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Background: There is suggestive evidence that inflammation is related to ovarian cancer survival. However, more research is needed to identify inflammation-related factors that are associated with ovarian cancer survival and to determine their combined effects. Methods: This analysis used pooled data on 8,147 women with invasive epithelial ovarian cancer from the Ovarian Cancer Association Consortium. The prediagnosis inflammation-related exposures of interest included alcohol use; aspirin use; other nonsteroidal anti-inflammatory drug use; body mass index; environmental tobacco smoke exposure; history of pelvic inflammatory disease, polycystic ovarian syndrome, and endometriosis; menopausal hormone therapy use; physical inactivity; smoking status; and talc use. Using Cox proportional hazards models, the relationship between each exposure and survival was assessed in 50% of the data. A weighted inflammation-related risk score (IRRS) was developed, and its association with survival was assessed using Cox proportional hazards models in the remaining 50% of the data. Results: There was a statistically significant trend of increasing risk of death per quartile of the IRRS [HR = 1.09; 95% confidence interval (CI), 1.03–1.14]. Women in the upper quartile of the IRRS had a 31% higher death rate compared with the lowest quartile (95% CI, 1.11–1.54). Conclusions: A higher prediagnosis IRRS was associated with an increased mortality risk after an ovarian cancer diagnosis. Further investigation is warranted to evaluate whether postdiagnosis exposures are also associated with survival. Impact: Given that pre- and postdiagnosis exposures are often correlated and many are modifiable, our study results can ultimately motivate the development of behavioral recommendations to enhance survival among patients with ovarian cancer.

Objective The Measure of Ovarian Symptoms and Treatment (MOST-T35) is a patient-reported symptom index, developed and validated in the context of palliative chemotherapy for recurrent ovarian cancer (OC). We aimed to develop and validate a version suitable for surveillance of symptoms following first-line treatment for OC to support clinical follow-up. Methods In a prospective study of women following completion of first-line chemotherapy for OC, patients completed MOST-T35 every 3 months for up to 3.5 years and other patient-reported outcome measures. Construct validity (Spearman's correlations), discriminative validity (t-tests/ANOVAs assessing differences between clinically distinct groups), ability to detect clinically important symptoms (receiver operating characteristic analysis), and responsiveness (t-tests examining change) were assessed. Results Data from 726 women who received ≥3 cycles of chemotherapy, did not progress within 3 months, and completed ≥one MOST-T35 were analysed. The revised version, MOST-S26, has 26 items and 5 multi-item indexes: peripheral neuropathy (MOST-NTx), disease or treatment-related (MOST-DorT), abdominal (MOST-Abdo), and psychological symptoms (MOST-Psych), and MOST-Wellbeing, plus 9 individual items. Construct validity was confirmed (r range = 0.43–0.88). Discriminative validity confirmed expected differences between groups. MOST-NTx and MOST-Psych detected improvements in peripheral neuropathy and psychological symptoms respectively, whereas MOST-Abdo detected worsening of abdominal symptoms pre-recurrence. Conclusions This study developed and validated the MOST-S26, for surveillance of women in follow-up after first-line chemotherapy for OC. MOST-S26 reliably detected improvement in symptoms of peripheral neuropathy, psychological distress and may detect symptoms of relapse. Administration of MOST-S26 in follow-up consultations could identify concerning symptoms and facilitate timely and appropriate intervention.

Background Falls cause considerable morbidity and mortality in older people. It is unclear how vitamin D supplementation affects falls risk, particularly when taken at high doses. We sought to determine whether monthly high‐dose vitamin D supplementation reduces risk and incidence of falls. Methods We used data from the randomized, double‐blind, placebo‐controlled D‐Health Trial conducted in Australia. Between February 2014 and May 2015, 21 315 participants aged 60–84 years were randomized (1:1) to monthly doses of either 60 000 IU of colecalciferol or placebo for a maximum of 5 years. People who reported a history of osteomalacia, sarcoidosis, hyperparathyroidism, hypercalcaemia or kidney stones or who were taking >500 IU/day supplementary vitamin D were ineligible. Each year, we collected blood samples from ~450 randomly sampled participants from each trial arm and measured 25‐hydroxyvitamin D [25(OH)D]. Falls, a prespecified tertiary outcome, were ascertained using annual surveys and, for a subset of participants, 3‐month falls diaries. The primary outcome for this analysis was any fall in the month before completing an annual survey. As part of our process to maintain blinding, we used random samples of participants (surveys, n = 16 000; diaries, n = 2400), with equal numbers per group. Participants with no outcome data were excluded. Following an intention‐to‐treat approach, we analysed outcomes using logistic, ordinal and negative binomial regression. Registration: Australian New Zealand Clinical Trials Registry (ACTRN12613000743763); registered 4 July 2013. Results Mean treatment duration was 4.3 years (standard deviation [SD] = 1.4 years). Mean serum 25(OH)D concentrations during the trial were 114.8 (SD 30.3) nmol/L and 77.5 (SD 25.2) nmol/L in the vitamin D and placebo groups, respectively. Survey and diary analytic sets included 15 416 and 2200 participants, respectively; approximately half were randomized to vitamin D (surveys: 50.1%; diaries: 50.4%). Vitamin D had no effect on falling in the past month (odds ratio [OR] 1.02, 95% confidence interval [CI] 0.95–1.10). There was an interaction with body mass index (BMI) (P‐interaction = 0.001); vitamin D increased risk in participants with BMI

Background: Many loci have been found to be associated with risk of epithelial ovarian cancer (EOC). However, although there is considerable variation in progression-free survival (PFS), no loci have been found to be associated with outcome at genome-wide levels of significance. Methods: We carried out a genome-wide association study (GWAS) of PFS in 2,352 women with EOC who had undergone cytoreductive surgery and standard carboplatin/paclitaxel chemotherapy. Results: We found seven SNPs at 12q24.33 associated with PFS (P < 5 × 10–8), the top SNP being rs10794418 (HR = 1.24; 95% CI, 1.15–1.34; P = 1.47 × 10–8). High expression of a nearby gene, ULK1, is associated with shorter PFS in EOC, and with poor prognosis in other cancers. SNP rs10794418 is also associated with expression of ULK1 in ovarian tumors, with the allele associated with shorter PFS being associated with higher expression, and chromatin interactions were detected between the ULK1 promoter and associated SNPs in serous and endometrioid EOC cell lines. ULK1 knockout ovarian cancer cell lines showed significantly increased sensitivity to carboplatin in vitro. Conclusions: The locus at 12q24.33 represents one of the first genome-wide significant loci for survival for any cancer. ULK1 is a plausible candidate for the target of this association. Impact: This finding provides insight into genetic markers associated with EOC outcome and potential treatment options. See related commentary by Peres and Monteiro, p. 1604

BACKGROUND After ovarian cancer treatment, women report health issues that may be amenable to change with dietary support. The present study investigated how many women encounter a dietitian post-treatment and the factors associated with dietitian service use. METHODS We used data from a cohort of women with invasive epithelial ovarian cancer to identify socio-economic, clinical and personal factors associated with dietitian encounter after treatment completion. Data were collected at regular intervals using validated questionnaires up to 4 years post-treatment completion. Logistic regression (LR) and generalised linear mixed models (GLMM) were used to calculate adjusted odds ratios (OR) and 95% confidence intervals (CI) to assess factors associated with dietitian encounter at any time-point post-treatment (LR), as well as in the 3 months prior to a follow-up questionnaire (GLMM) to assess time-varying factors. RESULTS Of 819 women, 97 (12%) reported seeing a dietitian post-treatment. Factors associated with dietitian encounter were being overweight (ORLR = 1.7, CI = 1.1-2.8), having poorer self-rated health (ORLR = 2.5, CI = 1.2-5.2; ORGLMM = 2.3, CI = 1.2-4.4) or poorer diet quality (ORLR = 0.5, CI = 0.2-1.0) pre-diagnosis, treatment within the public health system (ORGLMM = 1.8, CI = 1.2-2.7), previous support from dietetic (ORLR = 3.1, CI = 1.8-5.4; ORGLMM = 2.8, CI = 1.8-4.2) or other allied health services (ORLR = 2.0, CI = 1.2-3.2; ORGLMM = 3.7, CI = 2.4-5.5), and having progressive disease at follow-up (ORGLMM = 2.2, CI = 1.4-3.3). Most women (86%) with ≥ 3 moderate-to-severe nutrition impact symptoms did not report a dietitian encounter post-treatment. CONCLUSIONS Few women encounter a dietitian post-treatment for ovarian cancer, including those with multiple nutrition impact symptoms. Further work is needed to engage those likely to benefit from dietitian support but less likely to seek or receive it.

Background: Combined oral contraceptive use is associated with a decreased risk of invasive epithelial ovarian cancer (ovarian cancer). There is suggestive evidence of an inverse association between progestin-only contraceptive use and ovarian cancer risk, but previous studies have been underpowered. Methods: The current study used primary data from 7,977 women with ovarian cancer and 11,820 control women in seven case–control studies from the Ovarian Cancer Association Consortium to evaluate the association between use of depot-medroxyprogesterone acetate (DMPA), an injectable progestin-only contraceptive, and ovarian cancer risk. Logistic models were fit to determine the association between ever use of DMPA and ovarian cancer risk overall and by histotype. A systematic review of the association between DMPA use and ovarian cancer risk was conducted. Results: Ever use of DMPA was associated with a 35% decreased risk of ovarian cancer overall (OR, 0.65; 95% confidence interval, 0.50–0.85). There was a statistically significant trend of decreasing risk with increasing duration of use (Ptrend < 0.001). The systematic review yielded six studies, four of which showed an inverse association and two showed increased risk. Conclusions: DMPA use appears to be associated with a decreased risk of ovarian cancer in a duration-dependent manner based on the preponderance of evidence. Further study of the mechanism through which DMPA use is associated with ovarian cancer is warranted. Impact: The results of this study are of particular interest given the rise in popularity of progestin-releasing intrauterine devices that have a substantially lower progestin dose than that in DMPA, but may have a stronger local effect.

Summary Background Observational studies have linked vitamin D deficiency with acute respiratory tract infection, but results from randomised controlled trials are heterogeneous. We analysed data from the D-Health Trial to determine whether supplementing older Australian adults, recruited from the general population, with monthly doses of vitamin D reduced the risk, duration, and severity of acute respiratory tract infections. Methods We used data from the D-Health Trial, a randomised, double-blind, placebo-controlled trial of monthly vitamin D supplementation, for which acute respiratory infection was a pre-specified trial outcome. Participants were supplemented and followed for up to 5 years. The trial was set within the Australian general population, using the Commonwealth Electoral Roll as the sampling frame, but also allowing some volunteers to participate. Participants were men and women aged 60 to 79 years (with volunteers up to age 84 years). Participants were randomly assigned to receive either vitamin D or placebo (1:1) using computer-generated permuted block randomisation, which was stratified by age, sex, and state. This was an automated process and the assignment list was not visible to study staff or investigators. Active and placebo gel capsules, identical in appearance to ensure masking, were labelled A and B and the code was not available to study staff or investigators. Participants were asked to report occurrence of acute respiratory symptoms over the previous month via annual surveys, and a subset of participants completed 8-week respiratory symptom diaries in winter. As part of our process to maintain blinding, a random sample of participants was selected for analysis of survey data and a separate sample selected for analysis of diary data. Blood samples were obtained from a random sample of participants (about 450 per group per year) and serum 25-hydroxy vitamin D (25[OH]D) concentrations were measured to monitor adherence. We used regression models to estimate odds ratios (OR), rate ratios, and rate differences. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12613000743763. Findings Between Jan 13, 2014, and May 26, 2015, 421 207 invitations were sent, 40 824 people were interested in participating, and 21 315 participants were recruited and randomised. Of the 16 000 participants selected for potential analysis of survey data, 15 373 were included in the analysis; 295 in the vitamin D group and 332 in the placebo group who were missing data for all five annual surveys were excluded from the analysis. Of the 3800 selected for potential analysis of diary data, 3070 were invited to complete the diaries because 730 had already withdrawn. 2598 people were included in the analysis; 218 people in the vitamin D group and 254 in the placebo group were missing data and were therefore excluded from the analysis. In blood samples collected from randomly sampled participants throughout the trial, the mean serum 25(OH)D concentration was 114·8 (SD 30·3) nmol/L in the vitamin D group and 77·5 (25·2) nmol/L in the placebo group. Vitamin D supplementation did not reduce the risk of acute respiratory tract infection (survey OR 0·98, 95% CI 0·93 to 1·02; diary OR 0·98, 0·83 to 1·15). Analyses of diary data showed reductions in the overall duration of symptoms and of severe symptoms, but these were small and unlikely to be clinically significant. Interpretation Monthly bolus doses of 60 000 IU of vitamin D did not reduce the overall risk of acute respiratory tract infection, but could slightly reduce the duration of symptoms in the general population. These findings suggest that routine vitamin D supplementation of a population that is largely vitamin D replete is unlikely to have a clinically relevant effect on acute respiratory tract infection. Funding National Health and Medical Research Council.

Most women with ovarian cancer have a poor prognosis, but studies have reported an association between statin use and improved survival. We investigated the potential survival benefit of statins in women with ovarian cancer using data from the Ovarian cancer Prognosis and Lifestyle study, a prospective study of Australian women aged 18 to 79 years, diagnosed with ovarian cancer from 2012 to 2015 and followed for 5 to 8 years. We obtained information from patient-completed questionnaires and medical records. We defined exposure based on prediagnosis use, as most women used statins continuously (prediagnosis and postdiagnosis) and few started using statins postdiagnosis. We measured survival from date of first treatment (surgery or neoadjuvant chemotherapy) until date of death or last follow-up. We used Cox regression to calculate hazard ratios (HR) and 95% confidence intervals (CI), adjusting for potential confounders. To reduce bias due to confounding by indication, we also applied inverse probability of treatment weighting (IPTW). Of 955 eligible women, 21% reported statin use before diagnosis. Statin users had a slightly better survival (HR = 0.90, 95% CI = 0.70-1.15) that was driven by lipophilic statin use (HR = 0.82, 95% CI = 0.61-1.11), with no association for hydrophilic statins (HR = 1.04, 95% CI = 0.72-1.49). The IPTW model weighted to all women with ovarian cancer also suggested a possible reduction in mortality associated with lipophilic statins (HR = 0.80, 95% CI = 0.54-1.21). In analyses restricted to women with hyperlipidaemia, the HRs were further from the null. Our findings are consistent with previous evidence, suggesting that lipophilic statins might improve ovarian cancer survival. Further investigation, in larger cohorts, or preferably in a randomised trial, is required.

After treatment for ovarian cancer, women want to know when they will feel 'normal' again. Our objective was to document the proportions of women with high levels of physical and emotional symptoms at the end of treatment, determine if/when they return to normal and identify groups at risk of persistent symptoms/delayed recovery.Women in the OPAL (Ovarian cancer Prognosis And Lifestyle) study who received ≥3 cycles of first-line chemotherapy and completed patient-reported outcome (PRO) questionnaires on or 6 weeks after completing chemotherapy (baseline) were included in this analysis (n = 527). PRO measures included anxiety, depression, insomnia, fatigue and wellbeing (quality-of-life) at baseline, 3, 6, 9 and 18 months post-baseline. Group-based trajectory models identified clusters of individuals who followed similar patterns. Logistic and Cox regression identified factors associated with persistent symptoms and delayed recovery, respectively.At baseline, 57% of women reported moderate-to-severe fatigue, 22% anxiety, 20% depression, 14% clinical insomnia and 45% had quality-of-life scores significantly lower than the general population. Between 50 and 75% of individual PRO scores normalised within six months, with the exception of emotional wellbeing (42%), but approximately two-in-five women still had at least one persistently poor PRO at 18 months. Women with more severe symptoms at baseline, who were younger, or had a history of anxiety/depression were more likely to have persistent symptoms or delayed recovery.Two-in-five women might never fully return to 'normal' after completing primary treatment for ovarian cancer. Those with risk factors should be triaged for early supportive interventions.

Funder: Funding details are provided in the Supplementary Material, Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally-efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, ���select and shrink for summary statistics��� (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestry; 7,669 women of East Asian ancestry; 1,072 women of African ancestry, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestry. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38(95%CI:1.28���1.48,AUC:0.588) per unit standard deviation, in women of European ancestry; 1.14(95%CI:1.08���1.19,AUC:0.538) in women of East Asian ancestry; 1.38(95%CI:1.21-1.58,AUC:0.593) in women of African ancestry; hazard ratios of 1.37(95%CI:1.30���1.44,AUC:0.592) in BRCA1 pathogenic variant carriers and 1.51(95%CI:1.36-1.67,AUC:0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.

Objectives Insomnia is common in women with ovarian cancer but there are limited prospective data on the frequency and degree of impact on patients. Our objective was to determine the prevalence of insomnia over the first three years after a diagnosis of ovarian cancer; and the relationship between insomnia and quality of life. Methods OPAL (Ovarian cancer, Prognosis And Lifestyle) is a prospective study of Australian women with epithelial ovarian cancer; 894 provided information on insomnia symptoms, medications and quality of life at three, six, nine, 12, 24 and 36 months after diagnosis. Generalised linear mixed models were used to determine the relationship between insomnia and quality of life measured at the same time and three months later. Results One-quarter of women reported symptoms consistent with clinical insomnia within three years after diagnosis and an additional 13% regularly used sleep medication (total 36% affected). Excluding 7% who reported insomnia symptoms before diagnosis, 22% reported new insomnia, which reduced to 17% when also excluding women on chemotherapy. The proportion of women with clinical (14%) or subclinical (28%) insomnia symptoms was highest at three months after diagnosis. Compared to women with no insomnia, those with clinical insomnia had significantly lower quality of life measured at the same time (8.4 points lower, 95% CI: 7.2–9.5), and three months later (5.5 points lower, 95% CI: 3.4–7.6). Conclusions Over a third of women with ovarian cancer likely experience insomnia after diagnosis; this may persist and is associated with poorer quality of life.

PURPOSE: Prior studies of menopausal hormone therapy (MHT) and ovarian cancer survival have been limited by lack of hormone regimen detail and insufficient sample sizes. To address these limitations, a comprehensive analysis of 6419 post-menopausal women with pathologically confirmed ovarian carcinoma was conducted to examine the association between MHT use prior to diagnosis and survival. METHODS: Data from 15 studies in the Ovarian Cancer Association Consortium were included. MHT use was examined by type (estrogen-only (ET) or estrogen+progestin (EPT)), duration, and recency of use relative to diagnosis. Cox proportional hazards models were used to estimate the association between hormone therapy use and survival. Logistic regression and mediation analysis was used to explore the relationship between MHT use and residual disease following debulking surgery. RESULTS: Use of ET or EPT for at least five years prior to diagnosis was associated with better ovarian cancer survival (hazard ratio, 0.80; 95% CI, 0.74 to 0.87). Among women with advanced stage, high-grade serous carcinoma, those who used MHT were less likely to have any macroscopic residual disease at the time of primary debulking surgery (p for trend

Ovarian cancer has a poor survival rate and, understandably, women often want to know whether there is anything they can do to improve their prognosis. Our goal was to investigate the association between a healthy lifestyle prediagnosis and postdiagnosis and survival in a cohort of Australian women with invasive epithelial ovarian cancer. We calculated a healthy lifestyle index (HLI) based on women's self-reported smoking status, height, weight, physical activity, diet and alcohol consumption before diagnosis (n = 678) and after completing primary treatment (n = 512). Clinical data and vital status for each woman were ascertained through medical records. Cox proportional hazards regression was conducted to calculate hazard ratios (HR) and 95% confidence interval (CI) for all-cause mortality. There was a suggestive association between a more healthy lifestyle before diagnosis and better survival (HR 0.79, 95% CI: 0.59-1.04), however, the association was stronger for lifestyle after diagnosis, with women in the highest tertile having significantly better survival than women in the lowest tertile (HR 0.61, 95% CI: 0.40-0.93; P-trend = .02). Current smoking, particularly postdiagnosis, was associated with higher mortality (HR 1.68, 95% CI: 1.17-2.42; HR 2.82, 95% CI: 1.29-6.14, for prediagnosis and postdiagnosis smoking, respectively), but women who quit after diagnosis had survival outcomes similar to nonsmokers (HR 0.99, 95% CI: 0.57-1.72). Higher physical activity after diagnosis was associated with better survival (HR 0.60, 95% CI: 0.39-0.92; P-trend = .02). A healthy lifestyle after diagnosis, in particular not smoking and being physically active, may help women with ovarian cancer improve their prognosis.

To determine the impact of chemotherapy dose reductions and dose delays on progression-free survival (PFS) in women with ovarian cancer receiving first line chemotherapy in a real world prospective cohort study.Patients with newly diagnosed epithelial ovarian (or peritoneal, fallopian tube) cancer enrolled in a national Australian prospective study, OPAL, who commenced three-weekly carboplatin (AUC 5 or 6) and paclitaxel 175 mg/m634 evaluable patients, 309 commenced CP and 325 DD-CP. Patient's age was similar in the two groups (median 62 years, range 21-79). All planned chemotherapy doses were completed by 66% vs 40% (p 0.001) in the CP and DD-CP groups respectively. There was at least one treatment delay in 28% vs 58% (p 0.001) in the CP and DD-CP groups, respectively, and 29% vs 49% (p 0.001), respectively, required at least a 15% dose reduction for either carboplatin or paclitaxel. Median PFS was 29.2 [22.9, 43.8] and 21.5 [19.4, 23.1] months in the CP and DD-CP groups respectively. Adjusting for age, histology and FIGO stage PFS did not differ between treatment groups. Median PFS was similar in patients irrespective of dose reduction or dose delay.Patients receiving DD-CP required more dose reductions and delays due to haematological toxicities and lower completion rates than CP without significant difference in median PFS between CP and DD-CP. Median PFS was similar in patients irrespective of dose reduction or dose delay.

Background Menopausal estrogen-alone therapy is a risk factor for endometrial and ovarian cancers. When a progestin is included with the estrogen daily (continuous estrogen-progestin combined therapy), there is no increased risk of endometrial cancer. However, the effect of continuous estrogen-progestin combined therapy on risk of ovarian cancer is less clear. Methods We pooled primary data from five population-based case-control studies in the Ovarian Cancer Association Consortium, including 1509 postmenopausal ovarian cancer cases and 2295 postmenopausal controls. Information on previous menopausal hormonal therapy use, as well as ovarian cancer risk factors, was collected using in-person interviews. Logistic regression was used to assess the association between use of continuous estrogen-progestin combined therapy and risk of ovarian cancer by duration and recency of use and disease histotype. Results Ever postmenopausal use of continuous estrogen-progestin combined therapy was not associated with increased risk of ovarian cancer overall (OR = 0.85, 95% CI = 0.72, 1.0). A decreased risk was observed for mucinous ovarian cancer (OR = 0.40, 95% CI = 0.18, 0.91). The other main ovarian cancer histotypes did not show an association (endometrioid: OR = 0.86, 95% CI = 0.57, 1.3, clear cell: OR = 0.68, 95% CI = 0.40, 1.2; serous: OR = 0.98, 95% CI = 0.80, 1.2). Conclusions Given that estrogen-alone therapy has been shown to be associated with increased risk of ovarian cancer, these findings are consistent with the hypothesis that adding a progestin each day ameliorates the carcinogenic effects of estrogen on the cells of origin for all histotypes of ovarian cancer.

Background Height and body mass index (BMI) have both been positively associated with melanoma risk, although findings for BMI have been less consistent than height. It remains unclear, however, whether these associations reflect causality or are due to residual confounding by environmental and lifestyle risk factors. We re-evaluated these associations using a two-sample Mendelian randomization (MR) approach. Methods We identified single nucleotide polymorphisms (SNPs) for BMI and height from separate genome-wide association study (GWAS) meta-analyses. We obtained melanoma SNPs from the most recent melanoma GWAS meta-analysis comprising 12 874 cases and 23 203 controls. We used the inverse variance-weighted estimator to derive separate causal risk estimates across all SNP instruments for BMI and height. Results Based on the combined estimate derived from 730 SNPs for BMI, we found no evidence of an association between genetically predicted BMI and melanoma [odds ratio (OR) per one standard deviation (1 SD) (4.6 kg/m2) increase in BMI 1.00, 95% confidence interval (CI): 0.91–1.11]. In contrast, we observed a positive association between genetically-predicted height (derived from a pooled estimate of 3290 SNPs) and melanoma risk [OR 1.08, 95% CI: 1.02–1.13, per 1 SD (9.27 cm) increase in height]. Sensitivity analyses using two alternative MR methods yielded similar results. Conclusions These findings provide no evidence for a causal association between higher BMI and melanoma, but support the notion that height is causally associated with melanoma risk. Mechanisms through which height influences melanoma risk remain unclear, and it remains possible that the effect could be mediated through diverse pathways including growth factors and even socioeconomic status.

Chronic inflammation has been implicated in endometrial carcinogenesis yet the impact of potentially modifiable exposures that might affect inflammation, like diet, has been understudied. This study examined the association between the dietary inflammatory index (DII®), a literature-derived tool to assess the inflammatory potential of diet, and risk of developing, and survival after a diagnosis of endometrial cancer (EC). This study included data from 1,287 women with EC and 1,435 population controls who participated in the Australian National Endometrial Cancer Study. Energy-adjusted DII (E-DII) scores were calculated from pre-diagnostic dietary intake obtained using a semi-quantitative food frequency questionnaire. Logistic regression was used to assess the association between E-DII scores and risk of EC and proportional-hazards models were used for survival analyses. Higher E-DII scores, reflecting a more pro-inflammatory diet, were not associated with risk of EC [adjusted odds ratio (OR) 0.98, 95% CI 0.77–1.24, p-trend = 0.7]. However, in stratified analyses, higher E-DII scores were associated with increased risk of EC among very obese (BMI 35 + kg/m2) women (OR 1.60, 95% CI 0.80–3.21, p-trend = 0.049, p-interaction = 0.045). After a median follow-up of 7.2 years there were 160 deaths, of which 110 (69%) were from EC. We found no association between E-DII score and survival. Greater inflammatory potential of pre-diagnostic diet was not associated with EC risk or survival. Secondary stratified analysis suggested greater inflammatory potential may be associated with EC risk in very obese women.

Background Observational studies have reported survival benefits associated with non-steroidal anti-inflammatory drugs (NSAIDs), including aspirin, and non-aspirin NSAIDs (NA-NSAIDs), especially new use post-diagnosis, in women with ovarian cancer (OC). Methods Participants were women aged 18-79 diagnosed with OC in Australia, 2012-2015. Information was gathered through self-completed 3-monthly questionnaires and prescription records. Exposure was defined as any use (NA-NSAIDs/regular-dose aspirin □1/week or daily low-dose aspirin) during the year pre-diagnosis and first year post-diagnosis. We measured overall survival from start of primary treatment (surgery/neoadjuvant chemotherapy) (pre-diagnosis use) or from 12 months after the start of therapy (post-diagnosis) until the earliest of date of death/last follow-up/5 years. Cox proportional hazards regression was used to estimate survival. We also applied inverse-probability of treatment weighting (IPTW), which balances comparison groups regarding potential confounders. Results We observed improved survival associated with pre-diagnosis use of aspirin/NA-NSAIDs ≥4 days/week (frequent-users) compared to Conclusions Our findings suggest aspirin/NA-NSAID use might improve survival in women with OC. Larger cohorts or, preferably, a randomised controlled trial could clarify these findings. Key messages Use of aspirin/NA-NSAIDs may improve OC survival.

Background Epithelial ovarian cancer (EOC) is the eighth most common cancer in women, has a five-year survival of ∼45%, and very few established modifiable risk factors. Some evidence suggests that bisphosphonates could have chemopreventive benefits, but few epidemiological studies have investigated the association between bisphosphonate use and incidence of EOC. Methods We conducted a nested case-control study using linked administrative data. We identified 9,367 women over 50 years diagnosed with EOC (cases) from 2004 to 2013, and for each case identified five controls from the Australian Medicare Enrolment database matched by age, state, area of residence, and area-level socioeconomic disadvantage. We assessed the associations between bisphosphonate use using dispensed prescription data (ever use, duration and dose) and EOC (overall, by histotype), adjusting for comorbidities and MHT use. We conducted sensitivity analyses in women with complete ascertainment of dispensing claims and for residents of one Australian state that had linked with data linked to hospital procedures, including oophorectomy. Results Our analyses show an inverse association between bisphosphonate use and risk of EOC overall (OR = 0.81, 95%CI:0.75-0.88), and for endometrioid (OR = 0.51, 95%CI:0.33-0.79) and serous (OR = 0.84, 95%CI:0.75-0.93) histotypes. There was some evidence that higher dose and duration were associated with a greater reduction in risk. Results from sensitivity analyses were not appreciably different. Conclusions Bisphosphonate use was associated with lower risk of EOC, suggesting bisphosphonates may reduce risk of ovarian cancer development. Key messages Bisphosphonates may protect against development of serous and endometrioid ovarian cancers.

Background Observational studies link vitamin D deficiency with acute respiratory tract infection (ARTI) but results from randomised controlled trials are heterogeneous. Methods We used data from The D-Health Trial (N = 21,315); ARTI was a pre-specified trial outcome. Participants were men and women aged 60 to 79 years (with volunteers aged up to 84 years), supplemented with monthly doses of 60,000 international units of vitamin D and followed for up to 5 years. Participants were asked to report occurrence of ARTI over the previous month via annual surveys, and a subset of participants completed 8-week respiratory symptom diaries in winter. We used regression models to estimate odds ratios, rate ratios and rate differences. Results Vitamin D supplementation did not reduce the risk of ARTI (survey OR 0.98, 95% CI 0.93 to 1.02; diary OR 0.98, 95% CI 0.83 to 1.15). Analyses of diary data showed that vitamin D reduced the average duration by 0.5 days (95% CI 0.2 to 0.7 days) and the average number of days with severe symptoms by 0.4 days (95% CI 0.3 to 0.6 days). Conclusions Monthly bolus doses of 60,000 IU of vitamin D did not reduce the overall risk of ARTI but slightly reduce the duration of symptoms in the general population. Key messages The reduction in the duration of symptoms suggests a potential impact of vitamin D on the immune response to infection.

Objectives Research examining survival among people with ovarian cancer following use of statins or β-blockers has been conflicting. Many studies to date have suffered from immortal time bias and/or had limited power. To address these limitations, we used time-dependent analyses to study the association between statin or β-blocker use among all people diagnosed with an epithelial ovarian cancer in British Columbia, Canada between 1997 and 2015. Methods Population-based administrative data were linked for 4207 people with ovarian cancer. Statin or β-blocker use was examined using time-dependent variables for any use, cumulative duration of use and by user-group according to whether use was initiated before or after their ovarian cancer diagnosis. Cox proportional hazards models were run to estimate the association between statin or β-blocker use and survival. Results Any postdiagnosis use of statins was associated with better ovarian cancer survival in the full cohort (adjusted hazard ratio (aHR) = 0.76, 95% CI 0.64, 0.89) and among women with serous cancers (aHR = 0.80, 95%CI 0.67–0.96). This was primarily driven by new use post-diagnosis (aHR = 0.67, 95%CI, 0.51-0.89), but there was a trend towards better survival among those who continued use from before diagnosis (aHR 0.83, 95%CI, 0.68-1.00). There was no statistically significant association between β-blocker use and survival. Conclusion Postdiagnosis statin use was associated with improved survival among people with ovarian cancer. Given the consistency of this finding in the literature, we recommend a randomized clinical trial of statin use in people with ovarian cancer.

Background Polycystic ovary syndrome (PCOS) is a complex endocrine disorder with an estimated prevalence of 4–21% in reproductive aged women. Recently, the Ovarian Cancer Association Consortium (OCAC) reported a decreased risk of invasive ovarian cancer among women with self-reported PCOS. However, given the limitations of self-reported PCOS, the validity of these observed associations remains uncertain. Therefore, we sought to use Mendelian randomization with genetic markers as a proxy for PCOS, to examine the association between PCOS and ovarian cancer. Methods Utilizing 14 single nucleotide polymorphisms (SNPs) previously associated with PCOS we assessed the association between genetically predicted PCOS and ovarian cancer risk, overall and by histotype, using summary statistics from a previously conducted genome-wide association study (GWAS) of ovarian cancer among European ancestry women within the OCAC (22 406 with invasive disease, 3103 with borderline disease and 40 941 controls). Results An inverse association was observed between genetically predicted PCOS and invasive ovarian cancer risk: odds ratio (OR)=0.92 [95% confidence interval (CI)=0.85–0.99; P = 0.03]. When results were examined by histotype, the strongest inverse association was observed between genetically predicted PCOS and endometrioid tumors (OR = 0.77; 95% CI = 0.65–0.92; P = 0.003). Adjustment for individual-level body mass index, oral contraceptive use and parity did not materially change the associations. Conclusion Our study provides evidence for a relationship between PCOS and reduced ovarian cancer risk, overall and among specific histotypes of invasive ovarian cancer. These results lend support to our previous observational study results. Future studies are needed to understand mechanisms underlying this association.

PURPOSE: Previous epidemiologic studies have shown that smoking, obesity, and physical inactivity are associated with poor survival following a diagnosis of ovarian cancer. Yet, the combined relationship of these unfavorable lifestyle factors on ovarian cancer survival has not been sufficiently investigated. METHODS: Using data pooled from 13 studies, we examined the associations between combined exposures to smoking, overweight/obesity weight, and physical inactivity and overall survival (OS) as well as progression-free survival (PFS) among women diagnosed with invasive epithelial ovarian carcinoma (N=7,022). Using age-, stage, and site-adjusted Cox proportional hazards regression models, we estimated hazard ratios (HRs) and 95% confidence intervals (CIs) associated with joint exposure to these factors. RESULTS: Combined exposure to current smoking, overweight/obesity, and physical inactivity prior to diagnosis was associated with a significantly increased risk of mortality compared to women who never smoked, had normal body mass index (BMI), and were physically active (HR=1.37; 95% CI=1.10–1.70). The association for a joint exposure to these factors exceeded that of each exposure individually. In fact, exposure to both current smoking and overweight/obesity, and current smoking and physical inactivity was also associated with increased risk of death (HR=1.28; 95 % CI=1.08–1.52, and HR=1.26; 95% CI=1.04–1.54, respectively). The associations were of a similar magnitude when former smoking was assessed in combination with the other exposures and when excessive weight was limited to obesity only. No significant associations were observed between joint exposure to any of these factors and PFS. CONCLUSIONS: Joint exposure to smoking, excessive weight, and physical inactivity may negatively impact survival of ovarian cancer patients. These results suggest the importance of examining the combined effect of lifestyle factors on ovarian cancer patients’ survival.

The International Agency for Research on Cancer first concluded that alcohol causes cancer in humans in 1988. The World Cancer Research Fund has declared that alcohol causes cancer of the oral cavity, pharynx, larynx, oesophagus (squamous cell carcinoma), female breast, colon, rectum, stomach and liver. It recommended that alcohol be avoided altogether to prevent cancer. We aimed to quantify the impact of reducing alcohol consumption on future cancer incidence in Australia. We used PREVENT 3.01 simulation modelling software to estimate the proportion of cancers that could potentially be prevented over a 25-year period under two hypothetical intervention scenarios and two latency periods (20 and 30 years). Under a scenario where alcohol consumption abruptly ceases, we estimated up to 4% of alcohol-related cancers could be avoided over a 25-year period (~49,500 cancers, depending on assumed latency). If the maximum consumption of all Australian adults was ≤20 g/day (~two Australian standard drinks), up to 2% of alcohol-related cancers could be avoided (~29,600 cancers). The maximum proportions were higher for men (6% for no alcohol consumption; 5% for ≤20 g/day) than women (3%; 1%). The proportion avoidable was highest for oesophageal squamous cell carcinoma (17% no alcohol consumption; 9% ≤20 g/day), followed by cancers of the oral cavity (12%; 5%) and pharynx (11%; 5%). The cancer sites with the highest numbers of potentially avoidable cases were colon in men (11,500; 9,900) and breast in women (14,400; 4,100). Successful interventions to reduce alcohol intake could lead to significant reductions in cancer incidence. This article is protected by copyright. All rights reserved.

Globally, 39% of the world's adult population is overweight or obese and 23% is insufficiently active. These percentages are even larger in high-income countries with 58% overweight/obese and 33% insufficiently active. Fourteen cancer types have been declared by the World Cancer Research Fund to be causally associated with being overweight or obese: oesophageal adenocarcinoma, stomach cardia, colon, rectum, liver, gallbladder, pancreas, breast, endometrium, ovary, advanced/fatal prostate, kidney, thyroid and multiple myeloma. Colon, postmenopausal breast and endometrial cancers have also been judged causally associated with physical inactivity. We aimed to quantify the proportion of cancer cases that would be potentially avoidable in Australia if the prevalence of overweight/obesity and physical inactivity in the population could be reduced. We used the simulation modelling software PREVENT 3.01 to calculate the proportion of avoidable cancers over a 25-year period under different theoretical intervention scenarios that change the prevalence of overweight/obesity and physical inactivity in the population. Between 2013 and 2037, 10-13% of overweight/obesity-related cancers in men and 7-11% in women could be avoided if overweight and obesity were eliminated in the Australian population. If everyone in the population met the Australian physical activity guidelines for cancer prevention (i.e. engaged in at least 300 min of moderate-intensity physical activity per week), an estimated 2-3% of physical inactivity-related cancers could be prevented in men (colon cancer) and 1-2% in women (colon, breast and endometrial cancers). This would translate to the prevention of up to 190,500 overweight/obesity-related cancers and 19,200 inactivity-related cancers over 25 years.

Blood lipids have been associated with the development of a range of cancers, including breast, lung and colorectal cancer. For endometrial cancer, observational studies have reported inconsistent associations between blood lipids and cancer risk. To reduce biases from unmeasured confounding, we performed a bidirectional, two-sample Mendelian randomization analysis to investigate the relationship between levels of three blood lipids (low-density lipoprotein [LDL] and high-density lipoprotein [HDL] cholesterol, and triglycerides) and endometrial cancer risk. Genetic variants associated with each of these blood lipid levels (P

Background: Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers. Methods: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data. Results: Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10−9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10−7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation. Conclusions: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis. Impact: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.

Objective A recent paper suggested all women with endometrial cancer should take statins but it is unclear whether there is sufficient evidence to justify this recommendation. Methods We identified all women diagnosed with uterine cancer in Australia between July 2003 and December 2013 (2012 in New South Wales) through the Australian Cancer Database (N = 16,501) and linked these to the national prescription database and National Death Index to identify statin use and survival outcomes to December 2015. We used Cox proportional hazards regression to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the associations between statin use and survival. Results Among the 15,703 women with endometrial cancer, pre-diagnosis statin use was not associated with survival. Endometrial cancer-specific mortality was lower among women who used statins after diagnosis (time-varying models: HR = 0.92; 95%CI 0.82–1.03) but the association was only seen among women with type 1 cancers (0.87; 0.76–1.00), for hydrophilic statins (0.84; 0.68–1.03) and for new use of statins after diagnosis (0.75; 0.59–0.95). There was a weak dose-response with increasing number of statin prescriptions. Sensitivity analyses using inverse probability of treatment weights were similar. Conclusion Women with endometrial cancer who take statins after diagnosis may have better survival than those who do not use statins. However, it is impossible to completely rule out bias, particularly reverse causation where disease status may affect statin use. We believe it is too early to recommend all women with endometrial cancer take statins, but there is sufficient evidence to justify a randomized trial.

Background: Prior studies evaluating diet quality in relation to ovarian cancer survival are sparse, and to date none have assessed diet quality or diet-quality change after diagnosis. Methods: In the prospective Ovarian cancer Prognosis And Lifestyle (OPAL) study, diet-quality scores were calculated using data from food frequency questionnaires completed pre-diagnosis (n = 650) and 12 months' post-diagnosis (n = 503). We used Cox proportional hazard models to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) for the association between diet quality and survival. Results: During the median follow-up of 4.4 years, 278 women died from ovarian cancer. There was no evidence of an association between diet quality pre- or post-diagnosis and progression-free, overall, or ovarian cancer–specific survival. No survival advantage was observed for women who had either improved their diet quality or who consumed a high-quality diet both before and 12 months after diagnosis. Conclusions: Higher pre- and post-diagnosis diet quality was not associated with better survival outcomes in this cohort of women with ovarian cancer. Impact: Diet quality is important for a range of health outcomes but may not improve survival after a diagnosis of ovarian cancer.

Previous Mendelian randomization (MR) studies on 25-hydroxyvitamin D (25(OH)D) and cancer have typically adopted a handful of variants and found no relationship between 25(OH)D and cancer; however, issues of horizontal pleiotropy cannot be reliably addressed. Using a larger set of variants associated with 25(OH)D (74 SNPs, up from 6 previously), we perform a unified MR analysis to re-evaluate the relationship between 25(OH)D and ten cancers. Our findings are broadly consistent with previous MR studies indicating no relationship, apart from ovarian cancers (OR 0.89; 95% C.I: 0.82 to 0.96 per 1 SD change in 25(OH)D concentration) and basal cell carcinoma (OR 1.16; 95% C.I.: 1.04 to 1.28). However, after adjustment for pigmentation related variables in a multivariable MR framework, the BCC findings were attenuated. Here we report that lower 25(OH)D is unlikely to be a causal risk factor for most cancers, with our study providing more precise confidence intervals than previously possible., Studies of the genetic association between vitamin D and cancer risk have typically been underpowered. Here the authors analyse this using Mendelian Randomisation with more than 70 vitamin D variants obtained from the UK Biobank and large-scale data from various consortia, confirming null associations between vitamin D and most cancers.

Accumulating evidence suggests a relationship between endometrial cancer and epithelial ovarian cancer. For example, endometrial cancer and epithelial ovarian cancer share epidemiological risk factors and molecular features observed across histotypes are held in common (e.g. serous, endometrioid and clear cell). Independent genome-wide association studies (GWAS) for endometrial cancer and epithelial ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. Using GWAS summary statistics, we explored the shared genetic etiology between endometrial cancer and epithelial ovarian cancer. Genetic correlation analysis using LD Score regression revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e. inverse-variance meta-analysis, co-localization, and M-values), and performed analyses by stratified by subtype. We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10−9). In addition, four novel regions at 7p22.2, 7q22.1, 9p12 and 11q13.3 were identified at a sub-genome wide threshold (P < 5 × 10−7). Integration with promoter-associated HiChIP chromatin loops from immortalized endometrium and epithelial ovarian cell lines, and expression quantitative trait loci (eQTL) data highlighted candidate target genes for further investigation.

Background - Regular use of aspirin has been associated with a reduced risk of cancer at several sites but the data for endometrial cancer are conflicting. Evidence regarding use of other analgesics is limited. Patients and methods - We pooled individual-level data from seven cohort and five case–control studies participating in the Epidemiology of Endometrial Cancer Consortium including 7120 women with endometrial cancer and 16 069 controls. For overall analyses, study-specific odds ratios (ORs) and 95% confidence intervals (CI) were estimated using logistic regression and combined using random-effects meta-analysis; for stratified analyses, we used mixed-effects logistic regression with study as a random effect. Results - At least weekly use of aspirin and non-aspirin nonsteroidal anti-inflammatory drugs (NSAIDs) was associated with an approximately 15% reduced risk of endometrial cancer among both overweight and obese women (OR = 0.86 [95% CI 0.76–0.98] and 0.86 [95% CI 0.76–0.97], respectively, for aspirin; 0.87 [95% CI 0.76–1.00] and 0.84 [0.74–0.96], respectively, for non-aspirin NSAIDs). There was no association among women of normal weight (body mass index 2, Pheterogeneity = 0.04 for aspirin, Pheterogeneity = 0.003 for NSAIDs). Among overweight and obese women, the inverse association with aspirin was stronger for use 2–6 times/week (OR = 0.81, 95% CI 0.68–0.96) than for daily use (0.91, 0.80–1.03), possibly because a high proportion of daily users use low-dose formulations. There was no clear association with use of acetaminophen. Conclusion - Our pooled analysis provides further evidence that use of standard-dose aspirin or other NSAIDs may reduce risk of endometrial cancer among overweight and obese women.

PurposeThe known EOC susceptibility genes account for less than 50% of the heritable risk of ovarian cancer suggesting other susceptibility genes exist. The aim of this study was to evaluate the contribution to ovarian cancer susceptibility of rare deleterious germline variants in a set of candidate genes.MethodsWe sequenced the coding region of 54 candidate genes in 6385 invasive EOC cases and 6115 controls of broad European ancestry. Genes with an increased frequency of putative deleterious variants in cases verses controls were further examined in an independent set of 14,146 EOC cases and 28,661 controls from the ovarian cancer association consortium and the UK Biobank. For each gene, we estimated the EOC risks and evaluated associations between germline variant status and clinical characteristics.ResultsThe odds ratios (OR) associated for high-grade serous ovarian cancer were 3.01 for PALB2 (95% CI 1.59 – 5.68; P = 0.00068), 1.99 for POLK (95% CI 1.15 – 3.43; P = 0.014), and 4.07 for SLX4 (95% CI 1.34-12.4; P = 0.013). Deleterious mutations in FBXO10 were associated with a reduced risk of disease (OR 0.27, 95% CI 0.07 −1.00, P=0.049). However, based on the Bayes false discovery probability, only the association for PALB2 in high-grade serous ovarian cancer is likely to represent a true positive.ConclusionsWe have found strong evidence that carriers of PALB2 deleterious mutations are at increased risk of high-grade serous ovarian cancer. Whether the magnitude of risk is sufficiently high to warrant the inclusion of PALB2 in cancer gene panels for ovarian cancer risk testing is unclear; much larger sample sizes will be needed to provide sufficiently precise estimates for clinical counselling.

Background: Previous studies suggest that smokers have lower risks of cutaneous melanoma than nonsmokers, but data from population-based prospective studies are scarce. We investigated associations between smoking and melanoma in a cohort study purpose-designed to investigate skin cancer outcomes. Methods: Participants with no prior history of melanoma (n = 38,697) completed a risk factor survey at baseline (2011). Patients were followed through linkage to the cancer registry. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between smoking (including intensity, duration, time since quitting) and melanoma using multivariate Cox proportional hazards regression, accounting for death as a competing event. Results: During a mean follow-up of 3.5 years, invasive melanomas developed in 247 participants. Compared with never smokers, former smokers (but not current smokers) had lower risks of invasive melanoma (HR 0.76; 95% CI, 0.57–1.01). Among former smokers, risks were lower with greater quantity of cigarettes smoked (HR 0.75; 95% CI, 0.56–0.98 per 10 cigarettes/day). No association was observed with duration of smoking while longer time since quitting was associated with a relative risk of melanoma that was not significantly different from the null (HR 1.18; 95% CI, 0.91–1.51, for every 10 years since quitting). Conclusions: We observed complex associations between smoking and melanoma, with some suggestion that former smokers had lower risks than never or current smokers. The apparent inverse association among former smokers may be due to residual confounding, although surveillance bias or biological effects cannot be excluded entirely. Impact: Smoking does not increase the risk of cutaneous melanoma. Cancer Epidemiol Biomarkers Prev; 27(8); 874–81. ©2018 AACR.

ObjectiveAlthough endometrial cancer (EC) is associated with relatively good survival rates overall, women diagnosed with high-risk subtypes have poor outcomes. We examined the relationship between lifestyle factors and subsequent all-cause, cancer-specific and non-cancer related survival.MethodsIn a cohort of 1359 Australian women diagnosed with incident EC between 2005 and 2007 pre-diagnostic information was collected by interview at recruitment. Clinical and survival information was abstracted from women's medical records, supplemented by linkage to the Australian National Death Index. Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause and cause-specific survival (EC death vs. non-EC death) associated with each exposure, overall and by risk group (low-grade endometrioid vs. high-grade endometrioid and non-endometrioid).ResultsAfter a median follow-up of 7.1 years, 179 (13%) women had died, with 123 (69%) deaths from EC. As expected, elevated body mass index (BMI), diabetes and the presence of other co-morbidities were associated with a significantly increased risk of all-cause and non-cancer related death. Women with diabetes had higher cancer-specific mortality rates (HR 2.09, 95% CI 1.31–3.35), particularly those who had were not obese (HR 4.13, 95% CI 2.20–7.76). The presence of ≥2 other co-morbidities (excluding diabetes) was also associated with increased risk of cancer-specific mortality (HR 3.09, 95% CI 1.21–7.89). The patterns were generally similar for women with low-grade and high-grade endometrioid/non-endometrioid EC.ConclusionOur findings demonstrate the importance of diabetes, other co-morbidities and obesity as negative predictors of mortality among women with EC but that the risks differ for cancer-specific and non-cancer related mortality.

Background: Polycystic ovary syndrome (PCOS), and one of its distinguishing characteristics, oligomenorrhea, have both been associated with ovarian cancer risk in some but not all studies. However, these associations have been rarely examined by ovarian cancer histotypes, which may explain the lack of clear associations reported in previous studies. Methods: We analyzed data from 14 case–control studies including 16,594 women with invasive ovarian cancer (n = 13,719) or borderline ovarian disease (n = 2,875) and 17,718 controls. Adjusted study-specific ORs were calculated using logistic regression and combined using random-effects meta-analysis. Pooled histotype-specific ORs were calculated using polytomous logistic regression. Results: Women reporting menstrual cycle length >35 days had decreased risk of invasive ovarian cancer compared with women reporting cycle length ≤35 days [OR = 0.70; 95% confidence interval (CI) = 0.58–0.84]. Decreased risk of invasive ovarian cancer was also observed among women who reported irregular menstrual cycles compared with women with regular cycles (OR = 0.83; 95% CI = 0.76–0.89). No significant association was observed between self-reported PCOS and invasive ovarian cancer risk (OR = 0.87; 95% CI = 0.65–1.15). There was a decreased risk of all individual invasive histotypes for women with menstrual cycle length >35 days, but no association with serous borderline tumors (Pheterogeneity = 0.006). Similarly, we observed decreased risks of most invasive histotypes among women with irregular cycles, but an increased risk of borderline serous and mucinous tumors (Pheterogeneity < 0.0001). Conclusions: Our results suggest that menstrual cycle characteristics influence ovarian cancer risk differentially based on histotype. Impact: These results highlight the importance of examining ovarian cancer risk factors associations by histologic subtype. Cancer Epidemiol Biomarkers Prev; 27(2); 174–82. ©2017 AACR.

Objective To measure association between endometrial carcinoma ER and PR status and endometrial cancer (EC) survival, accounting for inter-observer variation. Methods The intensity and proportion of tumor cell expression of ER and PR in ECs were assessed independently and semi-quantitatively by two pathologists using digital images of duplicate tumor tissue microarrays (TMAs). Cases with inconsistent initial assessment were reviewed and final scoring agreed. The association between overall and EC-specific survival and hormone receptor expression (intensity, proportion and combined) was assessed using Cox regression analysis. The C-index was used to evaluate model discrimination with addition of ER and PR status. Results Tumor ER and PR analysis was possible in 659 TMAs from 255 patients, and in 459 TMAs from 243 patients, respectively. Initial ER and PR scoring was consistent in 82% and 80% of cases, respectively. In multivariate analyses decreased ER and PR expression was associated with increased tumor-related mortality. Associations reached statistical significance for ER proportion score (P=0.05), ER intensity score (P=0.003), and PR combined score (P=0.04). Decreased expression of combined ER/PR expression was associated with poorer EC-specific survival than decreased expression of either hormone receptor alone (P=0.005). However, hormone receptor status did not significantly improve mortality prediction in individual cases. Conclusion ER and PR expression combined, using cut-points that capture variation in scoring and across cores, is significantly associated with EC-specific survival in analyses adjusting for known prognostic factors. However, at the individual level, ER and PR expression does not improve mortality prediction.

The aldehyde dehydrogenase 2 (ALDH2) polymorphism rs671 (Glu504Lys) causes ALDH2 inactivation and adverse acetaldehyde exposure among Asians, but little is known of the association between alcohol consumption and rs671 and ovarian cancer (OvCa) in Asians. We conducted a pooled analysis of Asian ancestry participants in the Ovarian Cancer Association Consortium. We included seven case-control studies and one cohort study comprising 460 invasive OvCa cases, 37 borderline mucinous OvCa and 1274 controls of Asian descent with information on recent alcohol consumption. Pooled odds ratios (OR) with 95% confidence intervals (CI) for OvCa risk associated with alcohol consumption, rs671 and their interaction were estimated using logistic regression models adjusted for potential confounders. No significant association was observed for daily alcohol intake with invasive OvCa (OR comparing any consumption to none = 0.83; 95% CI = 0.58-1.18) or with individual histotypes. A significant decreased risk was seen for carriers of one or both Lys alleles of rs671 for invasive mucinous OvCa (OR = 0.44; 95% CI = 0.20-0.97) and for invasive and borderline mucinous tumors combined (OR = 0.48; 95% CI = 0.26-0.89). No significant interaction was observed between alcohol consumption and rs671 genotypes. In conclusion, self-reported alcohol consumption at the quantities estimated was not associated with OvCa risk among Asians. Because the rs671 Lys allele causes ALDH2 inactivation leading to increased acetaldehyde exposure, the observed inverse genetic association with mucinous ovarian cancer is inferred to mean that alcohol intake may be a risk factor for this histotype. This association will require replication in a larger sample.

Background: The relationship between diet and survival after ovarian cancer diagnosis is unclear as a result of a limited number of studies and inconsistent findings. Methods: We examined the association between pre-diagnostic diet and overall survival in a population-based cohort (n=811) of Australian women diagnosed with invasive epithelial ovarian cancer between 2002 and 2005. Diet was measured by validated food frequency questionnaire. Deaths were ascertained up to 31 August 2014 via medical record review and Australian National Death Index linkage. We conducted Cox proportional hazards regression analysis, controlling for diagnosis age, tumour stage, grade and subtype, residual disease, smoking status, body mass index, physical activity, marital status, and energy intake. Results: We observed improved survival with highest compared with lowest quartile of fibre intake (hazard ratio (HR)=0.69, 95% CI: 0.53–0.90, P-trend=0.002). There was a suggestion of better survival for women with highest compared with lowest intake category of green leafy vegetables (HR=0.79, 95% CI: 0.62–0.99), fish (HR=0.74, 95% CI: 0.57–0.95), poly- to mono-unsaturated fat ratio (HR=0.76, 95% CI: 0.59–0.98), and worse survival with higher glycaemic index (HR=1.28, 95% CI: 1.01–1.65, P-trend=0.03). Conclusions: The associations we observed between healthy components of diet pre-diagnosis and ovarian cancer survival raise the possibility that dietary choices after diagnosis may improve survival.

Globally, ovarian cancer is the seventh most common cancer in women and the eighth most common cause of cancer death, with five-year survival rates below 45%. Although age-standardised rates are stable or falling in most high-income countries, they are rising in many low and middle income countries. Furthermore, with increasing life-expectancy, the number of cases diagnosed each year is increasing. To control ovarian cancer we need to understand the causes. This will allow better prediction of those at greatest risk for whom screening might be appropriate, while identification of potentially modifable causes provides an opportunity for intervention to reduce rates. In this paper we will summarise the current state of knowledge regarding the known and possible causes of epithelial ovarian cancer and discuss some of the main theories of ovarian carcinogenesis. We will also briefly review the relationship between lifestyle and survival after a diagnosis of ovarian cancer.

Contains fulltext : 169777.pdf (Publisher’s version ) (Closed access) Inflammation has been implicated in ovarian carcinogenesis. However, studies investigating the association between pelvic inflammatory disease (PID) and ovarian cancer risk are few and inconsistent. We investigated the association between PID and the risk of epithelial ovarian cancer according to tumor behavior and histotype. We pooled data from 13 case-control studies, conducted between 1989 and 2009, from the Ovarian Cancer Association Consortium (OCAC), including 9,162 women with ovarian cancers, 2,354 women with borderline tumors, and 14,736 control participants. Study-specific odds ratios were estimated and subsequently combined into a pooled odds ratio using a random-effects model. A history of PID was associated with an increased risk of borderline tumors (pooled odds ratio (pOR) = 1.32, 95% confidence interval (CI): 1.10, 1.58). Women with at least 2 episodes of PID had a 2-fold increased risk of borderline tumors (pOR = 2.14, 95% CI: 1.08, 4.24). No association was observed between PID and ovarian cancer risk overall (pOR = 0.99, 95% CI: 0.83, 1.19); however, a statistically nonsignificantly increased risk of low-grade serous tumors (pOR = 1.48, 95% CI: 0.92, 2.38) was noted. In conclusion, PID was associated with an increased risk of borderline ovarian tumors, particularly among women who had had multiple episodes of PID. Although our results indicated a histotype-specific association with PID, the association of PID with ovarian cancer risk is still somewhat uncertain and requires further investigation.

Purpose Family history of pancreatic adenocarcinoma is an established risk factor for the disease. However, associations of pancreatic cancer with other familial cancers are less clear. We analyzed data from the Queensland Pancreatic Cancer Study (QPCS), an Australian population-based case-control study, to investigate associations between family history of various cancer types and risk of pancreatic cancer. Materials and methods Our study included 591 pancreatic cancer patients and 646 controls, all of whom self-reported the histories of cancer in their first-degree relatives. We used logistic regression to estimate adjusted odds ratios (ORs) and their 95% confidence intervals (CIs). Based on our results, we conducted a systematic literature review using the Medline (OVID) database to identify articles pertaining to the association between family history of melanoma and risk of pancreatic cancer. A meta-analysis including associations in five published studies, unpublished results from a study co-author and the QPCS results was then performed using the DerSimonian and Laird random-effects model. Results Cases were more likely than controls to report a family history of pancreatic cancer (OR 2.20, 95% CI 1.16–4.19) and melanoma (OR 1.74, 95% CI 1.03–2.95), but not of breast, ovarian, respiratory, other gastrointestinal or prostate cancer. Meta-analysis of melanoma family history and pancreatic cancer risk yielded an OR of 1.22 (95% CI 1.00–1.51). Conclusions Our results yield further evidence of increased risk of pancreatic cancer in those with family histories of the disease. We also provide suggestive evidence of an association between family history of melanoma and risk of pancreatic cancer.

As a follow-up to genome-wide association analysis of common variants associated with ovarian carcinoma (cancer), our study considers seven well-known ovarian cancer risk factors and their interactions with 28 genome-wide significant common genetic variants. The interaction analyses were based on data from 9971 ovarian cancer cases and 15,566 controls from 17 case-control studies. Likelihood ratio and Wald tests for multiplicative interaction and for relative excess risk due to additive interaction were used. The top multiplicative interaction was noted between oral contraceptive pill (OCP) use (ever vs. never) and rs13255292 (p value = 3.48 × 10-4 ). Among women with the TT genotype for this variant, the odds ratio for OCP use was 0.53 (95% CI = 0.46-0.60) compared to 0.71 (95%CI = 0.66-0.77) for women with the CC genotype. When stratified by duration of OCP use, women with 1-5 years of OCP use exhibited differential protective benefit across genotypes. However, no interaction on either the multiplicative or additive scale was found to be statistically significant after multiple testing correction. The results suggest that OCP use may offer increased benefit for women who are carriers of the T allele in rs13255292. On the other hand, for women carrying the C allele in this variant, longer (5+ years) use of OCP may reduce the impact of carrying the risk allele of this SNP. Replication of this finding is needed. The study presents a comprehensive analytic framework for conducting gene-environment analysis in ovarian cancer.

Publisher's version (útgefin grein)., Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10−8), breast and ovarian cancer (rg = 0.24, p = 7 × 10−5), breast and lung cancer (rg = 0.18, p =1.5 × 10−6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10−4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis., The authors in this manuscript were working on behalf of BCAC, CCFR, CIMBA, CORECT, GECCO, OCAC, PRACTICAL, CRUK, BPC3, CAPS, PEGASUS, TRICL-ILCCO, ABCTB, APCB, BCFR, CONSIT TEAM, EMBRACE, GC-HBOC, GEMO, HEBON, kConFab/AOCS Mod SQuaD, and SWE-BRCA. The breast cancer genome-wide association analyses: BCAC is funded by Cancer Research UK [C1287/A16563, C1287/A10118], the European Union’s Horizon 2020 Research and Innovation Programme (grant numbers 634935 and 633784 for BRIDGES and B-CAST, respectively), and by the European Community’s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009-223175) (COGS). The EU Horizon 2020 Research and Innovation Programme funding source had no role in study design, data collection, data analysis, data interpretation, or writing of the report. Genotyping of the OncoArray was funded by the NIH Grant U19 CA148065, and Cancer UK Grant C1287/A16563 and the PERSPECTIVE project supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research (grant GPH-129344) and, the Ministère de l’Économie, Science et Innovation du Québec through Genome Québec and the PSR-SIIRI-701 grant, and the Quebec Breast Cancer Foundation. Funding for the iCOGS infrastructure came from: the European Community’s Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), the National Institutes of Health (CA128978), and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065, and 1U19 CA148112—the GAME-ON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, and Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. The DRIVE Consortium was funded by U19 CA148065. The Australian Breast Cancer Family Study (ABCFS) was supported by grant UM1 CA164920 from the National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. The ABCFS was also supported by the National Health and Medical Research Council of Australia, the New South Wales Cancer Council, the Victorian Health Promotion Foundation (Australia), and the Victorian Breast Cancer Research Consortium. J.L.H. is a National Health and Medical Research Council (NHMRC) Senior Principal Research Fellow. M.C.S. is a NHMRC Senior Research Fellow. The ABCS study was supported by the Dutch Cancer Society [grants NKI 2007-3839; 2009 4363]. The Australian Breast Cancer Tissue Bank (ABCTB) is generously supported by the National Health and Medical Research Council of Australia, The Cancer Institute NSW and the National Breast Cancer Foundation. The ACP study is funded by the Breast Cancer Research Trust, UK. The AHS study is supported by the intramural research program of the National Institutes of Health, the National Cancer Institute (grant number Z01-CP010119), and the National Institute of Environmental Health Sciences (grant number Z01-ES049030). The work of the BBCC was partly funded by ELAN-Fond of the University Hospital of Erlangen. The BBCS is funded by Cancer Research UK and Breast Cancer Now and acknowledges NHS funding to the NIHR Biomedical Research Centre, and the National Cancer Research Network (NCRN). The BCEES was funded by the National Health and Medical Research Council, Australia and the Cancer Council Western Australia and acknowledges funding from the National Breast Cancer Foundation (JS). For the BCFR-NY, BCFR-PA, and BCFR-UT this work was supported by grant UM1 CA164920 from the National Cancer Institute. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the BCFR. For BIGGS, ES is supported by NIHR Comprehensive Biomedical Research Centre, Guy’s & St. Thomas’ NHS Foundation Trust in partnership with King’s College London, United Kingdom. IT is supported by the Oxford Biomedical Research Centre. BOCS is supported by funds from Cancer Research UK (C8620/A8372/A15106) and the Institute of Cancer Research (UK). BOCS acknowledges NHS funding to the Royal Marsden/Institute of Cancer Research NIHR Specialist Cancer Biomedical Research Centre. The BREast Oncology GAlician Network (BREOGAN) is funded by Acción Estratégica de Salud del Instituto de Salud Carlos III FIS PI12/02125/Cofinanciado FEDER; Acción Estratégica de Salud del Instituto de Salud Carlos III FIS Intrasalud (PI13/01136); Programa Grupos Emergentes, Cancer Genetics Unit, Instituto de Investigacion Biomedica Galicia Sur. Xerencia de Xestion Integrada de Vigo-SERGAS, Instituto de Salud Carlos III, Spain; Grant 10CSA012E, Consellería de Industria Programa Sectorial de Investigación Aplicada, PEME I + D e I + D Suma del Plan Gallego de Investigación, Desarrollo e Innovación Tecnológica de la Consellería de Industria de la Xunta de Galicia, Spain; Grant EC11-192. Fomento de la Investigación Clínica Independiente, Ministerio de Sanidad, Servicios Sociales e Igualdad, Spain; and Grant FEDER-Innterconecta. Ministerio de Economia y Competitividad, Xunta de Galicia, Spain. The BSUCH study was supported by the Dietmar-Hopp Foundation, the Helmholtz Society and the German Cancer Research Center (DKFZ). The CAMA study was funded by Consejo Nacional de Ciencia y Tecnología (CONACyT) (SALUD-2002-C01-7462). Sample collection and processing was funded in part by grants from the National Cancer Institute (NCI R01CA120120 and K24CA169004). CBCS is funded by the Canadian Cancer Society (grant # 313404) and the Canadian Institutes of Health Research. CCGP is supported by funding from the University of Crete. The CECILE study was supported by Fondation de France, Institut National du Cancer (INCa), Ligue Nationale contre le Cancer, Agence Nationale de Sécurité Sanitaire, de l’Alimentation, de l’Environnement et du Travail (ANSES), Agence Nationale de la Recherche (ANR). The CGPS was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the Danish Medical Research Council, and Herlev and Gentofte Hospital. The CNIO-BCS was supported by the Instituto de Salud Carlos III, the Red Temática de Investigación Cooperativa en Cáncer and grants from the Asociación Española Contra el Cáncer and the Fondo de Investigación Sanitario (PI11/00923 and PI12/00070). COLBCCC is supported by the German Cancer Research Center (DKFZ), Heidelberg, Germany. D.T. was in part supported by a postdoctoral fellowship from the Alexander von Humboldt Foundation. The American Cancer Society funds the creation, maintenance, and updating of the CPS-II cohort. The CTS was initially supported by the California Breast Cancer Act of 1993 and the California Breast Cancer Research Fund (contract 97-10500) and is currently funded through the National Institutes of Health (R01 CA77398, UM1 CA164917, and U01 CA199277). Collection of cancer incidence data was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885. H.A.C eceives support from the Lon V Smith Foundation (LVS39420). The University of Westminster curates the DietCompLyf database funded by Against Breast Cancer Registered Charity No. 1121258 and the NCRN. The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by: Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF) (Germany); the Hellenic Health Foundation, the Stavros Niarchos Foundation (Greece); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); Health Research Fund (FIS), PI13/00061 to Granada, PI13/01162 to EPIC-Murcia, Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC (RD06/0020) (Spain); Cancer Research UK (14136 to EPIC-Norfolk; C570/A16491 and C8221/A19170 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford) (United Kingdom). The ESTHER study was supported by a grant from the Baden Württemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the German Cancer Aid (Deutsche Krebshilfe). FHRISK is funded from NIHR grant PGfAR 0707-10031. The GC-HBOC (German Consortium of Hereditary Breast and Ovarian Cancer) is supported by the German Cancer Aid (grant no 110837, coordinator: Rita K. Schmutzler, Cologne). This work was also funded by the European Regional Development Fund and Free State of Saxony, Germany (LIFE - Leipzig Research Centre for Civilization Diseases, project numbers 713-241202, 713-241202, 14505/2470, and 14575/2470). The GENICA was funded by the Federal Ministry of Education and Research (BMBF) Germany grants 01KW9975/5, 01KW9976/8, 01KW9977/0, and 01KW0114, the Robert Bosch Foundation, Stuttgart, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, the Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bochum, as well as the Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn, Germany. The GEPARSIXTO study was conducted by the German Breast Group GmbH. The GESBC was supported by the Deutsche Krebshilfe e. V. [70492] and the German Cancer Research Center (DKFZ). GLACIER was supported by Breast Cancer Now, CRUK and Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The HABCS study was supported by the Claudia von Schilling Foundation for Breast Cancer Research, by the Lower Saxonian Cancer Society, and by the Rudolf-Bartling Foundation. The HEBCS was financially supported by the Helsinki University Central Hospital Research Fund, Academy of Finland (266528), the Finnish Cancer Society, and the Sigrid Juselius Foundation. The HERPACC was supported by MEXT Kakenhi (No. 170150181 and 26253041) from the Ministry of Education, Science, Sports, Culture and Technology of Japan, by a Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control from Ministry Health, Labour and Welfare of Japan, by Health and Labour Sciences Research Grants for Research on Applying Health Technology from Ministry Health, Labour and Welfare of Japan, by National Cancer Center Research and Development Fund, and “Practical Research for Innovative Cancer Control (15ck0106177h0001)” from Japan Agency for Medical Research and development, AMED, and Cancer Bio Bank Aichi. The HMBCS was supported by a grant from the Friends of Hannover Medical School and by the Rudolf Bartling Foundation. The HUBCS was supported by a grant from the German Federal Ministry of Research and Education (RUS08/017), and by the Russian Foundation for Basic Research and the Federal Agency for Scientific Organizations for support the Bioresource collections and RFBR grants 14-04-97088, 17-29-06014, and 17-44-020498. ICICLE was supported by Breast Cancer Now, CRUK, and Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. Financial support for KARBAC was provided through the regional agreement on medical training and clinical research (A.L.F.) between Stockholm County Council and Karolinska Institutet, the Swedish Cancer Society, The Gustav V Jubilee foundation and Bert von Kantzows foundation. The KARMA study was supported by Märit and Hans Rausings Initiative Against Breast Cancer. The KBCP was financially supported by the special Government Funding (E.V.O.) of Kuopio University Hospital grants, Cancer Fund of North Savo, the Finnish Cancer Organizations, and by the strategic funding of the University of Eastern Finland. kConFab is supported by a grant from the National Breast Cancer Foundation, and previously by the National Health and Medical Research Council (NHMRC), the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. Financial support for the AOCS was provided by the United States Army Medical Research and Materiel Command [DAMD17-01-1-0729], Cancer Council Victoria, Queensland Cancer Fund, Cancer Council New South Wales, Cancer Council South Australia, The Cancer Foundation of Western Australia, Cancer Council Tasmania and the National Health and Medical Research Council of Australia (NHMRC; 400413, 400281, 199600). G.C.-T. and P.W. are supported by the NHMRC. RB was a Cancer Institute NSW Clinical Research Fellow. The KOHBRA study was partially supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), and the National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea (HI16C1127; 1020350; 1420190). LAABC is supported by grants (1RB-0287, 3PB-0102, 5PB-0018, 10PB-0098) from the California Breast Cancer Research Program. Incident breast cancer cases were collected by the USC Cancer Surveillance Program (CSP) which is supported under subcontract by the California Department of Health. The CSP is also part of the National Cancer Institute’s Division of Cancer Prevention and Control Surveillance, Epidemiology, and End Results Program, under contract number N01CN25403. L.M.B.C. is supported by the ‘Stichting tegen Kanker’. D.L. is supported by the FWO. The MABCS study is funded by the Research Centre for Genetic Engineering and Biotechnology “Georgi D. Efremov” and supported by the German Academic Exchange Program, DAAD. The MARIE study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I, 106332, 108253, 108419, 110826, 110828], the Hamburg Cancer Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402]. MBCSG is supported by grants from the Italian Association for Cancer Research (AIRC) and by funds from the Italian citizens who allocated the 5/1000 share of their tax payment in support of the Fondazione IRCCS Istituto Nazionale Tumori, according to Italian laws (INT-Institutional strategic projects “5 × 1000”). The MCBCS was supported by the NIH grants CA192393, CA116167, CA176785 an NIH Specialized Program of Research Excellence (SPORE) in Breast Cancer [CA116201], and the Breast Cancer Research Foundation and a generous gift from the David F. and Margaret T. Grohne Family Foundation. MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057 and 396414, and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. The MEC was support by NIH grants CA63464, CA54281, CA098758, CA132839, and CA164973. The MISS study is supported by funding from ERC-2011-294576 Advanced grant, Swedish Cancer Society, Swedish Research Council, Local hospital funds, Berta Kamprad Foundation, Gunnar Nilsson. The MMHS study was supported by NIH grants CA97396, CA128931, CA116201, CA140286, and CA177150. MSKCC is supported by grants from the Breast Cancer Research Foundation and Robert and Kate Niehaus Clinical Cancer Genetics Initiative. The work of MTLGEBCS was supported by the Quebec Breast Cancer Foundation, the Canadian Institutes of Health Research for the “CIHR Team in Familial Risks of Breast Cancer” program – grant # CRN-87521 and the Ministry of Economic Development, Innovation and Export Trade – grant # PSR-SIIRI-701. MYBRCA is funded by research grants from the Malaysian Ministry of Higher Education (UM.C/HlR/MOHE/06) and Cancer Research Malaysia. MYMAMMO is supported by research grants from Yayasan Sime Darby LPGA Tournament and Malaysian Ministry of Higher Education (RP046B-15HTM). The NBCS has been supported by the Research Council of Norway grant 193387/V50 (to A.-L. Børresen-Dale and V.N. Kristensen) and grant 193387/H10 (to A.-L. Børresen-Dale and V.N. Kristensen), South Eastern Norway Health Authority (grant 39346 to A.-L. Børresen-Dale and 27208 to V.N. Kristensen) and the Norwegian Cancer Society (to A.-L. Børresen-Dale and 419616 - 71248 - PR-2006-0282 to V.N. Kristensen). It has received funding from the K.G. Jebsen Centre for Breast Cancer Research (2012-2015). The NBHS was supported by NIH grant R01CA100374. Biological sample preparation was conducted the Survey and Biospecimen Shared Resource, which is supported by P30 CA68485. The Northern California Breast Cancer Family Registry (NC-BCFR) and Ontario Familial Breast Cancer Registry (OFBCR) were supported by grant UM1 CA164920 from the National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. The Carolina Breast Cancer Study was funded by Komen Foundation, the National Cancer Institute (P50 CA058223, U54 CA156733, and U01 CA179715), and the North Carolina University Cancer Research Fund. The NGOBCS was supported by Grants-in-Aid for the Third Term Comprehensive Ten-Year Strategy for Cancer Control from the Ministry of Health, Labor and Welfare of Japan, and for Scientific Research on Priority Areas, 17015049 and for Scientific Research on Innovative Areas, 221S0001, from the Ministry of Education, Culture, Sports, Science, and Technology of Japan. The NHS was supported by NIH grants P01 CA87969, UM1 CA186107, and U19 CA148065. The NHS2 was supported by NIH grants UM1 CA176726 and U19 CA148065. The OBCS was supported by research grants from the Finnish Cancer Foundation, the Academy of Finland (grant number 250083, 122715 and Center of Excellence grant number 251314), the Finnish Cancer Foundation, the Sigrid Juselius Foundation, the University of Oulu, the University of Oulu Support Foundation, and the special Governmental EVO funds for Oulu University Hospital-based research activities. The ORIGO study was supported by the Dutch Cancer Society (RUL 1997-1505) and the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL CP16). The PBCS was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. Genotyping for PLCO was supported by the Intramural Research Program of the National Institutes of Health, NCI, Division of Cancer Epidemiology and Genetics. The PLCO is supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics and supported by contracts from the Division of Cancer Prevention, National Cancer Institute, National Institutes of Health. The POSH study is funded by Cancer Research UK (grants C1275/A11699, C1275/C22524, C1275/A19187, C1275/A15956, and Breast Cancer Campaign 2010PR62, 2013PR044. PROCAS is funded from NIHR grant PGfAR 0707-10031. The RBCS was funded by the Dutch Cancer Society (DDHK 2004-3124, DDHK 2009-4318). The SASBAC study was supported by funding from the Agency for Science, Technology and Research of Singapore (A*STAR), the US National Institute of Health (NIH) and the Susan G. Komen Breast Cancer Foundation. The SBCGS was supported primarily by NIH grants R01CA64277, R01CA148667, UMCA182910, and R37CA70867. Biological sample preparation was conducted the Survey and Biospecimen Shared Resource, which is supported by P30 CA68485. The scientific development and funding of this project were, in part, supported by the Genetic Associations and Mechanisms in Oncology (GAME-ON) Network U19 CA148065. The SBCS was supported by Sheffield Experimental Cancer Medicine Centre and Breast Cancer Now Tissue Bank. The SCCS is supported by a grant from the National Institutes of Health (R01 CA092447). Data on SCCS cancer cases used in this publication were provided by the Alabama Statewide Cancer Registry; Kentucky Cancer Registry, Lexington, KY; Tennessee Department of Health, Office of Cancer Surveillance; Florida Cancer Data System; North Carolina Central Cancer Registry, North Carolina Division of Public Health; Georgia Comprehensive Cancer Registry; Louisiana Tumor Registry; Mississippi Cancer Registry; South Carolina Central Cancer Registry; Virginia Department of Health, Virginia Cancer Registry; Arkansas Department of Health, Cancer Registry, 4815 W. Markham, Little Rock, AR 72205. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries, Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the National Program of Cancer Registries (NPCR) of the Centers for Disease Control and Prevention (CDC). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. SEARCH is funded by Cancer Research UK [C490/A10124, C490/A16561] and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. The University of Cambridge has received salary support for PDPP from the NHS in the East of England through the Clinical Academic Reserve. SEBCS was supported by the BRL (Basic Research Laboratory) program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (2012-0000347). SGBCC is funded by the NUS start-up Grant, National University Cancer Institute Singapore (NCIS) Centre Grant and the NMRC Clinician Scientist Award. Additional controls were recruited by the Singapore Consortium of Cohort Studies-Multi-ethnic cohort (SCCS-MEC), which was funded by the Biomedical Research Council, grant number: 05/1/21/19/425. The Sister Study (SISTER) is supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01-ES044005 and Z01-ES049033). The Two Sister Study (2SISTER) was supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01-ES044005 and Z01-ES102245), and, also by a grant from Susan G. Komen for the Cure, grant FAS0703856. SKKDKFZS is supported by the DKFZ. The SMC is funded by the Swedish Cancer Foundation. The SZBCS was supported by Grant PBZ_KBN_122/P05/2004. The TBCS was funded by The National Cancer Institute, Thailand. The TNBCC was supported by a Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA116201), a grant from the Breast Cancer Research Foundation, a generous gift from the David F. and Margaret T. Grohne Family Foundation. The TWBCS is supported by the Taiwan Biobank project of the Institute of Biomedical Sciences, Academia Sinica, Taiwan. The UCIBCS component of this research was supported by the NIH [CA58860, CA92044] and the Lon V Smith Foundation [LVS39420]. The UKBGS is funded by Breast Cancer Now and the Institute of Cancer Research (ICR), London. ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. The UKOPS study was funded by The Eve Appeal (The Oak Foundation) and supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. The US3SS study was supported by Massachusetts (K.M.E., R01CA47305), Wisconsin (P.A.N., R01 CA47147) and New Hampshire (L.T.-E., R01CA69664) centers, and Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. The USRT Study was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. The WAABCS study was supported by grants from the National Cancer Institute of the National Institutes of Health (R01 CA89085 and P50 CA125183 and the D43 TW009112 grant), Susan G. Komen (SAC110026), the Dr. Ralph and Marian Falk Medical Research Trust, and the Avon Foundation for Women. The WHI program is funded by the National Heart, Lung, and Blood Institute, the US National Institutes of Health and the US Department of Health and Human Services (HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C). This work was also funded by NCI U19 CA148065-01. D.G.E. is supported by the all Manchester NIHR Biomedical research center Manchester (IS-BRC-1215-20007). HUNBOCS, Hungarian Breast and Ovarian Cancer Study was supported by Hungarian Research Grant KTIA-OTKA CK-80745, NKFI_OTKA K-112228. C.I. received support from the Nontherapeutic Subject Registry Shared Resource at Georgetown University (NIH/NCI P30-CA-51008) and the Jess and Mildred Fisher Center for Hereditary Cancer and Clinical Genomics Research. K.M. is supported by CRUK C18281/A19169. City of Hope Clinical Cancer Community Research Network and the Hereditary Cancer Research Registry, supported in part by Award Number RC4CA153828 (PI: J Weitzel) from the National Cancer Institute and the office of the Directory, National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The colorectal cancer genome-wide association analyses: Colorectal Transdisciplinary Study (CORECT): The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the CORECT Consortium, nor does mention of trade names, commercial products or organizations imply endorsement by the US Government or the CORECT Consortium. We are incredibly grateful for the contributions of Dr. Brian Henderson and Dr. Roger Green over the course of this study and acknowledge them in memoriam. We are also grateful for support from Daniel and Maryann Fong. ColoCare: we thank the many investigators and staff who made this research possible in ColoCare Seattle and ColoCare Heidelberg. ColoCare was initiated and developed at the Fred Hutchinson Cancer Research Center by Drs. Ulrich and Grady. CCFR: the Colon CFR graciously thanks the generous contributions of their study participants, dedication of study staff, and financial support from the U.S. National Cancer Institute, without which this important registry would not exist. Galeon: GALEON wishes to thank the Department of Surgery of University Hospital of Santiago (CHUS), Sara Miranda Ponte, Carmen M Redondo, and the staff of the Department of Pathology and Biobank of CHUS, Instituto de Investigación Sanitaria de Santiago (IDIS), Instituto de Investigación Sanitaria Galicia Sur (IISGS), SERGAS, Vigo, Spain, and Programa Grupos Emergentes, Cancer Genetics Unit, CHUVI Vigo Hospital, Instituto de Salud Carlos III, Spain. MCCS: this study was made possible by the contribution of many people, including the original investigators and the diligent team who recruited participants and continue to work on follow-up. We would also like to express our gratitude to the many thousands of Melbourne residents who took part in the study and provided blood samples. SEARCH: We acknowledge the contributions of Mitul Shah, Val Rhenius, Sue Irvine, Craig Luccarini, Patricia Harrington, Don Conroy, Rebecca Mayes, and Caroline Baynes. The Swedish low-risk colorectal cancer study: we thank Berith Wejderot and the Swedish low-risk colorectal cancer study group. Genetics & Epidemiology of Colorectal Cancer Consortium (GECCO): we thank all those at the GECCO Coordinating Center for helping bring together the data and people that made this project possible. ASTERISK: we are very grateful to Dr. Bruno Buecher without whom this project would not have existed. We also thank all those who agreed to participate in this study, including the patients and the healthy control persons, as well as all the physicians, technicians and students. DACHS: we thank all participants and cooperating clinicians, and Ute Handte-Daub, Renate Hettler-Jensen, Utz Benscheid, Muhabbet Celik, and Ursula Eilber for excellent technical assistance. HPFS, NHS and PHS: we acknowledge Patrice Soule and Hardeep Ranu of the Dana-Farber Harvard Cancer Center High-Throughput Polymorphism Core who assisted in the genotyping for NHS, HPFS, and PHS under the supervision of Dr. Immaculata Devivo and Dr. David Hunter, Qin (Carolyn) Guo, and Lixue Zhu who assisted in programming for NHS and HPFS and Haiyan Zhang who assisted in programming for the PHS. We thank the participants and staff of the Nurses’ Health Study and the Health Professionals Follow-Up Study, for their valuable contributions as well as the following state cancer registries for their help: A.L., A.Z., A.R., C.A., C.O., C.T., D.E., F.L., G.A., I.D., I.L., I.N., I.A., K.Y., L.A., M.E., M.D., M.A., M.I., N.E., N.H., N.J., N.Y., N.C., N.D., O.H., O.K., O.R., P.A., R.I., S.C., T.N., T.X., V.A., W.A., W.Y. In addition, this study was approved by the Connecticut Department of Public Health (DPH) Human Investigations Committee. Certain data used in this publication were obtained from the DPH. We assume full responsibility for analyses and interpretation of these data. PLCO: we thank Drs. Christine Berg and Philip Prorok, Division of Cancer Prevention, National Cancer Institute, the Screening Center investigators and staff or the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial, Mr. Tom Riley and staff, Information Management Services Inc., Ms. Barbara O’Brien and staff, Westat Inc. and Drs. Bill Kopp, Wen Shao and staff, SAIC-Frederick. Most importantly, we acknowledge the study participants for their contributions for making this study possible. The statements contained herein are solely those of the authors and do not represent or imply concurrence or endorsement by NCI. PMH: we thank the study participants and staff of the Hormones and Colon Cancer study. WHI: we thank the WHI investigators and staff for their dedication, and the study participants for making the program possible. A full listing of WHI investigators can be found at https://cleo.whi.org/researchers/Documents%20%20Write%20a%20Paper/WHI%20Investigator%20Short20List.pdf. CORECT: The CORECT Study was supported by the National Cancer Institute, National Institutes of Health (NCI/NIH), U.S. Department of Health and Human Services (grant numbers U19 CA148107, R01 CA81488, P30 CA014089, R01 CA197350; P01 CA196569; and R01 CA201407) and National Institutes of Environmental Health Sciences, National Institutes of Health (grant number T32 ES013678). The ATBC Study was supported by the US Public Health Service contracts (N01-CN-45165, N01-RC-45035, N01-RC-37004, and HHSN261201000006C) from the National Cancer Institute. The Cancer Prevention Study-II Nutrition Cohort is funded by the American Cancer Society. ColoCare: This work was supported by the National Institutes of Health (grant numbers R01 CA189184, U01 CA206110, 2P30CA015704-40 (Gilliland)), the Matthias Lackas-Foundation, the German Consortium for Translational Cancer Research, and the EU TRANSCAN initiative. Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO): funding for GECCO was provided by the National Cancer Institute, National Institutes of Health, U.S. Department of Health and Human Services (grant numbers U01 CA137088, R01 CA059045, and U01 CA164930). This research was funded in part through the NIH/NCI Cancer Center Support Grant P30 CA015704. The Colon Cancer Family Registry (CFR) Illumina GWAS was supported by funding from the National Cancer Institute, National Institutes of Health (grant numbers U01 CA122839, R01 CA143247). The Colon CFR/CORECT Affymetrix Axiom GWAS and OncoArray GWAS were supported by funding from National Cancer Institute, National Institutes of Health (grant number U19 CA148107 to S.G.). The Colon CFR participant recruitment and collection of data and biospecimens used in this study were supported by the National Cancer Institute, National Institutes of Health (grant number UM1 CA167551) and through cooperative agreements with the following Colon CFR centers: Australasian Colorectal Cancer Family Registry (NCI/NIH grant numbers U01 CA074778 and U01/U24 CA097735), USC Consortium Colorectal Cancer Family Registry (NCI/NIH grant numbers U01/U24 CA074799), Mayo Clinic Cooperative Family Registry for Colon Cancer Studies (NCI/NIH grant number U01/U24 CA074800), Ontario Familial Colorectal Cancer Registry (NCI/NIH grant number U01/U24 CA074783), Seattle Colorectal Cancer Family Registry (NCI/NIH grant number U01/U24 CA074794), and University of Hawaii Colorectal Cancer Family Registry (NCI/NIH grant number U01/U24 CA074806), Additional support for case ascertainment was provided from the Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer Institute to Fred Hutchinson Cancer Research Center (Control Nos. N01-CN-67009 and N01-PC-35142, and Contract No. HHSN2612013000121), the Hawai’i Department of Health (Control Nos. N01-PC-67001 and N01-PC-35137, and Contract No. HHSN26120100037C, and the California Department of Public Health (contracts HHSN261201000035C awarded to the University of Southern California, and the following state cancer registries: A.Z., C.O., M.N., N.C., N.H., and by the Victoria Cancer Registry and Ontario Cancer Registry. ESTHER/VERDI was supported by grants from the Baden–Württemberg Ministry of Science, Research and Arts and the German Cancer Aid. MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. GALEON: FIS Intrasalud (PI13/01136). The MCCS was further supported by Australian NHMRC grants 509348, 209057, 251553, and 504711 and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. MSKCC: the work at Sloan Kettering in New York was supported by the Robert and Kate Niehaus Center for Inherited Cancer Genomics and the Romeo Milio Foundation. Moffitt: This work was supported by funding from the National Institutes of Health (grant numbers R01 CA189184, P30 CA076292), Florida Department of Health Bankhead-Coley Grant 09BN-13, and the University of South Florida Oehler Foundation. Moffitt contributions were supported in part by the Total Cancer Care Initiative, Collaborative Data Services Core, and Tissue Core at the H. Lee Moffitt Cancer Center & Research Institute, a National Cancer Institute-designated Comprehensive Cancer Center (grant number P30 CA076292). SEARCH: Cancer Research UK (C490/A16561). The Spanish study was supported by Instituto de Salud Carlos III, co-funded by FEDER funds –a way to build Europe– (grants PI14-613 and PI09-1286), Catalan Government DURSI (grant 2014SGR647), and Junta de Castilla y León (grant LE22A10-2). The Swedish Low-risk Colorectal Cancer Study: the study was supported by grants from the Swedish research council; K2015-55 × -22674-01-4, K2008-55 × -20157-03-3, K2006-72 × -20157-01-2 and the Stockholm County Council (ALF project). CIDR genotyping for the Oncoarray was conducted under contract 268201200008I (to K.D.), through grant 101HG007491-01 (to C.I.A.). The Norris Cotton Cancer Center - P30CA023108, The Quantitative Biology Research Institute - P20GM103534, and the Coordinating Center for Screen Detected Lesions - U01CA196386 also supported efforts of C.I.A. This work was also supported by the National Cancer Institute (grant numbers U01 CA1817700, R01 CA144040). ASTERISK: a Hospital Clinical Research Program (PHRC) and supported by the Regional Council of Pays de la Loire, the Groupement des Entreprises Françaises dans la Lutte contre le Cancer (GEFLUC), the Association Anne de Bretagne Génétique and the Ligue Régionale Contre le Cancer (LRCC). COLO2&3: National Institutes of Health (grant number R01 CA060987). DACHS: This work was supported by the German Research Council (BR 1704/6-1, BR 1704/6-3, BR 1704/6-4, CH 117/1-1, HO 5117/2-1, HE 5998/2-1, KL 2354/3-1, RO 2270/8-1, and BR 1704/17-1), the Interdisciplinary Research Program of the National Center for Tumor Diseases (NCT), Germany, and the German Federal Ministry of Education and Research (01KH0404, 01ER0814, 01ER0815, 01ER1505A, and 01ER1505B). DALS: National Institutes of Health (grant number R01 CA048998 to M.L.S). HPFS is supported by National Institutes of Health (grant numbers P01 CA055075, UM1 CA167552, R01 137178, and P50 CA127003), NHS by the National Institutes of Health (grant numbers UM1 CA186107, R01 CA137178, P01 CA087969, and P50 CA127003), NHSII by the National Institutes of Health (grant numbers R01 050385CA and UM1 CA176726), and PHS by the National Institutes of Health (grant number R01 CA042182). MEC: National Institutes of Health (grant numbers R37 CA054281, P01 CA033619, and R01 CA063464). OFCCR: National Institutes of Health, through funding allocated to the Ontario Registry for Studies of Familial Colorectal Cancer (grant number U01 CA074783); see Colon CFR section above. As subset of ARCTIC, OFCCR is supported by a GL2 grant from the Ontario Research Fund, the Canadian Institutes of Health Research, and the Cancer Risk Evaluation (CaRE) Program grant from the Canadian Cancer Society Research Institute. T.J.H. and B.W.Z. are recipients of Senior Investigator Awards from the Ontario Institute for Cancer Research, through generous support from the Ontario Ministry of Research and Innovation. PLCO: Intramural Research Program of the Division of Cancer Epidemiology and Genetics and supported by contracts from the Division of Cancer Prevention, National Cancer Institute, NIH, DHHS. Additionally, a subset of control samples was genotyped as part of the Cancer Genetic Markers of Susceptibility (CGEMS) Prostate Cancer GWAS, Colon CGEMS pancreatic cancer scan (PanScan), and the Lung Cancer and Smoking study. The prostate and PanScan study datasets were accessed with appropriate approval through the dbGaP online resource (http://cgems.cancer.gov/data/) accession numbers phs000207.v1.p1 and phs000206.v3.p2, respectively, and the lung datasets were accessed from the dbGaP website (http://www.ncbi.nlm.nih.gov/gap) through accession number phs000093.v2.p2. Funding for the Lung Cancer and Smoking study was provided by National Institutes of Health (NIH), Genes, Environment and Health Initiative (GEI) Z01 CP 010200, NIH U01 HG004446, and NIH GEI U01 HG 004438. For the lung study, the GENEVA Coordinating Center provided assistance with genotype cleaning and general study coordination, 23 and the Johns Hopkins University Center for Inherited Disease Research conducted genotyping. PMH: National Institutes of Health (grant number R01 CA076366). VITAL: National Institutes of Health (grant number K05-CA154337). WHI: The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C. The head and neck cancer genome-wide association analyses: The study was supported by NIH/NCI: P50 CA097190, and P30 CA047904, Canadian Cancer Society Research Institute (no. 020214) and Cancer Care Ontario Research Chair to R.H. The Princess Margaret Hospital Head and Neck Cancer Translational Research Program is funded by the Wharton family, Joe’s Team, Gordon Tozer, Bruce Galloway and the Elia family. Geoffrey Liu was supported by the Posluns Family Fund and the Lusi Wong Family Fund at the Princess Margaret Foundation, and the Alan B. Brown Chair in Molecular Genomics. This publication presents data from Head and Neck 5000 (H&N5000). H&N5000 was a component of independent research funded by the UK National Institute for Health Research (NIHR) under its Programme Grants for Applied Research scheme (RP-PG-0707-10034). The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. Human papillomavirus (HPV) in H&N5000 serology was supported by a Cancer Research UK Programme Grant, the Integrative Cancer Epidemiology Programme (grant number: C18281/A19169). National Cancer Institute (R01-CA90731); National Institute of Environmental Health Sciences (P30ES10126). The authors thank all the members of the GENCAPO team/The Head and Neck Genome Project (GENCAPO) was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (Grant numbers 04/12054-9 and 10/51168-0). CPS-II recruitment and maintenance is supported with intramural research funding from the American Cancer Society. Genotyping performed at the Center for Inherited Disease Research (CIDR) was funded through the U.S. National Institute of Dental and Craniofacial Research (NIDCR) grant 1 × 01HG007780-0. The University of Pittsburgh head and neck cancer case-control study is supported by National Institutes of Health grants P50 CA097190 and P30 CA047904. The Carolina Head and Neck Cancer Study (CHANCE) was supported by the National Cancer Institute (R01-CA90731). The Head and Neck Genome Project (GENCAPO) was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (Grant numbers 04/12054-9 and 10/51168-0). The authors thank all the members of the GENCAPO team. The HN5000 study was funded by the National Institute for Health Research (NIHR) under its Programme Grants for Applied Research scheme (RP-PG-0707-10034), the views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. The Toronto study was funded by the Canadian Cancer Society Research Institute (020214) and the National Cancer Institute (U19-CA148127) and the Cancer Care Ontario Research Chair. The alcohol-related cancers and genetic susceptibility study in Europe (ARCAGE) was funded by the European Commission’s 5th Framework Program (QLK1-2001-00182), the Italian Association for Cancer Research, Compagnia di San Paolo/FIRMS, Region Piemonte, and Padova University (CPDA057222). The Rome Study was supported by the Associazione Italiana per la Ricerca sul Cancro (AIRC) IG 2011 10491 and IG2013 14220 to S.B., and Fondazione Veronesi to S.B. The IARC Latin American study was funded by the European Commission INCO-DC programme (IC18-CT97-0222), with additional funding from Fondo para la Investigacion Cientifica y Tecnologica (Argentina) and the Fundação de Amparo à Pesquisa do Estado de São Paulo (01/01768-2). We thank Leticia Fernandez, Instituto Nacional de Oncologia y Radiobiologia, La Habana, Cuba and Sergio and Rosalina Koifman, for their efforts with the IARC Latin America study São Paulo center. The IARC Central Europe study was supported by European Commission’s INCO-COPERNICUS Program (IC15- CT98-0332), NIH/National Cancer Institute grant CA92039, and the World Cancer Research Foundation grant WCRF 99A28. The IARC Oral Cancer Multicenter study was funded by grant S06 96 202489 05F02 from Europe against Cancer; grants FIS 97/0024, FIS 97/0662, and BAE 01/5013 from Fondo de Investigaciones Sanitarias, Spain; the UICC Yamagiwa-Yoshida Memorial International Cancer Study; the National Cancer Institute of Canada; Associazione Italiana per la Ricerca sul Cancro; and the Pan-American Health Organization. Coordination of the EPIC study is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The lung cancer genome-wide association analyses: Transdisciplinary Research for Cancer in Lung (TRICL) of the International Lung Cancer Consortium (ILCCO) was supported by (U19-CA148127, CA148127S1, U19CA203654, and Cancer Prevention Research Institute of Texas RR170048). The ILCCO data harmonization is supported by Cancer Care Ontario Research Chair of Population Studies to R. H. and Lunenfeld-Tanenbaum Research Institute, Sinai Health System. The TRICL-ILCCO OncoArray was supported by in-kind genotyping by the Centre for Inherited Disease Research (26820120008i-0-26800068-1). The CAPUA study was supported by FIS-FEDER/Spain grant numbers FIS-01/310, FIS-PI03-0365, and FIS-07-BI060604, FICYT/Asturias grant numbers FICYT PB02-67 and FICYT IB09-133, and the University Institute of Oncology (IUOPA), of the University of Oviedo and the Ciber de Epidemiologia y Salud Pública. CIBERESP, SPAIN. The work performed in the CARET study was supported by the National Institute of Health/National Cancer Institute: UM1 CA167462 (PI: Goodman), National Institute of Health UO1-CA6367307 (PIs Omen, Goodman); National Institute of Health R01 CA111703 (PI Chen), National Institute of Health 5R01 CA151989-01A1(PI Doherty). The Liverpool Lung project is supported by the Roy Castle Lung Cancer Foundation. The Harvard Lung Cancer Study was supported by the NIH (National Cancer Institute) grants CA092824, CA090578, CA074386. The Multi-ethnic Cohort Study was partially supported by NIH Grants CA164973, CA033619, CA63464, and CA148127. The work performed in MSH-PMH study was supported by The Canadian Cancer Society Research Institute (020214), Ontario Institute of Cancer and Cancer Care Ontario Chair Award to R.J.H. and G.L. and the Alan Brown Chair and Lusi Wong Programs at the Princess Margaret Hospital Foundation. NJLCS was funded by the State Key Program of National Natural Science of China (81230067), the National Key Basic Research Program Grant (2011CB503805), the Major Program of the National Natural Science Foundation of China (81390543). The Norway study was supported by Norwegian Cancer Society, Norwegian Research Council. The Shanghai Cohort Study (SCS) was supported by National Institutes of Health R01 CA144034 (PI: Yuan) and UM1 CA182876 (PI: Yuan). The Singapore Chinese Health Study (SCHS) was supported by National Institutes of Health R01 CA144034 (PI: Yuan) and UM1 CA182876 (PI: Yuan). The work in TLC study has been supported in part the James & Esther King Biomedical Research Program (09KN-15), National Institutes of Health Specialized Programs of Research Excellence (SPORE) Grant (P50 CA119997), and by a Cancer Center Support Grant (CCSG) at the H. Lee Moffitt Cancer Center and Research Institute, an NCI designated Comprehensive Cancer Center (grant number P30-CA76292). The Vanderbilt Lung Cancer Study—BioVU dataset used for the analyses described was obtained from Vanderbilt University Medical Center’s BioVU, which is supported by institutional funding, the 1S10RR025141-01 instrumentation award, and by the Vanderbilt CTSA grant UL1TR000445 from NCATS/NIH. Dr. Aldrich was supported by NIH/National Cancer Institute K07CA172294 (PI: Aldrich) and Dr. Bush was supported by NHGRI/NIH U01HG004798 (PI: Crawford). The Copenhagen General Population Study (CGPS) was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the Danish Medical Research Council and Herlev Hospital. The NELCS study: Grant Number P20RR018787 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). The Kentucky Lung Cancer Research Initiative was supported by the Department of Defense [Congressionally Directed Medical Research Program, U.S. Army Medical Research and Materiel Command Program] under award number: 10153006 (W81XWH-11-1-0781). Views and opinions of, and endorsements by the author(s) do not reflect those of the US Army or the Department of Defense. This research was also supported by unrestricted infrastructure funds from the UK Center for Clinical and Translational Science, NIH grant UL1TR000117 and Markey Cancer Center NCI Cancer Center Support Grant (P30 CA177558) Shared Resource Facilities: Cancer Research Informatics, Biospecimen and Tissue Procurement, and Biostatistics and Bioinformatics. The M.D. Anderson Cancer Center study was supported in part by grants from the NIH (P50 CA070907, R01 CA176568) (to X.W.), Cancer Prevention & Research Institute of Texas (RP130502) (to X.W.), and The University of Texas MD Anderson Cancer Center institutional support for the Center for Translational and Public Health Genomics. The deCODE study of smoking and nicotine dependence was funded in part by a grant from NIDA (R01- DA017932). The study in Lodz center was partially funded by Nofer Institute of Occupational Medicine, under task NIOM 10.13: Predictors of mortality from non-small cell lung cancer—field study. Genetic sharing analysis was funded by NIH grant CA194393. The research undertaken by M.D.T., L.V.W., and M.S.A. was partly funded by the National Institute for Health Research (NIHR). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. M.D.T. holds a Medical Research Council Senior Clinical Fellowship (G0902313). The work to assemble the FTND GWAS meta-analysis was supported by the National Institutes of Health (NIH), National Institute on Drug Abuse (NIDA) grant number R01 DA035825 (Principal Investigator [PI]: DBH). The study populations included COGEND (dbGaP phs000092.v1.p1 and phs000404.v1.p1), COPDGene (dbGaP phs000179.v3.p2), deCODE Genetics, EAGLE (dbGaP phs000093.vs.p2), and SAGE. dbGaP phs000092.v1.p1). See Hancock et al. Transl Psychiatry 2015 (PMCID: PMC4930126) for the full listing of funding sources and other acknowledgments. The Resource for the Study of Lung Cancer Epidemiology in North Trent (ReSoLuCENT)study was funded by the Sheffield Hospitals Charity, Sheffield Experimental Cancer Medicine Centre and Weston Park Hospital Cancer Charity. The ovarian cancer genome-wide association analysis: The Ovarian Cancer Association Consortium (OCAC) is supported by a grant from the Ovarian Cancer Research Fund thanks to donations by the family and friends of Kathryn Sladek Smith (PPD/RPCI.07). The scientific development and funding for this project were in part supported by the US National Cancer Institute GAME-ON Post-GWAS Initiative (U19-CA148112). This study made use of data generated by the Wellcome Trust Case Control consortium that was funded by the Wellcome Trust under award 076113. The results published here are in part based upon data generated by The Cancer Genome Atlas Pilot Project established by the National Cancer Institute and National Human Genome Research Institute (dbGap accession number phs000178.v8.p7). The OCAC OncoArray genotyping project was funded through grants from the U.S. National Institutes of Health (CA1X01HG007491-01 (C.I.A.), U19-CA148112 (T.A.S.), R01-CA149429 (C.M.P.), and R01-CA058598 (M.T.G.); Canadian Institutes of Health Research (MOP-86727 (L.E.K.) and the Ovarian Cancer Research Fund (A.B.). The COGS project was funded through a European Commission’s Seventh Framework Programme grant (agreement number 223175 - HEALTH-F2-2009-223175) and through a grant from the U.S. National Institutes of Health (R01-CA122443 (E.L.G)). Funding for individual studies: AAS: National Institutes of Health (RO1-CA142081); AOV: The Canadian Institutes for Health Research (MOP-86727); AUS: The Australian Ovarian Cancer Study Group was supported by the U.S. Army Medical Research and Materiel Command (DAMD17-01-1-0729), National Health & Medical Research Council of Australia (199600, 400413 and 400281), Cancer Councils of New South Wales, Victoria, Queensland, South Australia and Tasmania and Cancer Foundation of Western Australia (Multi-State Applications 191, 211, and 182). The Australian Ovarian Cancer Study gratefully acknowledges additional support from Ovarian Cancer Australia and the Peter MacCallum Foundation; BAV: ELAN Funds of the University of Erlangen-Nuremberg; BEL: National Kankerplan; BGS: Breast Cancer Now, Institute of Cancer Research; BVU: Vanderbilt CTSA grant from the National Institutes of Health (NIH)/National Center for Advancing Translational Sciences (NCATS) (ULTR000445); CAM: National Institutes of Health Research Cambridge Biomedical Research Centre and Cancer Research UK Cambridge Cancer Centre; CHA: Innovative Research Team in University (PCSIRT) in China (IRT1076); CNI: Instituto de Salud Carlos III (PI12/01319); Ministerio de Economía y Competitividad (SAF2012); COE: Department of Defense (W81XWH-11-2-0131); CON: National Institutes of Health (R01-CA063678, R01-CA074850; and R01-CA080742); DKE: Ovarian Cancer Research Fund; DOV: National Institutes of Health R01-CA112523 and R01-CA87538; EMC: Dutch Cancer Society (EMC 2014-6699); EPC: The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF) (Germany); the Hellenic Health Foundation (Greece); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); ERC-2009-AdG 232997 and Nordforsk, Nordic Centre of Excellence programme on Food, Nutrition and Health (Norway); Health Research Fund (FIS), PI13/00061 to Granada, PI13/01162 to EPIC-Murcia, Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC (RD06/0020) (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skåne and Västerbotten (Sweden); Cancer Research UK (14136 to EPIC-Norfolk; C570/A16491 and C8221/A19170 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford) (United Kingdom); GER: German Federal Ministry of Education and Research, Programme of Clinical Biomedical Research (01 GB 9401) and the German Cancer Research Center (DKFZ); GRC: This research has been co-financed by the European Union (European Social Fund—ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF)—Research Funding Program of the General Secretariat for Research & Technology: SYN11_10_19 NBCA. Investing in knowledge society through the European Social Fund; GRR: Roswell Park Cancer Institute Alliance Foundation, P30 CA016056; HAW: U.S. National Institutes of Health (R01-CA58598, N01-CN-55424, and N01-PC-67001); HJO: Intramural funding; Rudolf-Bartling Foundation; HMO: Intramural funding; Rudolf-Bartling Foundation; HOC: Helsinki University Research Fund; HOP: Department of Defense (DAMD17-02-1-0669) and NCI (K07-CA080668, R01-CA95023, P50-CA159981 MO1-RR000056 R01-CA126841); HUO: Intramural funding; Rudolf-Bartling Foundation; JGO: JSPS KAKENHI grant; JPN: Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare; KRA: This study (Ko-EVE) was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), and the National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea (HI16C1127; 0920010); LAX: American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences (NCATS), Grant UL1TR000124; LUN: ERC-2011-AdG 294576-risk factors cancer, Swedish Cancer Society, Swedish Research Council, Beta Kamprad Foundation; MAC: National Institutes of Health (R01-CA122443, P30-CA15083, P50-CA136393); Mayo Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; Fraternal Order of Eagles; MAL: Funding for this study was provided by research grant R01- CA61107 from the National Cancer Institute, Bethesda, MD, research grant 94 222 52 from the Danish Cancer Society, Copenhagen, Denmark; and the Mermaid I project; MAS: Malaysian Ministry of Higher Education (UM.C/HlR/MOHE/06) and Cancer Research Initiatives Foundation; MAY: National Institutes of Health (R01-CA122443, P30-CA15083, and P50-CA136393); Mayo Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; MCC: Cancer Council Victoria, National Health and Medical Research Council of Australia (NHMRC) grants number 209057, 251533, 396414, and 504715; MDA: DOD Ovarian Cancer Research Program (W81XWH-07-0449); MEC: NIH (CA54281, CA164973, CA63464); MOF: Moffitt Cancer Center, Merck Pharmaceuticals, the state of Florida, Hillsborough County, and the city of Tampa; NCO: National Institutes of Health (R01-CA76016) and the Department of Defense (DAMD17-02-1-0666); NEC: National Institutes of Health R01-CA54419 and P50-CA105009 and Department of Defense W81XWH-10-1-02802; NHS: UM1 CA186107, P01 CA87969, R01 CA49449, R01-CA67262, UM1 CA176726; NJO: National Cancer Institute (NIH-K07 CA095666, R01-CA83918, NIH-K22-CA138563, and P30-CA072720) and the Cancer Institute of New Jersey; If Sara Olson and/or Irene Orlow is a co-author, please add NCI CCSG award (P30-CA008748) to the funding sources; NOR: Helse Vest, The Norwegian Cancer Society, The Research Council of Norway; NTH: Radboud University Medical Centre; OPL: National Health and Medical Research Council (NHMRC) of Australia (APP1025142) and Brisbane Women’s Club; ORE: OHSU Foundation; OVA: This work was supported by Canadian Institutes of Health Research grant (MOP-86727) and by NIH/NCI 1 R01CA160669-01A1; PLC: Intramural Research Program of the National Cancer Institute; POC: Pomeranian Medical University; POL: Intramural Research Program of the National Cancer Institute; PVD: Canadian Cancer Society and Cancer Research Society GRePEC Program; RBH: National Health and Medical Research Council of Australia; RMH: Cancer Research UK, Royal Marsden Hospital; RPC: National Institute of Health (P50-CA159981, R01-CA126841); SEA: Cancer Research UK (C490/A10119 C490/A10124); UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge; SIS: NIH, National Institute of Environmental Health Sciences, Z01-ES044005 and Z01-ES049033; SMC: The bbSwedish Research Council-SIMPLER infrastructure; the Swedish Cancer Foundation; SON: National Health Research and Development Program, Health Canada, grant 6613-1415-53; SRO: Cancer Research UK (C536/A13086, C536/A6689) and Imperial Experimental Cancer Research Centre (C1312/A15589); STA: NIH grants U01 CA71966 and U01 CA69417; SWE: Swedish Cancer foundation, WeCanCureCancer and VårKampMotCancer foundation; SWH: NIH (NCI) grant R37-CA070867; TBO: National Institutes of Health (R01-CA106414-A2), American Cancer Society (CRTG-00-196-01-CCE), Department of Defense (DAMD17-98-1-8659), Celma Mastery Ovarian Cancer Foundation; TOR: NIH grants R01-CA063678 and R01 CA063682; UCI: NIH R01-CA058860 and the Lon V Smith Foundation grant LVS39420; UHN: Princess Margaret Cancer Centre Foundation-Bridge for the Cure; UKO: The UKOPS study was funded by The Eve Appeal (The Oak Foundation) and supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre; UKR: Cancer Research UK (C490/A6187), UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge; USC: P01CA17054, P30CA14089, R01CA61132, N01PC67010, R03CA113148, R03CA115195, N01CN025403, and California Cancer Research Program (00-01389V-20170, 2II0200); VAN: BC Cancer Foundation, VGH & UBC Hospital Foundation; VTL: NIH K05-CA154337; WMH: National Health and Medical Research Council of Australia, Enabling Grants ID 310670 & ID 628903. Cancer Institute NSW Grants 12/RIG/1-17 & 15/RIG/1-16; WOC: National Science Centren (N N301 5645 40). The Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Warsaw, Poland. The University of Cambridge has received salary support for PDPP from the NHS in the East of England through the Clinical Academia Reserve. The prostate cancer genome-wide association analyses: we pay tribute to Brian Henderson, who was a driving force behind the OncoArray project, for his vision and leadership, and who sadly passed away before seeing its fruition. We also thank the individuals who participated in these studies enabling this work. The ELLIPSE/PRACTICAL (http//:practical.icr.ac.uk) prostate cancer consortium and his collaborating partners were supported by multiple funding mechanisms enabling this current work. ELLIPSE/PRACTICAL Genotyping of the OncoArray was funded by the US National Institutes of Health (NIH) (U19 CA148537 for ELucidating Loci Involved in Prostate Cancer SuscEptibility (ELLIPSE) project and X01HG007492 to the Center for Inherited Disease Research (CIDR) under contract number HHSN268201200008I). Additional analytical support was provided by NIH NCI U01 CA188392 (F.R.S.). Funding for the iCOGS infrastructure came from the European Community’s Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, and C8197/A16565), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065, and 1U19 CA148112; the GAME-ON initiative), the Department of Defense (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. This work was supported by the Canadian Institutes of Health Research, European Commission’s Seventh Framework Programme grant agreement n° 223175 (HEALTH-F2-2009-223175), Cancer Research UK Grants C5047/A7357, C1287/A10118, C1287/A16563, C5047/A3354, C5047/A10692, C16913/A6135, C5047/A21332 and The National Institute of Health (NIH) Cancer Post-Cancer GWAS initiative grant: No. 1 U19 CA148537-01 (the GAME-ON initiative). We also thank the following for funding support: The Institute of Cancer Research and The Everyman Campaign, The Prostate Cancer Research Foundation, Prostate Research Campaign UK (now Prostate Action), The Orchid Cancer Appeal, The National Cancer Research Network UK, and The National Cancer Research Institute (NCRI) UK. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. The Prostate Cancer Program of Cancer Council Victoria also acknowledge grant support from The National Health and Medical Research Council, Australia (126402, 209057, 251533, 396414, 450104, 504700, 504702, 504715, 623204, 940394, and 614296), VicHealth, Cancer Council Victoria, The Prostate Cancer Foundation of Australia, The Whitten Foundation, PricewaterhouseCoopers, and Tattersall’s. E.A.O., D.M.K., and E.M.K. acknowledge the Intramural Program of the National Human Genome Research Institute for their support. The BPC3 was supported by the U.S. National Institutes of Health, National Cancer Institute (cooperative agreements U01-CA98233 to D.J.H., U01-CA98710 to S.M.G., U01-CA98216 to E.R., and U01-CA98758 to B.E.H., and Intramural Research Program of NIH/National Cancer Institute, Division of Cancer Epidemiology and Genetics). CAPS GWAS study was supported by the Swedish Cancer Foundation (grant no 09-0677, 11-484, 12-823), the Cancer Risk Prediction Center (CRisP; www.crispcenter.org), a Linneus Centre (Contract ID 70867902) financed by the Swedish Research Council, Swedish Research Council (grant no K2010-70 × -20430-04-3, 2014-2269). The Hannover Prostate Cancer Study was supported by the Lower Saxonian Cancer Society. PEGASUS was supported by the Intramural Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health. RAPPER was supported by the NIHR Manchester Biomedical Research Center, Cancer Research UK (C147/A25254, C1094/A18504) and the EU’s 7th Framework Programme Grant/Agreement no 60186. Overall: this research has been conducted using the UK Biobank Resource (application number 16549). NHS is supported by UM1 CA186107 (NHS cohort infrastructure grant), P01 CA87969, and R01 CA49449. NHSII is supported by UM1 CA176726 (NHSII cohort infrastructure grant), and R01-CA67262. A.L.K. is supported by R01 MH107649. We would like to thank the participants and staff of the NHS and NHSII for their valuable contributions as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. The authors assume full responsibility for analyses and interpretation of these data.

Background: Despite a large body of literature evaluating the association between recreational physical activity and epithelial ovarian cancer (EOC) risk, the extant evidence is inconclusive, and little is known about the independent association between recreational physical inactivity and EOC risk. We conducted a pooled analysis of nine studies from the Ovarian Cancer Association Consortium to investigate the association between chronic recreational physical inactivity and EOC risk. Methods: In accordance with the 2008 Physical Activity Guidelines for Americans, women reporting no regular, weekly recreational physical activity were classified as inactive. Multivariable logistic regression was utilized to estimate the ORs and 95% confidence intervals (CI) for the association between inactivity and EOC risk overall and by subgroups based upon histotype, menopausal status, race, and body mass index. Results: The current analysis included data from 8,309 EOC patients and 12,612 controls. We observed a significant positive association between inactivity and EOC risk (OR = 1.34; 95% CI, 1.14–1.57), and similar associations were observed for each histotype. Conclusions: In this large pooled analysis examining the association between recreational physical inactivity and EOC risk, we observed consistent evidence of an association between chronic inactivity and all EOC histotypes. Impact: These data add to the growing body of evidence suggesting that inactivity is an independent risk factor for cancer. If the apparent association between inactivity and EOC risk is substantiated, additional work via targeted interventions should be pursued to characterize the dose of activity required to mitigate the risk of this highly fatal disease. Cancer Epidemiol Biomarkers Prev; 25(7); 1114–24. ©2016 AACR.

Background: Little is known about modifiable behaviours that may be associated with epithelial ovarian cancer (EOC) survival. We conducted a pooled analysis of 12 studies from the Ovarian Cancer Association Consortium to investigate the association between pre-diagnostic physical inactivity and mortality. Methods: Participants included 6806 women with a primary diagnosis of invasive EOC. In accordance with the Physical Activity Guidelines for Americans, women reporting no regular, weekly recreational physical activity were classified as inactive. We utilised Cox proportional hazard models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) representing the associations of inactivity with mortality censored at 5 years. Results: In multivariate analysis, inactive women had significantly higher mortality risks, with (HR=1.34, 95% CI: 1.18–1.52) and without (HR=1.22, 95% CI: 1.12–1.33) further adjustment for residual disease, respectively. Conclusion: In this large pooled analysis, lack of recreational physical activity was associated with increased mortality among women with invasive EOC.

Basal cell and squamous cell carcinomas of the skin are the commonest cancers in humans, yet no validated tools exist to estimate future risks of developing keratinocyte carcinomas. To develop a prediction tool, we used baseline data from a prospective cohort study (n = 38,726) in Queensland, Australia, and used data linkage to capture all surgically excised keratinocyte carcinomas arising within the cohort. Predictive factors were identified through stepwise logistic regression models. In secondary analyses, we derived separate models within strata of prior skin cancer history, age, and sex. The primary model included terms for 10 items. Factors with the strongest effects were >20 prior skin cancers excised (odds ratio 8.57, 95% confidence interval [95% CI] 6.73–10.91), >50 skin lesions destroyed (odds ratio 3.37, 95% CI 2.85–3.99), age ≥ 70 years (odds ratio 3.47, 95% CI 2.53–4.77), and fair skin color (odds ratio 1.75, 95% CI 1.42–2.15). Discrimination in the validation dataset was high (area under the receiver operator characteristic curve 0.80, 95% CI 0.79–0.81) and the model appeared well calibrated. Among those reporting no prior history of skin cancer, a similar model with 10 factors predicted keratinocyte carcinoma events with reasonable discrimination (area under the receiver operator characteristic curve 0.72, 95% CI 0.70–0.75). Algorithms using self-reported patient data have high accuracy for predicting risks of keratinocyte carcinomas.