METHODS: To gain a more comprehensive picture on how these markers can modulate BC risk, alone or in conjunction, we performed simultaneous measurements of LTL and mtDNA copy number in up to 570 BC cases and 538 controls from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. As a first step, we measured LTL and mtDNA copy number in 96 individuals for which a blood sample had been collected twice with an interval of 15 years.

RESULTS: According to the intraclass correlation (ICC), we found very good stability over the time period for both measurements, with ICCs of 0.63 for LTL and 0.60 for mtDNA copy number. In the analysis of the entire study sample, we observed that longer LTL was strongly associated with increased risk of BC (OR 2.71, 95% CI 1.58-4.65, p = 3.07 × 10- 4 for highest vs. lowest quartile; OR 3.20, 95% CI 1.57-6.55, p = 1.41 × 10- 3 as a continuous variable). We did not find any association between mtDNA copy number and BC risk; however, when considering only the functional copies, we observed an increased risk of developing estrogen receptor-positive BC (OR 2.47, 95% CI 1.05-5.80, p = 0.04 for highest vs. lowest quartile).

METHODS: We built two models, for ER+ (ModelER+) and ER- tumors (ModelER-), respectively, in 281,330 women (51% postmenopausal at recruitment) from the European Prospective Investigation into Cancer and Nutrition cohort. Discrimination (C-statistic) and calibration (the agreement between predicted and observed tumor risks) were assessed both internally and externally in 82,319 postmenopausal women from the Women's Health Initiative study. We performed decision curve analysis to compare ModelER+ and the Gail model (ModelGail) regarding their applicability in risk assessment for chemoprevention.

RESULTS: Parity, number of full-term pregnancies, age at first full-term pregnancy and body height were only associated with ER+ tumors. Menopausal status, age at menarche and at menopause, hormone replacement therapy, postmenopausal body mass index, and alcohol intake were homogeneously associated with ER+ and ER- tumors. Internal validation yielded a C-statistic of 0.64 for ModelER+ and 0.59 for ModelER-. External validation reduced the C-statistic of ModelER+ (0.59) and ModelGail (0.57). In external evaluation of calibration, ModelER+ outperformed the ModelGail: the former led to a 9% overestimation of the risk of ER+ tumors, while the latter yielded a 22% underestimation of the overall BC risk. Compared with the treat-all strategy, ModelER+ produced equal or higher net benefits irrespective of the benefit-to-harm ratio of chemoprevention, while ModelGail did not produce higher net benefits unless the benefit-to-harm ratio was below 50. The clinical applicability, i.e. the area defined by the net benefit curve and the treat-all and treat-none strategies, was 12.7 × 10- 6 for ModelER+ and 3.0 × 10- 6 for ModelGail.

MATERIALS & METHODS: Here, we examined the potential of DNA methylation changes in 910 prediagnostic peripheral blood samples as a marker of exposure to tobacco smoke in a large multinational cohort.

RESULTS: We identified 748 CpG sites that were differentially methylated between smokers and nonsmokers, among which we identified novel regionally clustered CpGs associated with active smoking. Importantly, we found a marked reversibility of methylation changes after smoking cessation, although specific genes remained differentially methylated up to 22 years after cessation.

OBJECTIVE: To test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer.

DESIGN, SETTING, AND PARTICIPANTS: SNPs implicated in any phenotype other than prostate cancer (p≤10(-7)) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24,534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Odds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated.

RESULTS AND LIMITATIONS: A total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p=1.6×10(-6)), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95% CI 1.16-1.27; p=3.22×10(-18)). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86-0.94; p=2.5×10(-6)). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12, 95% CI 1.06-1.19; p=4.67×10(-5)); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL.

CONCLUSIONS: We did not identify new SNPs for aggressive prostate cancer. However, rs16844874 may provide preliminary genetic evidence on the role of the glycine pathway in prostate cancer etiology.

Methods: In 12 cohorts from 6 European countries, individual estimates of annual mean air pollution levels at the baseline residence were estimated by standardized land-use regression models developed within the ESCAPE and TRANSPHORM projects: particulate matter (PM) ≤2.5, ≤10, and 2.5-10 μm in diameter (PM2.5, PM10, and PMcoarse), PM2.5 absorbance, nitrogen oxides (NO2 and NOx) and elemental composition of PM. We estimated cohort-specific associations of air pollutant concentrations and traffic intensity with total, malignant, and nonmalignant brain tumor, in separate Cox regression models, adjusting for risk factors, and pooled cohort-specific estimates using random-effects meta-analyses.

Results: Of 282194 subjects from 12 cohorts, 466 developed malignant brain tumors during 12 years of follow-up. Six of the cohorts also had data on nonmalignant brain tumor, where among 106786 subjects, 366 developed brain tumor: 176 nonmalignant and 190 malignant. We found a positive, statistically nonsignificant association between malignant brain tumor and PM2.5 absorbance (hazard ratio and 95% CI: 1.67; 0.89-3.14 per 10-5/m3), and weak positive or null associations with the other pollutants. Hazard ratio for PM2.5 absorbance (1.01; 0.38-2.71 per 10-5/m3) and all other pollutants were lower for nonmalignant than for malignant brain tumors.

METHODS: We analysed the relationship between pre-diagnostic prolactin levels and the risk of in situ breast cancer overall, and by menopausal status and use of postmenopausal hormone therapy (HT) at blood donation. Conditional logistic regression was used to assess this association in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, including 307 in situ breast cancer cases and their matched control subjects.

RESULTS: We found a significant positive association between higher circulating prolactin levels and risk of in situ breast cancer among all women [pre-and postmenopausal combined, ORlog2=1.35 (95% CI 1.04-1.76), Ptrend=0.03]. No statistically significant heterogeneity was found between prolactin levels and in situ cancer risk by menopausal status (Phet=0.98) or baseline HT use (Phet=0.20), although the observed association was more pronounced among postmenopausal women using HT compared to non-users (Ptrend=0.06 vs Ptrend=0.35). In subgroup analyses, the observed positive association was strongest in women diagnosed with in situ breast tumors<4 years compared to ≥4 years after blood donation (Ptrend=0.01 vs Ptrend=0.63; Phet=0.04) and among nulliparous women compared to parous women (Ptrend=0.03 vs Ptrend=0.15; Phet=0.07).

OBJECTIVE: We examined the association between sweet-beverage consumption (including total, sugar-sweetened, and artificially sweetened soft drink and juice and nectar consumption) and pancreatic cancer risk.

DESIGN: The study was conducted within the European Prospective Investigation into Cancer and Nutrition cohort. A total of 477,199 participants (70.2% women) with a mean age of 51 y at baseline were included, and 865 exocrine pancreatic cancers were diagnosed after a median follow-up of 11.60 y (IQR: 10.10-12.60 y). Sweet-beverage consumption was assessed with the use of validated dietary questionnaires at baseline. HRs and 95% CIs were obtained with the use of multivariable Cox regression models that were stratified by age, sex, and center and adjusted for educational level, physical activity, smoking status, and alcohol consumption. Associations with total soft-drink consumption were adjusted for juice and nectar consumption and vice versa.

RESULTS: Total soft-drink consumption (HR per 100 g/d: 1.03; 95% CI: 0.99, 1.07), sugar-sweetened soft-drink consumption (HR per 100 g/d: 1.02; 95% CI: 0.97, 1.08), and artificially sweetened soft-drink consumption (HR per 100 g/d: 1.04; 95% CI: 0.98, 1.10) were not associated with pancreatic cancer risk. Juice and nectar consumption was inversely associated with pancreatic cancer risk (HR per 100 g/d: 0.91; 95% CI: 0.84, 0.99); this association remained statistically significant after adjustment for body size, type 2 diabetes, and energy intake.

METHODS: Multivariable-adjusted Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). After an average of 13.9 years of follow-up, there were 7024 incident prostate cancers and 934 prostate cancer deaths.

RESULTS: Height was not associated with total prostate cancer risk. Subgroup analyses showed heterogeneity in the association with height by tumour grade (P heterogeneity = 0.002), with a positive association with risk for high-grade but not low-intermediate-grade disease (HR for high-grade disease tallest versus shortest fifth of height, 1.54; 95% CI, 1.18-2.03). Greater height was also associated with a higher risk for prostate cancer death (HR = 1.43, 1.14-1.80). Body mass index (BMI) was significantly inversely associated with total prostate cancer, but there was evidence of heterogeneity by tumour grade (P heterogeneity = 0.01; HR = 0.89, 0.79-0.99 for low-intermediate grade and HR = 1.32, 1.01-1.72 for high-grade prostate cancer) and stage (P heterogeneity = 0.01; HR = 0.86, 0.75-0.99 for localised stage and HR = 1.11, 0.92-1.33 for advanced stage). BMI was positively associated with prostate cancer death (HR = 1.35, 1.09-1.68). The results for waist circumference were generally similar to those for BMI, but the associations were slightly stronger for high-grade (HR = 1.43, 1.07-1.92) and fatal prostate cancer (HR = 1.55, 1.23-1.96).

METHODS: A total of 4,666 controls were pooled from several studies of cancer and HPV seropositivity, all tested within the same laboratory. HPV16 E6 seropositive controls were classified as having (i) moderate [mean fluorescent intensity (MFI) ≥ 484 and <1,000] or (ii) high seroreactivity (MFI ≥ 1,000). Associations of moderate and high HPV16 E6 seroreactivity with (i) demographic risk factors; and seropositivity for (ii) other HPV16 proteins (E1, E2, E4, E7, and L1), and (iii) E6 proteins from non-HPV16 types (HPV6, 11, 18, 31, 33, 45, and 52) were evaluated.

RESULTS: Thirty-two (0.7%) HPV16 E6 seropositive controls were identified; 17 (0.4%) with moderate and 15 (0.3%) with high seroreactivity. High HPV16 E6 seroreactivity was associated with former smoking [odds ratio (OR), 5.5; 95% confidence interval (CI), 1.2-51.8], and seropositivity against HPV16 L1 (OR, 4.8; 95% CI, 1.3-15.4); E2 (OR, 7.7; 95% CI, 1.4-29.1); multiple HPV16 proteins (OR, 25.3; 95% CI, 2.6-119.6 for three HPV16 proteins beside E6) and HPV33 E6 (OR, 17.7; 95% CI, 1.9-81.8). No associations were observed with moderate HPV16 E6 seroreactivity.

CONCLUSIONS: High HPV16 E6 seroreactivity is rare among individuals without diagnosed cancer and was not explained by demographic factors.

METHODS: DNA methylation profiles (Illumina Infinium® HumanMethylation450 BeadChip) from 1941 individuals from four population-based European cohorts were analysed in relation to body mass index, waist circumference, waist-hip and waist-height ratio within a meta-analytical framework. In a subset of these individuals, data on genome-wide gene expression level, biomarkers of glucose and lipid metabolism were also available. Validation of methylation markers associated with all adiposity measures was performed in 358 individuals. Finally, we investigated the association of obesity-related methylation marks with breast, colorectal cancer and myocardial infarction within relevant subsets of the discovery population.

METHODS AND FINDINGS: The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed.

METHODS: A total of 1,065 incident colorectal cancer cases (colon, n = 667; rectal, n = 398) were matched (1:1) to control subjects. Serum flagellin- and LPS-specific IgA and IgG levels were quantitated by ELISA. Multivariable conditional logistic regression models were used to calculate ORs and 95% confidence intervals (CI), adjusting for multiple relevant confouding factors.

RESULTS: Overall, elevated anti-LPS and anti-flagellin biomarker levels were not associated with colorectal cancer risk. After testing potential interactions by various factors relevant for colorectal cancer risk and anti-LPS and anti-flagellin, sex was identified as a statistically significant interaction factor (Pinteraction < 0.05 for all the biomarkers). Analyses stratified by sex showed a statistically significant positive colorectal cancer risk association for men (fully-adjusted OR for highest vs. lowest quartile for total anti-LPS + flagellin, 1.66; 95% CI, 1.10-2.51; Ptrend, 0.049), whereas a borderline statistically significant inverse association was observed for women (fully-adjusted OR, 0.70; 95% CI, 0.47-1.02; Ptrend, 0.18).

CONCLUSION: In this prospective study on European populations, we found bacterial exposure levels to be positively associated to colorectal cancer risk among men, whereas in women, a possible inverse association may exist.