chinese (P = 1.64 × 10-2). rs5933886 also showed nominally significant gender × SNP interaction in both Guangdong (P = 6.25 × 10-4) and Taiwan datasets (P = 2.99 × 10-2).
CONCLUSION: Our finding reveals new susceptibility loci at the X chromosome conferring risk of NPC and supports the value of including the X chromosome in large-scale association studies.