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.
IMPACT: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk.
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.
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.
IMPACT: Future studies should be designed for identification of rare variants with large effect sizes or common variants with small effect sizes.
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.
IMPACT: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.
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.
IMPACT: Abnormal EGFR GCN is a potential biomarker for identifying OPMD that are at risk of malignant transformation. Cancer Epidemiol Biomarkers Prev; 25(6); 927-35. ©2016 AACR.
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.
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.
IMPACT: The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.
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.
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.
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.
IMPACT: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.
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.
IMPACT: Some HPV16 E6 seropositive individuals without diagnosed HPV-driven cancer, especially those with seropositivity against other HPV16 proteins, may harbor a biologically relevant HPV16 infection.
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.
IMPACT: Further studies are warranted to better clarify these preliminary observations.
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.
IMPACT: Our finding suggests that factors involved in telomere length maintenance are involved in NPC pathogenesis.
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.
IMPACT: Biological mechanisms for a potential causal role of H. pylori in colorectal carcinogenesis need to be elucidated, and subsequently whether H. pylori eradication may decrease colorectal cancer incidence.
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.
IMPACT: Our findings in prospectively ascertained serum samples contradict the existing literature on the association of F. nucleatum with colorectal cancer risk. Future prospective studies, specifically detecting F. nucleatum in stool or tissue biopsies, are needed to complement our findings.
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.
IMPACT: Our data add to global evidence that ovarian carcinogenesis may be promoted by an inflammatory milieu.
METHODS: Data on highest education attained were gathered for 459,170 participants (70% women) from 10 European countries. A relative index of inequality (RII) based on adult education was calculated for comparability across countries and generations. Cox regression models were applied to estimate relative inequality in pancreatic cancer risk, stratifying by age, gender, and center, and adjusting for known pancreatic cancer risk factors.
RESULTS: A total of 1,223 incident pancreatic cancer cases were included after a mean follow-up of 13.9 (±4.0) years. An inverse social trend was found in models adjusted for age, sex, and center for both sexes [HR of RII, 1.27; 95% confidence interval (CI), 1.02-1.59], which was also significant among women (HR, 1.42; 95% CI, 1.05-1.92). Further adjusting by smoking intensity, alcohol consumption, body mass index, prevalent diabetes, and physical activity led to an attenuation of the RII risk and loss of statistical significance.
CONCLUSIONS: The present reanalysis does not sustain the existence of an independent social inequality influence on pancreatic cancer risk in Western European women and men, using an index based on adult education, the most relevant social indicator linked to individual lifestyles, in a context of very low pancreatic cancer survival from (quasi) universal public health systems.
IMPACT: The results do not support an association between education and risk of pancreatic cancer.
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.
IMPACT: More detailed studies on parity are needed to understand the possible effects of perinatal hormone changes in urothelial cells.