Background

The etiology of small intestinal cancer (SIC) is largely unknown, and there are very few epidemiological studies published to date. No studies have investigated abdominal adiposity in relation to SIC.

Methods

We investigated overall obesity and abdominal adiposity in relation to SIC in the European Prospective Investigation into Cancer and Nutrition (EPIC), a large prospective cohort of approximately half a million men and women from ten European countries. Overall obesity and abdominal obesity were assessed by body mass index (BMI), waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR). Multivariate Cox proportional hazards regression modeling was performed to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs). Stratified analyses were conducted by sex, BMI, and smoking status.

Results

During an average of 13.9 years of follow-up, 131 incident cases of SIC (including 41 adenocarcinomas, 44 malignant carcinoid tumors, 15 sarcomas and 10 lymphomas, and 21 unknown histology) were identified. WC was positively associated with SIC in a crude model that also included BMI (HR per 5-cm increase = 1.20, 95 % CI 1.04, 1.39), but this association attenuated in the multivariable model (HR 1.18, 95 % CI 0.98, 1.42). However, the association between WC and SIC was strengthened when the analysis was restricted to adenocarcinoma of the small intestine (multivariable HR adjusted for BMI = 1.56, 95 % CI 1.11, 2.17). There were no other significant associations.

Conclusion

WC, rather than BMI, may be positively associated with adenocarcinomas but not carcinoid tumors of the small intestine.

Impact

Abdominal obesity is a potential risk factor for adenocarcinoma in the small intestine.

Chromosome 5p15.33 has been identified as a lung cancer susceptibility locus, however the underlying causal mechanisms were not fully elucidated. Previous fine-mapping studies of this locus have relied on imputation or investigated a small number of known, common variants. This study represents a significant advance over previous research by investigating a large number of novel, rare variants, as well as their underlying mechanisms through telomere length. Variants for this fine-mapping study were identified through a targeted deep sequencing (average depth of coverage greater than 4000×) of 576 individuals. Subsequently, 4652 SNPs, including 1108 novel SNPs, were genotyped in 5164 cases and 5716 controls of European ancestry. After adjusting for known risk loci, rs2736100 and rs401681, we identified a new, independent lung cancer susceptibility variant in LPCAT1: rs139852726 (OR = 0.46, P = 4.73×10(-9)), and three new adenocarcinoma risk variants in TERT: rs61748181 (OR = 0.53, P = 2.64×10(-6)), rs112290073 (OR = 1.85, P = 1.27×10(-5)), rs138895564 (OR = 2.16, P = 2.06×10(-5); among young cases, OR = 3.77, P = 8.41×10(-4)). In addition, we found that rs139852726 (P = 1.44×10(-3)) was associated with telomere length in a sample of 922 healthy individuals. The gene-based SKAT-O analysis implicated TERT as the most relevant gene in the 5p15.33 region for adenocarcinoma (P = 7.84×10(-7)) and lung cancer (P = 2.37×10(-5)) risk. In this largest fine-mapping study to investigate a large number of rare and novel variants within 5p15.33, we identified novel lung and adenocarcinoma susceptibility loci with large effects and provided support for the role of telomere length as the potential underlying mechanism.

The role of amount and type of dietary fat consumption in the etiology of hepatocellular carcinoma (HCC) is poorly understood, despite suggestive biological plausibility. The associations of total fat, fat subtypes and fat sources with HCC incidence were investigated in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, which includes 191 incident HCC cases diagnosed between 1992 and 2010. Diet was assessed by country-specific, validated dietary questionnaires. A single 24-hr diet recall from a cohort subsample was used for measurement error calibration. Hazard ratios (HR) and 95% confidence intervals (95% CI) were estimated from Cox proportional hazard models. Hepatitis B and C viruses (HBV/HCV) status and biomarkers of liver function were assessed separately in a nested case-control subset with available blood samples (HCC = 122). In multivariable calibrated models, there was a statistically significant inverse association between total fat intake and risk of HCC (per 10 g/day, HR = 0.80, 95% CI: 0.65-0.99), which was mainly driven by monounsaturated fats (per 5 g/day, HR = 0.71, 95% CI: 0.55-0.92) rather than polyunsaturated fats (per 5 g/day, HR = 0.92, 95% CI: 0.68-1.25). There was no association between saturated fats (HR = 1.08, 95% CI: 0.88-1.34) and HCC risk. The ratio of polyunsaturated/monounsaturated fats to saturated fats was not significantly associated with HCC risk (per 0.2 point, HR = 0.86, 95% CI: 0.73-1.01). Restriction of analyses to HBV/HCV free participants or adjustment for liver function did not substantially alter the findings. In this large prospective European cohort, higher consumption of monounsaturated fats is associated with lower HCC risk.

Neopterin may be relevant for colorectal cancer (CRC) development, as a biomarker of cellular immune activity exerting pleiotropic effects on cellular ageing, oxidative stress, and inflammation. So far, the association between prediagnostic neopterin and colon and rectal cancer risk has not been evaluated in human populations. A nested case-control study was conducted within the European Prospective Investigation into Cancer and Nutrition cohort using data on plasma concentrations of total neopterin (T-N, sum of neopterin and 7,8-dihydroneopterin) in 830 incident CRC case patients (561 colon and 269 rectal) matched within risk sets to 830 control participants. A subsequent replication study used data from the Hordaland Health Study, where 173 CRC case patients have been diagnosed among 6594 healthy participants over 12 years of follow-up. After multivariable adjustment for a priori chosen CRC risk factors, a "U-shaped" association of T-N with CRC was revealed. Compared with the second quintile of the T-N distribution, the relative risks for the first, third, fourth, and fifth quintiles were 2.37 (95% CI = 1.66 to 3.39), 1.24 (95% CI = 0.87 to 1.77), 1.55 (95% CI = 1.08 to 2.22), and 2.31 (95% CI = 1.63 to 3.27), respectively. Replication of these associations within the Hordaland Health Study yielded similar results. No differences have been observed when the associations were explored by colon and rectal cancer site (two-sided P difference = .87) and after excluding case patients diagnosed within the first four follow-up years. These novel findings provide evidence of the role of both suppressed and activated cell-mediated immunity as reflected by prediagnostic T-N concentrations in the development of CRC.

Despite the potential cancer preventive effects of flavonoids and lignans, their ability to reduce pancreatic cancer risk has not been demonstrated in epidemiological studies. Our aim was to examine the association between dietary intakes of flavonoids and lignans and pancreatic cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. A total of 865 exocrine pancreatic cancer cases occurred after 11.3 years of follow-up of 477,309 cohort members. Dietary flavonoid and lignan intake was estimated through validated dietary questionnaires and the US Department of Agriculture (USDA) and Phenol Explorer databases. Hazard ratios (HR) and 95% confidence intervals (CIs) were calculated using age, sex and center-stratified Cox proportional hazards models, adjusted for energy intake, body mass index (BMI), smoking, alcohol and diabetes status. Our results showed that neither overall dietary intake of flavonoids nor of lignans were associated with pancreatic cancer risk (multivariable-adjusted HR for a doubling of intake = 1.03, 95% CI: 0.95-1.11 and 1.02; 95% CI: 0.89-1.17, respectively). Statistically significant associations were also not observed by flavonoid subclasses. An inverse association between intake of flavanones and pancreatic cancer risk was apparent, without reaching statistical significance, in microscopically confirmed cases (HR for a doubling of intake = 0.96, 95% CI: 0.91-1.00). In conclusion, we did not observe an association between intake of flavonoids, flavonoid subclasses or lignans and pancreatic cancer risk in the EPIC cohort.

Background

Increased serum neopterin had been described in older age two decades ago. Neopterin is a biomarker of systemic adaptive immune activation that could be potentially implicated in metabolic syndrome (MetS). Measurements of waist circumference, triglycerides, high-density lipoprotein cholesterol (HDLC), systolic and diastolic blood pressure, glycated hemoglobin as components of MetS definition, and plasma total neopterin concentrations were performed in 594 participants recruited in the European Prospective Investigation into Cancer and Nutrition (EPIC).

Results

Higher total neopterin concentrations were associated with reduced HDLC (9.7 %, p < 0.01 for men and 9.2 %, p < 0.01 for women), whereas no association was observed with the rest of the MetS components as well as with MetS overall (per 10 nmol/L: OR = 1.42, 95 % CI = 0.85-2.39 for men and OR = 1.38, 95 % CI = 0.79-2.43).

Conclusions

These data suggest that high total neopterin concentrations are cross-sectionally associated with reduced HDLC, but not with overall MetS.

Most men diagnosed with prostate cancer will experience indolent disease; hence, discovering genetic variants that distinguish aggressive from nonaggressive prostate cancer is of critical clinical importance for disease prevention and treatment. In a multistage, case-only genome-wide association study of 12,518 prostate cancer cases, we identify two loci associated with Gleason score, a pathological measure of disease aggressiveness: rs35148638 at 5q14.3 (RASA1, P=6.49 × 10(-9)) and rs78943174 at 3q26.31 (NAALADL2, P=4.18 × 10(-8)). In a stratified case-control analysis, the SNP at 5q14.3 appears specific for aggressive prostate cancer (P=8.85 × 10(-5)) with no association for nonaggressive prostate cancer compared with controls (P=0.57). The proximity of these loci to genes involved in vascular disease suggests potential biological mechanisms worthy of further investigation.

Background

Individual studies have suggested that circulating carotenoids, retinol, or tocopherols may be associated with prostate cancer risk, but the studies have not been large enough to provide precise estimates of associations, particularly by stage and grade of disease.

Objective

The objective of this study was to conduct a pooled analysis of the associations of the concentrations of 7 carotenoids, retinol, α-tocopherol, and γ-tocopherol with risk of prostate cancer and to describe whether any associations differ by stage or grade of the disease or other factors.

Design

Principal investigators of prospective studies provided individual participant data for prostate cancer cases and controls. Risk by study-specific fifths of each biomarker was estimated by using multivariable-adjusted conditional logistic regression in matched case-control sets.

Results

Data were available for up to 11,239 cases (including 1654 advanced stage and 1741 aggressive) and 18,541 controls from 15 studies. Lycopene was not associated with overall risk of prostate cancer, but there was statistically significant heterogeneity by stage of disease, and the OR for aggressive disease for the highest compared with the lowest fifth of lycopene was 0.65 (95% CI: 0.46, 0.91; P-trend = 0.032). No other carotenoid was significantly associated with overall risk of prostate cancer or with risk of advanced-stage or aggressive disease. For retinol, the OR for the highest compared with the lowest fifth was 1.13 (95% CI: 1.04, 1.22; P-trend = 0.015). For α-tocopherol, the OR for the highest compared with the lowest fifth was 0.86 (95% CI: 0.78, 0.94; P-trend < 0.001), with significant heterogeneity by stage of disease; the OR for aggressive prostate cancer was 0.74 (95% CI: 0.59, 0.92; P-trend = 0.001). γ-Tocopherol was not associated with risk.

Conclusions

Overall prostate cancer risk was positively associated with retinol and inversely associated with α-tocopherol, and risk of aggressive prostate cancer was inversely associated with lycopene and α-tocopherol. Whether these associations reflect causal relations is unclear.

Objectives

To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age.

Design

Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa.

Setting

Multiple institutions that were members of international PRACTICAL consortium.

Participants

All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men.

Main outcome measures

Prediction with hazard score of age of onset of aggressive cancer in validation set.

Results

In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P<10^-16). When men in the validation set with high scores (>98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score.

Conclusions

Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.

We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR_98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR_98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR_98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.