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Background: Genome-wide association studies (GWAS) of multiple myeloma in populations of European ancestry (EA) identified and confirmed 24 susceptibility loci. For other cancers (e.g., colorectum and melanoma), risk loci have also been associated with patient survival. Methods: We explored the possible association of all the known risk variants and their polygenic risk score (PRS) with multiple myeloma overall survival (OS) in multiple populations of EA [the International Multiple Myeloma rESEarch (IMMEnSE) consortium, the International Lymphoma Epidemiology consortium, CoMMpass, and the German GWAS] for a total of 3,748 multiple myeloma cases. Cox proportional hazards regression was used to assess the association between each risk SNP with OS under the allelic and codominant models of inheritance. All analyses were adjusted for age, sex, country of origin (for IMMEnSE) or principal components (for the others) and disease stage (ISS). SNP associations were meta-analyzed. Results: SNP associations were meta-analyzed. From the meta-analysis, two multiple myeloma risk SNPs were associated with OS (P < 0.05), specifically POT1-AS1-rs2170352 [HR = 1.37; 95% confidence interval (CI) = 1.09–1.73; P = 0.007] and TNFRSF13B-rs4273077 (HR = 1.19; 95% CI = 1.01–1.41; P = 0.04). The association between the combined 24 SNP MM-PRS and OS, however, was not significant. Conclusions: Overall, our results did not support an association between the majority of multiple myeloma risk SNPs and OS. Impact: This is the first study to investigate the association between multiple myeloma PRS and OS in multiple myeloma.

Background: Self-reported information may not accurately capture smoking exposure. We aimed to evaluate whether smoking-associated DNA methylation markers improve urothelial cell carcinoma (UCC) risk prediction. Methods: Conditional logistic regression was used to assess associations between blood-based methylation and UCC risk using two matched case–control samples: 404 pairs from the Melbourne Collaborative Cohort Study (MCCS) and 440 pairs from the Women's Health Initiative (WHI) cohort. Results were pooled using fixed-effects meta-analysis. We developed methylation-based predictors of UCC and evaluated their prediction accuracy on two replication data sets using the area under the curve (AUC). Results: The meta-analysis identified associations (P < 4.7 × 10−5) for 29 of 1,061 smoking-associated methylation sites, but these were substantially attenuated after adjustment for self-reported smoking. Nominally significant associations (P < 0.05) were found for 387 (36%) and 86 (8%) of smoking-associated markers without/with adjustment for self-reported smoking, respectively, with same direction of association as with smoking for 387 (100%) and 79 (92%) markers. A Lasso-based predictor was associated with UCC risk in one replication data set in MCCS [N = 134; odds ratio per SD (OR) = 1.37; 95% CI, 1.00–1.90] after confounder adjustment; AUC = 0.66, compared with AUC = 0.64 without methylation information. Limited evidence of replication was found in the second testing data set in WHI (N = 440; OR = 1.09; 95% CI, 0.91–1.30). Conclusions: Combination of smoking-associated methylation marks may provide some improvement to UCC risk prediction. Our findings need further evaluation using larger data sets. Impact: DNA methylation may be associated with UCC risk beyond traditional smoking assessment and could contribute to some improvements in stratification of UCC risk in the general population.

Background: Estimates of future burden of cancer attributable to current modifiable causal exposures can guide cancer prevention. We quantified future head and neck cancer burden in Australia attributable to individual and joint causal exposures, and assessed whether these burdens differ between population subgroups. Methods: We estimated the strength of the associations between exposures and head and neck cancer using adjusted proportional hazards models from pooled data from seven Australian cohorts (N = 367,058) linked to national cancer and death registries and estimated exposure prevalence from the 2017 to 2018 Australian National Health Survey. We calculated population attributable fractions (PAF) with 95% confidence intervals (CI), accounting for competing risk of death, and compared PAFs for population subgroups. Results: Contemporary levels of current and former smoking contribute 30.6% (95% CI, 22.7%–37.8%), alcohol consumption exceeding two standard drinks per day 12.9% (95% CI, 7.6%–17.9%), and these exposures jointly 38.5% (95% CI, 31.1%–45.0%) to the future head and neck cancer burden. Alcohol-attributable burden is triple and smoking-attributable burden is double for men compared with women. Smoking-attributable burden is also at least double for those consuming more than two alcoholic drinks daily or doing less than 150 minutes of moderate or 75 minutes of vigorous activity weekly, and for those aged under 65 years, unmarried, with low or intermediate educational attainment or lower socioeconomic status, compared with their counterparts. Conclusions: Two-fifths of head and neck cancers in Australia are preventable by investment in tobacco and alcohol control. Impact: Targeting men and other identified high-burden subgroups can help to reduce head and neck cancer burden disparities.

Background: High numbers of lymphocytes in tumor tissue, including T regulatory cells (Treg), have been associated with better colorectal cancer survival. Tregs, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and therefore variants in genes related to Treg differentiation and function could be associated with colorectal cancer prognosis. Methods: In a prospective German cohort of 3,593 colorectal cancer patients, we assessed the association of 771 single-nucleotide polymorphisms (SNP) in 58 Treg-related genes with overall and colorectal cancer–specific survival using Cox regression models. Effect modification by microsatellite instability (MSI) status was also investigated because tumors with MSI show greater lymphocytic infiltration and have been associated with better prognosis. Replication of significant results was attempted in 2,047 colorectal cancer patients of the International Survival Analysis in Colorectal Cancer Consortium (ISACC). Results: A significant association of the TGFBR3 SNP rs7524066 with more favorable colorectal cancer–specific survival [hazard ratio (HR) per minor allele: 0.83; 95% confidence interval (CI), 0.74–0.94; P value: 0.0033] was replicated in ISACC (HR: 0.82; 95% CI, 0.68–0.98; P value: 0.03). Suggestive evidence for association was found with two IL7 SNPs, rs16906568 and rs7845577. Thirteen SNPs with differential associations with overall survival according to MSI in the discovery analysis were not confirmed. Conclusions: Common genetic variation in the Treg pathway implicating genes such as TGFBR3 and IL7 was shown to be associated with prognosis of colorectal cancer patients. Impact: The implicated genes warrant further investigation.

Background: Whether circulating polyunsaturated fatty acid (PUFA) levels are associated with pancreatic cancer risk is uncertain. Mendelian randomization (MR) represents a study design using genetic instruments to better characterize the relationship between exposure and outcome. Methods: We utilized data from genome-wide association studies within the Pancreatic Cancer Cohort Consortium and Pancreatic Cancer Case–Control Consortium, involving approximately 9,269 cases and 12,530 controls of European descent, to evaluate associations between pancreatic cancer risk and genetically predicted plasma n-6 PUFA levels. Conventional MR analyses were performed using individual-level and summary-level data. Results: Using genetic instruments, we did not find evidence of associations between genetically predicted plasma n-6 PUFA levels and pancreatic cancer risk [estimates per one SD increase in each PUFA-specific weighted genetic score using summary statistics: linoleic acid odds ratio (OR) = 1.00, 95% confidence interval (CI) = 0.98–1.02; arachidonic acid OR = 1.00, 95% CI = 0.99–1.01; and dihomo-gamma-linolenic acid OR = 0.95, 95% CI = 0.87–1.02]. The OR estimates remained virtually unchanged after adjustment for covariates, using individual-level data or summary statistics, or stratification by age and sex. Conclusions: Our results suggest that variations of genetically determined plasma n-6 PUFA levels are not associated with pancreatic cancer risk. Impact: These results suggest that modifying n-6 PUFA levels through food sources or supplementation may not influence risk of pancreatic cancer.

Background: Obesity and diabetes are major modifiable risk factors for pancreatic cancer. Interactions between genetic variants and diabetes/obesity have not previously been comprehensively investigated in pancreatic cancer at the genome-wide level. Methods: We conducted a gene–environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I–III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case–control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics. Results: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P < 1.25 × 10−6) was observed in the meta-analysis (PGxE = 1.2 ×10−6, PJoint = 4.2 ×10−7). Conclusions: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans. Impact: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, with few known risk factors and biomarkers. Several blood protein biomarkers have been linked to PDAC in previous studies, but these studies have assessed only a limited number of biomarkers, usually in small samples. In this study, we evaluated associations of circulating protein levels and PDAC risk using genetic instruments. Methods: To identify novel circulating protein biomarkers of PDAC, we studied 8,280 cases and 6,728 controls of European descent from the Pancreatic Cancer Cohort Consortium and the Pancreatic Cancer Case-Control Consortium, using genetic instruments of protein quantitative trait loci. Results: We observed associations between predicted concentrations of 38 proteins and PDAC risk at an FDR of < 0.05, including 23 of those proteins that showed an association even after Bonferroni correction. These include the protein encoded by ABO, which has been implicated as a potential target gene of PDAC risk variant. Eight of the identified proteins (LMA2L, TM11D, IP-10, ADH1B, STOM, TENC1, DOCK9, and CRBB2) were associated with PDAC risk after adjusting for previously reported PDAC risk variants (OR ranged from 0.79 to 1.52). Pathway enrichment analysis showed that the encoding genes for implicated proteins were significantly enriched in cancer-related pathways, such as STAT3 and IL15 production. Conclusions: We identified 38 candidates of protein biomarkers for PDAC risk. Impact: This study identifies novel protein biomarker candidates for PDAC, which if validated by additional studies, may contribute to the etiologic understanding of PDAC development.

Background: The role of vitamin D in cancer risk remains controversial, and limited data exist on associations between vitamin D and subtypes of specific cancers. We investigated associations between circulating 25-hydroxyvitamin D (25(OH)D) and risk of colorectal, breast, and prostate cancers, including subtypes. Methods: A case–cohort study within the Melbourne Collaborative Cohort Study included 547 colorectal, 634 breast, and 824 prostate cancers, and a sex-stratified random sample of participants (n = 2,996). Concentration of 25(OH)D in baseline-dried blood spots was measured using LC-MS/MS. Cox regression yielded adjusted HRs and 95% confidence intervals (CI) for each cancer in relation to plasma-equivalent 25(OH)D concentration. Associations by stage and BRAF/KRAS status for colorectal cancer, estrogen receptor status for breast cancer, and aggressiveness for prostate cancer were examined in competing risks models. Results: 25(OH)D concentrations were inversely associated with risk of colorectal cancer [highest vs. lowest 25(OH)D quintile: HR, 0.71; 95% confidence interval (CI), 0.51–0.98], which was limited to women (HR, 0.52; 95% CI, 0.33–0.82). Circulating 25(OH)D was also inversely associated with BRAF V600E–positive colorectal cancer (per 25 nmol/L increment: HR, 0.71; 95% CI, 0.50–1.01). There were no inverse associations with breast cancer (HR, 0.98; 95% CI, 0.70–1.36) or prostate cancer (HR, 1.11; 95% CI, 0.82–1.48). Conclusions: Circulating 25(OH)D concentration was inversely associated with colorectal cancer risk for women, but not with risk of breast cancer or prostate cancer. Impact: Vitamin D might play a role in preventing colorectal cancer. Further studies are required to confirm whether vitamin D is associated with specific tumor subtypes.

Background: Although some familial cancer syndromes include biliary tract cancers (BTCs; cancers of the gallbladder, intrahepatic and extrahepatic bile ducts, and ampulla of Vater), the few studies that have examined the relationships between family history of cancer (FHC) and BTCs have reported inconclusive findings. The objective of this study was to investigate the associations of FHC with risk of BTC in the Biliary Tract Cancers Pooling Project (BiTCaPP). Methods: We used Cox proportional hazards regressions models to estimate HRs and 95% confidence intervals for associations between FHC (any, first-degree, in female relative, in male relative, relative with gastrointestinal cancer, and relative with hormonally related cancer) and BTC risk by anatomic site within the biliary tract, adjusting for sex and race/ethnicity. Sensitivity analyses were conducted that restricted to studies reporting cholecystectomy data and to people without a history of cholecystectomy. Results: Data on FHC were available from 12 prospective studies within BiTCaPP, which collectively contributed 2,246 cases (729 gallbladder, 345 intrahepatic and 615 extrahepatic bile duct, and 385 ampulla of Vater cancers) with 21,706,107 person-years of follow-up. A marginal, inverse association between FHC and gallbladder cancer was driven to the null when analysis was restricted to studies reporting cholecystectomy data and to people without a history of cholecystectomy. FHC was not associated with risk of BTC at the other anatomic sites. Conclusions: These findings do not support an association between FHC and BTCs. Impact: In a study of 1.5 million people, FHC is not a risk factor for BTCs. Cancer Epidemiol Biomarkers Prev; 27(3); 348–51. ©2018 AACR.

Background: After adjusting for age and body mass index (BMI), mammographic measures—dense area (DA), percent dense area (PDA), and nondense area (NDA)—are associated with breast cancer risk. Our aim was to use longitudinal data to estimate the extent to which these risk-predicting measures track over time. Methods: We collected 4,320 mammograms (age range, 24–83 years) from 970 women in the Melbourne Collaborative Cohort Study and the Australian Breast Cancer Family Registry. Women had on average 4.5 mammograms (range, 1–14). DA, PDA, and NDA were measured using the Cumulus software and normalized using the Box–Cox method. Correlations in the normalized risk-predicting measures over time intervals of different lengths were estimated using nonlinear mixed-effects modeling of Gompertz curves. Results: Mean normalized DA and PDA were constant with age to the early 40s, decreased over the next two decades, and were almost constant from the mid-60s onward. Mean normalized NDA increased nonlinearly with age. After adjusting for age and BMI, the within-woman correlation estimates for normalized DA were 0.94, 0.93, 0.91, 0.91, and 0.91 for mammograms taken 2, 4, 6, 8, and 10 years apart, respectively. Similar correlations were estimated for the age- and BMI-adjusted normalized PDA and NDA. Conclusions: The mammographic measures that predict breast cancer risk are highly correlated over time. Impact: This has implications for etiologic research and clinical management whereby women at increased risk could be identified at a young age (e.g., early 40s or even younger) and recommended appropriate screening and prevention strategies. Cancer Epidemiol Biomarkers Prev; 26(4); 651–60. ©2017 AACR.

Background: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. Methods: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. Cancer Epidemiol Biomarkers Prev; 24(10); 1574–84. ©2015 AACR.

Background: Quantifying the risk of colorectal cancer for individuals is likely to be useful for health service provision. Our aim was to develop and externally validate a prediction model to predict 5-year colorectal cancer risk. Methods: We used proportional hazards regression to develop the model based on established personal and lifestyle colorectal cancer risk factors using data from 197,874 individuals from the 45 and Up Study, Australia. We subsequently validated the model using 24,233 participants from the Melbourne Collaborative Cohort Study (MCCS). Results: A total of 1,103 and 224 cases of colorectal cancer were diagnosed in the development and validation sample, respectively. Our model, which includes age, sex, BMI, prevalent diabetes, ever having undergone colorectal cancer screening, smoking, and alcohol intake, exhibited a discriminatory accuracy of 0.73 [95% confidence interval (CI), 0.72–0.75] and 0.70 (95% CI, 0.66–0.73) using the development and validation sample, respectively. Calibration was good for both study samples. Stratified models according to colorectal cancer screening history, that additionally included family history, showed discriminatory accuracies of 0.75 (0.73–0.76) and 0.70 (0.67–0.72) for unscreened and screened individuals of the development sample, respectively. In the validation sample, discrimination was 0.68 (0.64–0.73) and 0.72 (0.67–0.76), respectively. Conclusion: Our model exhibited adequate predictive performance that was maintained in the external population. Impact: The model may be useful to design more powerful cancer prevention trials. In the group of unscreened individuals, the model may be useful as a preselection tool for population-based screening programs. Cancer Epidemiol Biomarkers Prev; 23(11); 2543–52. ©2014 AACR.

Background: Both prostate cancer and androgenetic alopecia are strongly age-related conditions that are considered to be androgen dependent, but studies of the relationship between them have yielded inconsistent results. We aimed to assess whether androgenetic alopecia at ages 20 and 40 years are associated with risk of prostate cancer. Methods: At a follow-up of the Melbourne Collaborative Cohort Study, men were asked to assess their hair pattern at ages 20 and 40 years relative to eight categories in showcards. Cases were men notified to the Victorian Cancer Registry with prostate cancer diagnosed between cohort enrollment (1990–1994) and follow-up attendance (2003–2009). Flexible parametric survival models were used to estimate age-varying HRs and predicted cumulative probabilities of prostate cancer by androgenetic alopecia categories. Results: Of 9,448 men that attended follow-up and provided data on androgenetic alopecia, we identified 476 prostate cancer cases during a median follow-up of 11 years four months. Cumulative probability of prostate cancer was greater at all ages up to 76 years, for men with vertex versus no androgenetic alopecia at age of 40 years. At age of 76 years, the estimated probabilities converged to 0.15. Vertex androgenetic alopecia at 40 years was also associated with younger age of diagnosis for prostate cancer cases. Conclusions: Vertex androgenetic alopecia at age of 40 years might be a marker of increased risk of early-onset prostate cancer. Impact: If confirmed, these results suggest that the apparently conflicting findings of previous studies might be explained by failure to adequately model the age-varying nature of the association between androgenetic alopecia and prostate cancer. Cancer Epidemiol Biomarkers Prev; 22(2); 209–15. ©2012 AACR.

Background: Mammographic density is a strong risk factor for breast cancer. It is unknown whether there are different causes of variation in mammographic density at different ages. Methods: Mammograms and questionnaires were obtained on average 8 years apart from 327 Australian female twin pairs (204 monozygous and 123 dizygous). Mammographic dense area and percentage dense area were measured using a computer-assisted method. The correlational structure of the longitudinal twin data was estimated under a multivariate normal model using FISHER. Inference about causation from examination of familial confounding was made by regressing each twin's recent mammographic density measure against one or both of her and her co-twin's past measures. Results: For square root dense area and percentage dense area (age- and body mass index–adjusted), the correlations over time within twins were 0.86 and 0.82, and the cross-twin correlations were 0.71 and 0.65 for monozygous pairs and 0.25 and 0.20 for dizygous pairs, respectively. As a predictor of a twin's recent dense area, the regression coefficient (SE) for the co-twin's past dense area reduced after adjusting for her own past measure from 0.84 (0.03) to 0.09 (0.03) for monozygous pairs and from 0.63 (0.04) to 0.04 (0.03) for dizygous pairs. Corresponding estimates for percentage dense area were 0.73 (0.04), 0.10 (0.03), 0.42 (0.05), and 0.03 (0.03). Conclusion: Mammographic density measures are highly correlated over time and the familial/genetic components of their variation are established before mid-life. Impact: Mammographic density of young women could provide a means for breast cancer control. Cancer Epidemiol Biomarkers Prev; 21(7); 1149–55. ©2012 AACR.

Background: Epidemiologic studies have consistently reported positive associations between obesity and colon cancer risk for men, but the evidence is less consistent for women. Few studies have investigated effects of weight change on colon cancer risk. Methods: Using the Melbourne Collaborative Cohort Study, which recruited men and women mostly in 40 to 69 years of age, we investigated associations between weight and body mass index (BMI) at age 18 years and at study entry and weight change since age 18 years and colon cancer. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using Cox regression. Results: During follow-up of 16,188 men and 23,438 women for 14 years on average, we ascertained 569 incident colon cancers. Weight and BMI at study entry were positively associated with colon cancer risk for men [HR, 1.12 (95% CI, 1.04-1.21) per 5-kg increment; HR, 1.39 (95% CI, 1.12-1.71) per 5 kg/m2], but not women. Risk of colon cancer was not associated with weight or BMI at age 18 years. Adult weight change was positively associated with colon cancer risk for men (HR, 1.11 per 5-kg increment; 95% CI, 1.03-1.20), but not women (HR, 1.00; 95% CI, 0.94-1.07). Men who gained ≥20 kg from age 18 had an increased risk of colon cancer compared with men whose weight was stable (HR, 1.47; 95% CI, 0.94-2.31). Conclusion: Weight gain during adult life increases men's risk of colon cancer. Impact: Avoiding excessive weight gain might help reduce colon cancer risk for men. Cancer Epidemiol Biomarkers Prev; 19(11); 2978–86. ©2010 AACR.

Studies have examined the prognostic relevance of reproductive factors before breast cancer diagnosis, but most have been small and their overall findings inconclusive. Associations between reproductive risk factors and all-cause mortality after breast cancer diagnosis were assessed with the use of a population-based cohort of 3,107 women of White European ancestry with invasive breast cancer (1,130 from Melbourne and Sydney, Australia; 1,441 from Ontario, Canada; and 536 from Northern California, United States). During follow-up with a median of 8.5 years, 567 deaths occurred. At recruitment, questionnaire data were collected on oral contraceptive use, number of full-term pregnancies, age at first full-term pregnancy, time from last full-term pregnancy to breast cancer diagnosis, breastfeeding, age at menarche, and menopause and menopausal status at breast cancer diagnosis. Hazard ratios for all-cause mortality were estimated with the use of Cox proportional hazards models with and without adjustment for age at diagnosis, study center, education, and body mass index. Compared with nulliparous women, those who had a child up to 2 years, or between 2 and 5 years, before their breast cancer diagnosis were more likely to die. The unadjusted hazard ratio estimates were 2.75 [95% confidence interval (95% CI), 1.98-3.83; P < 0.001] and 2.20 (95% CI, 1.65-2.94; P < 0.001), respectively, and the adjusted estimates were 2.25 (95% CI, 1.59-3.18; P < 0.001) and 1.82 (95% CI, 1.35-2.46; P < 0.001), respectively. When evaluating the prognosis of women recently diagnosed with breast cancer, the time since last full-term pregnancy should be routinely considered along with other established host and tumor prognostic factors, but consideration of other reproductive factors may not be warranted. (Cancer Epidemiol Biomarkers Prev 2009;18(6):1792–7)

Fruit and vegetable consumption has been hypothesized to reduce the risk of renal cell cancer. We conducted a pooled analysis of 13 prospective studies, including 1,478 incident cases of renal cell cancer (709 women and 769 men) among 530,469 women and 244,483 men followed for up to 7 to 20 years. Participants completed a validated food-frequency questionnaire at baseline. Using the primary data from each study, the study-specific relative risks (RR) were calculated using the Cox proportional hazards model and then pooled using a random effects model. We found that fruit and vegetable consumption was associated with a reduced risk of renal cell cancer. Compared with

Understanding which factors influence mammographically dense and nondense areas is important because percent mammographic density adjusted for age is a strong, continuously distributed risk factor for breast cancer, especially when adjusted for weight or body mass index. Using computer-assisted methods, we measured mammographically dense areas for 571 monozygotic and 380 dizygotic Australian and North American twin pairs ages 40 to 70 years. We used a novel regression modeling approach in which each twin's measure of dense and nondense area was regressed against one or both of the twin's and co-twin's covariates. The nature of changes to regression estimates with the inclusion of the twin and/or co-twin's covariates can be evaluated for consistency with causal and/or other models. By causal, we mean that if it were possible to vary a covariate experimentally then the expected value of the outcome measure would change. After adjusting for the individual's weight, the co-twin associations with weight were attenuated, consistent with a causal effect of weight on mammographic measures, which in absolute log cm2/kg was thrice stronger for nondense than dense area. After adjusting for weight, later age at menarche, and greater height were associated with greater dense and lesser nondense areas in a manner inconsistent with causality. The associations of dense and nondense areas with parity are consistent with a causal effect and/or within-person confounding. The associations between mammographic density measures and height are consistent with shared early life environmental factors that predispose to both height and percent mammographic density and possibly breast cancer risk. (Cancer Epidemiol Biomarkers Prev 2008;17(12):3474–81)

A recent genome-wide association study found that genetic variants on chromosomes 3, 6, 7, 10, 11, 19 and X were associated with prostate cancer risk. We evaluated the most significant single-nucleotide polymorphisms (SNP) in these loci using a worldwide consortium of 13 groups (PRACTICAL). Blood DNA from 7,370 prostate cancer cases and 5,742 male controls was analyzed by genotyping assays. Odds ratios (OR) associated with each genotype were estimated using unconditional logistic regression. Six of the seven SNPs showed clear evidence of association with prostate cancer (P = 0.0007-P = 10−17). For each of these six SNPs, the estimated per-allele OR was similar to those previously reported and ranged from 1.12 to 1.29. One SNP on 3p12 (rs2660753) showed a weaker association than previously reported [per-allele OR, 1.08 (95% confidence interval, 1.00-1.16; P = 0.06) versus 1.18 (95% confidence interval, 1.06-1.31)]. The combined risks associated with each pair of SNPs were consistent with a multiplicative risk model. Under this model, and in combination with previously reported SNPs on 8q and 17q, these loci explain 16% of the familial risk of the disease, and men in the top 10% of the risk distribution have a 2.1-fold increased risk relative to general population rates. This study provides strong confirmation of these susceptibility loci in multiple populations and shows that they make an important contribution to prostate cancer risk prediction. (Cancer Epidemiol Biomarkers Prev 2008;17(8):2052–61)

Some recent epidemiologic studies have failed to confirm positive associations between insulin-like growth factor-I (IGF-I) and the risk of prostate cancer observed in earlier studies but have reported suggestive evidence for a positive association between IGF-binding protein-3 (IGFBP-3) and prostate cancer risk, a result contradicting the earlier assumption that high levels of IGFBP-3 would be protective against prostate cancer. We tested the association between IGF-I and IGFBP-3 and prostate cancer risk by measuring the two peptides in plasma samples collected at baseline in a prospective cohort study of 17,049 men. We used a case-cohort design, including 524 cases diagnosed during a mean of 8.7 years follow-up and a randomly sampled subcohort of 1,826 men. The association between each peptide level and prostate cancer risk was tested using Cox models adjusted for country of birth and alcohol consumption. The risk of prostate cancer was not associated with baseline levels of IGF-I or the molar ratio IGF-I/IGFBP-3 (all odds ratios are between 0.82 and 1.08; Ptrend ≥ 0.2), whereas the risk increased with baseline levels of IGFBP-3 (Ptrend = 0.008), the hazard ratio (HR) associated with a doubling of the concentration of IGFBP-3 being 1.70 (95% confidence interval, 1.15-2.52). The HR for quartile 4 relative to quartile 1 of IGFBP-3 was 1.49 (95% confidence interval, 1.11-2.00). The HRs did not differ by tumor aggressiveness or age at onset (all Ps ≥ 0.4). In our study, high levels of IGFBP-3 but not IGF-I were associated with an increased risk of prostate cancer. (Cancer Epidemiol Biomarkers Prev 2006;15(6):1137–41)

A substantial proportion of the familial risk of breast cancer may be due to genetic variants, each contributing a small effect. The protein encoded by ERCC2 is a key enzyme involved in nucleotide excision repair, in which gene defects could lead to cancer prone syndromes such as Xeroderma pigmentosum D. We have examined the association between single nucleotide polymorphisms in the ERCC2 gene and the incidence of invasive breast cancer in three case-control series, with a maximum of 3,634 patients and of 3,340 controls. None of the three single nucleotide polymorphisms were significantly associated with the incidence of breast cancer.

Purpose: Obesity is associated with adverse outcomes in postmenopausal women with breast cancer. In premenopausal women, the association is less clear. Methods: A population-based sample of 1,360 Australian women with breast cancer before the age of 60 years, 47% diagnosed before age 40, and 74% premenopausal, was studied prospectively for a median of 5 years (range, 0.2-10.8 years). Obesity was defined as a body mass index of ≥30 kg/m2. The hazard ratio (HR) for adverse clinical outcome associated with obesity was estimated using Cox proportional hazard survival models. Results: Obesity increased with age (P < 0.001) and was associated with increased breast cancer recurrence (P = 0.02) and death (P = 0.06), larger tumors (P = 0.002), and more involved axillary nodes (P = 0.003) but not with hormone receptor status (P ≥ 0.6) or with first cycle adjuvant chemotherapy dose reductions (P = 0.1). Adjusting for number of axillary nodes, age at diagnosis, tumor size, grade, and hormone receptor status, obese women of all ages were more likely than nonobese women to have disease recurrence [HR, 1.57; 95% confidence interval (95% CI), 1.11-2.22; P = 0.02] and to die from any cause during follow-up (HR, 1.56; 95% CI, 1.01-2.40; P = 0.05). In premenopausal women, the adjusted HRs were 1.50 (95% CI, 1.00-2.26; P = 0.06) and 1.71 (95% CI, 1.05-2.77; P = 0.04), respectively. Conclusions: Obesity is independently associated with poorer outcomes in premenopausal women, as it is in postmenopausal women, and this is not entirely explained by differences in tumor size or nodal status. Given the high and increasing prevalence of obesity in western countries, more research on improving the treatment of obese breast cancer patients is warranted.

Objective: We examine to what extent the lower mammographic sensitivity found in hormone replacement therapy (HRT) users can be explained by any association of HRT use with higher mammographic density and more difficult to detect cancers. Methods: We used logistic regression to estimate the odds of a false-negative screen (a breast cancer diagnosed in the 24 months after a negative screening examination) for HRT users and to estimate, and adjust for, mammographic density (measured on a continuous scale, blinded, using a reliable, computer-assisted method), tumor characteristics (size, grade, and morphology), and potential confounders (age, symptom status, family history, and prior screening) among women ages ≥55 years who attended BreastScreen Victoria for first round screening mammography in 1994 and 1995 (1,086 breast cancers) and for subsequent round screening (471 breast cancers) in 1995 and 1996. Results: After adjusting for confounders, HRT users were more likely to have a false-negative screen [first round: odds ratio (OR), 1.99; 95% confidence interval (95% CI), 1.4-2.9; subsequent round: OR, 2.29; 95% CI, 1.4-3.8]. This effect was modestly attenuated by adjusting for mammographic density (first round: OR, 1.54; 95% CI, 1.0-2.3; subsequent round: OR, 1.97; 95% CI, 1.2-3.3). Adjusting for tumor characteristics resulted in a modest increase in the odds of a false negative at first round but had no effect at subsequent round. Conclusions: Mammographic density only partly explains the effect of HRT on sensitivity. Further research needs to clarify whether hyperemic breast tissue changes affect cancer detectability in HRT users as well as the possibility that the quality of mammography may be poor in some HRT users.

Background: Variants in the gene encoding the macrophage scavenger receptor 1 (MSR14) protein have been identified in men with prostate cancer, and several small studies have suggested that the 999C>T (R293X) protein-truncating mutation may be associated with an increased risk for this disease. Methods: Using large case-control, cohort, and prostate cancer family studies conducted in several Western countries, we tested for the 999C>T mutation in 2,943 men with invasive prostate carcinoma, including 401 males from multiple-case families, 1,982 cases unselected for age, and 575 men diagnosed before the age of 56 years, and in 2,870 male controls. Risk ratios were estimated by unconditional logistic regression adjusting for country and by a modified segregation analysis. A meta-analysis was conducted pooling our data with published data. Results: The prevalence of MSR1*999C>T mutation carriers was 0.027 (SE, 0.003) in cases and 0.022 (SE, 0.002) in controls, and did not differ by country, ethnicity, or source. The adjusted risk ratio for prostate cancer associated with being a 999C>T carrier was 1.31 [95% confidence interval (CI), 0.93-1.84; P = 0.16]. The modified segregation analysis estimated the risk ratio to be 1.20 (95% CI, 0.87-1.66; P = 0.16). The risk ratio estimated from the meta-analysis was 1.34 (95% CI, 0.94-1.89; P = 0.10). Conclusion: Our large-scale analysis of case and controls from several countries found no evidence that the 999C>T mutation is associated with increased risk of prostate cancer. The meta-analysis suggests it is unlikely that this mutation confers more than a 2-fold increased risk.

Background: Studies of postmenopausal breast cancer have reported positive associations with body size and composition but it is uncertain whether these are due to non-adipose, adipose mass, or central adiposity, and whether they are limited to subgroups defined by age or tumor characteristics. Methods: In a prospective cohort study of women ages 27 to 75, body measurements were taken directly; fat mass and fat-free mass being estimated by bioelectrical impedance analysis, and central adiposity by waist circumference. Among 13,598 women followed on average for 9.1 years, 357 invasive breast cancers were ascertained via the population cancer registry. Data were obtained on estrogen receptor and progesterone receptor status, grade, and stage. Results: Estimates of body size such as fat-free mass [hazard ratio per 10 kg increase = 1.45, 95% confidence interval (CI) 1.16-1.82], fat mass (hazard ratio per 10 kg increase = 1.18, 95% CI, 1.06-1.31), and waist circumference (hazard ratio per 10 cm increase = 1.13, 95% CI, 1.03-1.24) were associated with breast cancer risk. There was no association with risk before 15 years postmenopause. About 15 years after menopause, risk increased sharply and remained elevated. There was some evidence that this association might be stronger for estrogen receptor-positive and poorly differentiated tumors but no evidence that it differed by stage. Conclusion: Given that elements of body size and composition are positively associated with breast cancer risk, although not until 15 or more years postmenopause, it is possible that women could reduce risk by maintaining ideal body weight after menopause.

Background: Red meat and processed meat consumption have been associated with increased risk of colorectal cancer in some, but not all, relevant cohort studies. Evidence on the relationship between risk of colorectal cancer and poultry and fish consumption is inconsistent. Methods: We conducted a prospective cohort study of 37,112 residents of Melbourne, Australia recruited from 1990 to 1994. Diet was measured with a food frequency questionnaire. We categorized the frequency of fresh red meat, processed meat, chicken, and fish consumption into approximate quartiles. Adenocarcinomas of the colon or rectum were ascertained via the Victorian Cancer Registry. Results: We identified 283 colon cancers and 169 rectal cancers in an average of 9 years of follow-up. For rectal cancer, the hazard ratios [95% confidence intervals (95% CI)] in the highest quartile of consumption of fresh red meat and processed meat were 2.3 (1.2–4.2; P for trend = 0.07) and 2.0 (1.1–3.4; P for trend = 0.09), respectively. The corresponding hazard ratios (95% CIs) for colon cancer were 1.1 (0.7–1.6; P for trend = 0.9) and 1.3 (0.9–1.9; P for trend = 0.06). However, for neither type of meat was the heterogeneity between subsites significant. Chicken consumption was weakly negatively associated with colorectal cancer (hazard ratio highest quartile, 0.7; 95% CI, 0.6–1.0; P for trend = 0.03), whereas hazard ratios for fish consumption were close to unity. Conclusion: Consumption of fresh red meat and processed meat seemed to be associated with an increased risk of rectal cancer. Consumption of chicken and fish did not increase risk.

Background: Several studies of male colon cancer have found positive associations with body size and composition. It is uncertain whether this relationship is due to non-adipose mass, adipose mass, distribution of adipose mass such as central adiposity, or all three. Methods: In a prospective cohort study of men aged 27–75 at recruitment in 1990–1994, body measurements were taken by interviewers. Fat mass and fat-free mass (FFM) were estimated from bioelectrical impedance analysis. Waist circumference and waist-to-hips ratio (WHR) estimated central adiposity. Incident colon cancers were ascertained via the population cancer registry. Altogether, 16,556 men contributed 145,433 person-years and 153 colon cancers. Results: Rate ratios (RRs) comparing men in the fourth quartile with those in the first quartile were as follows: FFM 2.3 [95% confidence interval (CI) 1.4–3.7]; height 1.9 (95% CI 1.1–3.1); waist circumference 2.1 (95% CI 1.3–3.5); WHR 2.1 (95% CI 1.3–3.4); fat mass 1.8 (95% CI 1.1–3.0); and body mass index 1.7 (95% CI 1.1–2.8). When continuous measures of FFM and WHR were modeled together, the RR for FFM per 10 kg was 1.37 (95% CI 1.04–1.80) and the RR for WHR per 0.1 unit was 1.65 (95% CI 1.28–2.13). After adjustment for FFM and WHR, the RRs for fat mass and body mass index were no longer statistically significant. Conclusion: Male colon cancer appears to be related to body size and composition by two different pathways, via central adiposity and via non-adipose mass.

Background and Aims: Colorectal cancer (CRC) is one of the most preventable and treatable cancers when detected early via screening. The current screening guidelines for CRC recommend exams only based on age, family history, and previous screening results. Multiple environmental and lifestyle risk factors, however, have been established or suspected for CRC, as have many common genetic susceptibility loci. It is critical to utilize this information to better stratify individuals into low- and high-risk groups for optimized and personalized screening and intervention recommendations. Methods: Using data from two large consortia (8421 CRC cases and 9767 controls): the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and the Colorectal Transdisciplinary study (CORECT), we developed risk prediction models for men and women based on family history, environmental and lifestyle risk factors, and known CRC susceptibility loci identified through genome-wide association studies. We constructed an environmental risk score (E-score) as a weighted sum of 19 established or potential environmental and lifestyle risk factors for CRC with weights obtained from a multivariate logistic regression analysis. Similarly, we also constructed a genetic risk score (G-score) using 64 common variants associated with CRC risk. We evaluated the discriminatory accuracy of risk prediction models by calculating the area under the Receiver Operating Characteristic curve (AUC), correcting for potential overestimating by using the training data set. Our models also estimate absolute risk of developing CRC given various risk profiles, and provide recommended ages for the first endoscopic screening exam. Results: Both the E-score and the G-score are independent predictors of CRC risk, and models that incorporate both scores improve the discriminatory accuracy significantly compared to family history-only models. Compared to the model that includes only family history, the E-score significantly improves the discriminatory accuracy for both men (AUC = 0.62 vs. 0.53, p-value < 1e-5 ) and women (AUC = 0.60 vs. 0.52, p-value < 1e-5 ). The G-score also significantly improves the discriminatory accuracy for both men (AUC = 0.60 vs. 0.53, p-value < 1e-5 ) and women (AUC = 0.60 vs. 0.52, p-value < 1e-5 ) over the family history-only model. Compared to the model with family history and E-score, the inclusion of the G-score in the model further improves the discriminatory accuracy for both men (AUC = 0.65 vs. 0.62, p-value = 0.0152) and women (AUC = 0.63 vs. 0.60, p-value = 0.0005). Based on the 10-year risk estimates of developing CRC, the difference in recommended age to start screening for the top 90% and the bottom 10% of risk score ranges from 12 to 14 years depending on sex and status of CRC family history. Conclusions: Our risk prediction models incorporating both comprehensive environmental and lifestyle risk factors, and known CRC common genetic variants provide more accurate estimation of CRC risk. These models will be useful for recommending individually tailored screening and intervention strategies to prevent this common cancer. This abstract is also being presented as Poster B17. Citation Format: Jihyoun Jeon, Sonja I. Berndt, Hermann Brenner, Peter T. Campbell, Andrew T. Chan, Jenny Chang-Claude, Mengmeng Du, Graham Giles, Jian Gong, Stephen B. Gruber, Tabitha A. Harrison, Michael Hoffmeister, Loic LeMarchand, Li Li, John D. Potter, Gad Rennert, Robert E. Schoen, Martha L. Slattery, Emily White, Michael O. Woods, Ulrike Peters, Li Hsu. Comprehensive colorectal cancer risk prediction to inform personalized screening and intervention. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr PR17.

There is growing evidence that inflammation and infection play important roles in the etiology of prostate cancer. As the chemokine network is directly involved in inflammation and infectious diseases, we tested for an association between six common putative functional variants and prostate cancer risk using an Australian case-control study. We measured CCL5 −403G>A, CXCL12 +801G>A, CCR2V64I (G>A), CCR5Δ32, CX3CR1V249I (G>A), and CX3CR1T280M (C>T) for 815 cases and 738 controls. Of these, only CXCL12 +801G>A has previously been tested and found to be associated with prostate cancer risk. We found no significant associations with prostate cancer risk (all P > 0.4). All per allele odds ratios ranged from 0.96 (95% confidence intervals, 0.80-1.16) to 1.06 (95% confidence intervals, 0.90-1.23). This suggests that these common chemokine and chemokine receptor variants do not play a major, if any, role in susceptibility to prostate cancer. (Cancer Epidemiol Biomarkers Prev 2008;17(12):3615–7)

A recent study from deCode reported an association between common variants in the region 8q24 and prostate cancer risk. The strongest association was found with the single nucleotide polymorphism rs1447295. We genotyped 821 prostate cancer cases and 732 population controls for rs1447295 to test the association between this common variant and prostate cancer risk, and examine whether this association depends on Gleason score. Our case-control study confirmed the association between rs1447295 and prostate cancer risk (P = 0.0005). The odds ratio (OR) for prostate cancer was 1.52 [95% confidence interval (CI), 1.20-1.93] for carriers of any A allele compared with noncarriers. The OR for Gleason score 5 to 6 prostate cancer (1.48; 95% CI, 1.13-1.95) was similar to the OR for Gleason score 7 to 10 prostate cancer (1.58; 95% CI, 1.18-2.11, P for heterogeneity = 0.7). We conclude that the A allele of rs1447295 is associated with a higher risk of prostate cancer regardless of tumor aggressiveness, suggesting that such a variant, or a variant in linkage disequilibrium with it, plays a role early in prostate carcinogenesis. (Cancer Epidemiol Biomarkers Prev 2007;16(3):610–2)

Vitamin D receptor (VDR), a member of the steroid/thyroid hormone nuclear receptor family, is bound by the steroid hormone 1,25-dihydroxyvitamin D3, which is thought to play a role in the etiology and progression of prostate cancer. Polymorphisms in the VDR gene have been associated with prostate cancer risk, although findings are inconclusive. The purpose of this study was to determine if VDR polymorphisms were associated with prostate cancer risk using a large, Australian population–based study of 812 cases and 713 controls frequency-matched by age. As the 3′ region polymorphisms are in strong linkage disequilibrium, for joint effects, we only evaluated the common g.60890G > A polymorphism with the unlinked g.27823C > T (5′ region) polymorphism. Allele frequencies were similar in cases and controls (g.27823C > T, 36% versus 36%; g.60890 G>A, 41% versus 43%). No genotypes were individually associated with prostate cancer risk (all P > 0.3). All nine possible genotype combinations were evident, and although the g.27823CT/g.60890GA combination was nominally more prevalent in controls (24%) than in cases (19%, P = 0.03), there was no difference in the combined genotype distribution between cases and controls (P = 0.2). The associations of risk with genotype were between 0.91 and 1.03, all with 95% confidence intervals within 0.81 to 1.15. In conclusion, VDR polymorphisms either alone or in combination do not seem to contribute appreciably to prostate cancer risk.