METHODS: We conducted a meta-analysis of four NPC GWAS among Chinese individuals (2,152 cases; 3,740 controls). Forty-three noteworthy findings outside the MHC region were identified and targeted for replication in a pooled analysis of four independent case-control studies across three regions in Asia (4,716 cases; 5,379 controls). A meta-analysis that combined results from the initial GWA and replication studies was performed.

RESULTS: In the combined meta-analysis, rs31489, located within the CLPTM1L/TERT region on chromosome 5p15.33, was strongly associated with NPC (OR = 0.81; P value 6.3 × 10(-13)). Our results also provide support for associations reported from published NPC GWAS-rs6774494 (P = 1.5 × 10(-12); located in the MECOM gene region), rs9510787 (P = 5.0 × 10(-10); located in the TNFRSF19 gene region), and rs1412829/rs4977756/rs1063192 (P = 2.8 × 10(-8), P = 7.0 × 10(-7), and P = 8.4 × 10(-7), respectively; located in the CDKN2A/B gene region).

CONCLUSIONS: We have identified a novel association between genetic variation in the CLPTM1L/TERT region and NPC. Supporting our finding, rs31489 and other SNPs in this region have been reported to be associated with multiple cancer sites, candidate-based studies have reported associations between polymorphisms in this region and NPC, the TERT gene has been shown to be important for telomere maintenance and has been reported to be overexpressed in NPC, and an EBV protein expressed in NPC (LMP1) has been reported to modulate TERT expression/telomerase activity.

METHODS: A nested case-control study in nonsmoking postmenopausal women (334 cases, 417 controls) was conducted within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Unconditional logistic regression models were used to estimate ORs and 95% confidence intervals (CI) for the association between HbAA, HbGA, HbAA+HbGA, and HbGA/HbAA and EOC and invasive serous EOC risk.

RESULTS: No overall associations were observed between biomarkers of acrylamide exposure analyzed in quintiles and EOC risk; however, positive associations were observed between some middle quintiles of HbGA and HbAA+HbGA. Elevated but nonstatistically significant ORs for serous EOC were observed for HbGA and HbAA+HbGA (ORQ5vsQ1, 1.91; 95% CI, 0.96-3.81 and ORQ5vsQ1, 1.90; 95% CI, 0.94-3.83, respectively); however, no linear dose-response trends were observed.

CONCLUSION: This EPIC nested case-control study failed to observe a clear association between biomarkers of acrylamide exposure and the risk of EOC or invasive serous EOC.

METHODS: Individual participant data meta-analysis included 362,114 participants (43% women), from seven prospective cohort studies, free from cancer at enrollment. The WCRF/AICR diet score was based on: (i) energy-dense foods and sugary drinks, (ii) plant foods, (iii) red and processed meat, and (iv) alcoholic drinks. Cox proportional hazards regression was used to examine the association between the diet score and cancer risks. Adjusted, cohort-specific HRs were pooled using random-effects meta-analysis. Risk advancement periods (RAP) were calculated to quantify the time period by which the risk of cancer was postponed among those adhering to the recommendations.

RESULTS: After a median follow-up of 11 to 15 years across cohorts, 70,877 cancer cases were identified. Each one-point increase in the WCRF/AICR diet score [range, 0 (no) to 4 (complete adherence)] was significantly associated with a lower risk of total cancer [HR, 0.94; 95% confidence interval (CI), 0.92-0.97], cancers of the colorectum (HR, 0.84; 95% CI, 0.80-0.89) and prostate (HR, 0.94; 95% CI, 0.92-0.97), but not breast or lung. Adherence to an additional component of the WCRF/AICR diet score significantly postponed the incidence of cancer at any site by 1.6 years (RAP, -1.6; 95% CI, -4.09 to -2.16).

CONCLUSIONS: Adherence to WCRF/AICR dietary recommendations is associated with lower risk of cancer among older adults.

METHODS: We applied a multiplex serology assay to simultaneously measure antibody responses to 11 F. nucleatum antigens in prediagnostic serum samples from 485 colorectal cancer cases and 485 matched controls. Conditional logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CI).

RESULTS: We observed neither a statistically significant colorectal cancer risk association for antibodies to individual F. nucleatum proteins nor for combined positivity to any of the 11 proteins (OR, 0.81; 95% CI, 0.62-1.06).

CONCLUSIONS: Antibody responses to F. nucleatum proteins in prediagnostic serum samples from a subset of colorectal cancer cases and matched controls within the EPIC study were not associated with colorectal cancer risk.

METHODS: We applied H. pylori multiplex serology to measure antibody responses to 13 H. pylori proteins in prediagnostic serum samples from 485 colorectal cancer cases and 485 matched controls nested within the EPIC study. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using multivariable conditional logistic regression to estimate the association of H. pylori overall and protein-specific seropositivity with odds of developing colorectal cancer.

RESULTS: Fifty-one percent of colorectal cancer cases were H. pylori seropositive compared with 44% of controls, resulting in an OR of 1.36 (95% CI, 1.00-1.85). Among the 13 individual H. pylori proteins, the association was driven mostly by seropositivity to Helicobacter cysteine-rich protein C (HcpC; OR: 1.66; 95% CI, 1.19-2.30) and Vacuolating cytotoxin A (VacA) (OR: 1.34; 95% CI, 0.99-1.82), the latter being nonstatistically significant only in the fully adjusted model.

CONCLUSIONS: In this prospective multicenter European study, antibody responses to H. pylori proteins, specifically HcpC and VacA, were associated with an increased risk of developing colorectal cancer.

METHODS: We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer-specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype.

RESULTS: There was no evidence of heterogeneous associations between risk factors and mortality by subtype (P adj > 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5-25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06-1.34)]; current versus never smoking [1.37 (1.27-1.47)], high versus low physical activity [0.43 (0.21-0.86)], age ≥30 years versus <20 years at first pregnancy [0.79 (0.72-0.86)]; >0-<5 years versus ≥10 years since last full-term birth [1.31 (1.11-1.55)]; ever versus never use of oral contraceptives [0.91 (0.87-0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen-progestin therapy [0.61 (0.54-0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02-1.21) for current versus never smoking.

CONCLUSIONS: We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype.

METHODS: EGFR GCN was examined by in situ hybridization (ISH) in biopsies from 78 patients with OPMD and 92 patients with early-stage (stages I and II) OSCC. EGFR ISH signals were scored by two pathologists and a category assigned by consensus. The data were correlated with patient demographics and clinical outcomes.

RESULTS: OPMD with abnormal EGFR GCN were more likely to undergo malignant transformation than diploid cases. EGFR genomic gain was detected in a quarter of early-stage OSCC, but did not correlate with clinical outcomes.

CONCLUSION: These data suggest that abnormal EGFR GCN has clinical utility as a biomarker for the detection of OPMD destined to undergo malignant transformation. Prospective studies are required to verify this finding. It remains to be determined if EGFR GCN could be used to select patients for EGFR-targeted therapies.

METHODS: The case-control portion of the study was conducted in nine UK centers with men ages 50-69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.

RESULTS: Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal.

CONCLUSIONS: We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk.

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 (P Bonferroni < 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.

METHODS: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium.

RESULTS: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10(-4); OR, 1.04; 95% confidence interval (CI), 1.02-1.07] and rs77928427 (P = 1.86 × 10(-4); OR, 1.04; 95% CI, 1.02-1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r(2) ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor-binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue.

CONCLUSION: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2.

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 (P GxE = 1.2 ×10-6, P Joint = 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.

METHODS: We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR).

RESULTS: We observed no significant association between genetic variants and prostate cancer survival.

CONCLUSIONS: Common genetic variants with large impact on prostate cancer survival were not observed in this study.

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: We conducted a nested case-control study in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort to evaluate C-reactive protein (CRP), IL6, and EOC risk by tumor characteristics. A total of 754 eligible EOC cases were identified; two controls (n = 1,497) were matched per case. We used multivariable conditional logistic regression to assess associations.

RESULTS: CRP and IL6 were not associated with overall EOC risk. However, consistent with prior research, CRP >10 versus CRP ≤1 mg/L was associated with higher overall EOC risk [OR, 1.67 (1.03-2.70)]. We did not observe significant associations or heterogeneity in analyses by tumor characteristics. In analyses stratified by waist circumference, inflammatory markers were associated with higher risk among women with higher waist circumference; no association was observed for women with normal waist circumference [e.g., IL6: waist ≤80: ORlog2, 0.97 (0.81-1.16); waist >88: ORlog2, 1.78 (1.28-2.48), Pheterogeneity ≤ 0.01].

CONCLUSIONS: Our data suggest that high CRP is associated with increased risk of overall EOC, and that IL6 and CRP may be associated with EOC risk among women with higher adiposity.

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.

METHODS: We used an analytic cohort of 333,919 women from the European Prospective Investigation into Cancer and Nutrition Cohort. Associations between hormonal factors and incident urothelial carcinoma (overall and by tumor grade, tumor aggressiveness, and non-muscle-invasive urothelial carcinoma) risk were evaluated using Cox proportional hazards models.

RESULTS: During a mean of 15 years of follow-up, 529 women developed urothelial carcinoma. In a model including number of full-term pregnancies (FTP), menopausal status, and menopausal hormone therapy (MHT), number of FTP was inversely associated with urothelial carcinoma risk (HR≥5vs1 = 0.48; 0.25-0.90; P trend in parous women = 0.010) and MHT use (compared with nonuse) was positively associated with urothelial carcinoma risk (HR = 1.27; 1.03-1.57), but no dose response by years of MHT use was observed. No modification of HRs by smoking status was observed. Finally, sensitivity analyses in never smokers showed similar HR patterns for the number of FTP, while no association between MHT use and urothelial carcinoma risk was observed. Association between MHT use and urothelial carcinoma risk remained significant only in current smokers. No heterogeneity of the risk estimations in the final model was observed by tumor aggressiveness or by tumor grade. A positive association between MTH use and non-muscle-invasive urothelial carcinoma risk was observed.

CONCLUSIONS: Our results support that increasing the number of FTP may reduce urothelial carcinoma risk.