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  1. Steffen A, Huerta JM, Weiderpass E, Bueno-de-Mesquita HB, May AM, Siersema PD, et al.
    Int J Cancer, 2015 Aug 01;137(3):646-57.
    PMID: 25598323 DOI: 10.1002/ijc.29432
    General obesity, as reflected by BMI, is an established risk factor for esophageal adenocarcinoma (EAC), a suspected risk factor for gastric cardia adenocarcinoma (GCC) and appears unrelated to gastric non-cardia adenocarcinoma (GNCC). How abdominal obesity, as commonly measured by waist circumference (WC), relates to these cancers remains largely unexplored. Using measured anthropometric data from 391,456 individuals from the European Prospective Investigation into Cancer and Nutrition (EPIC) study and 11 years of follow-up, we comprehensively assessed the association of anthropometric measures with risk of EAC, GCC and GNCC using multivariable proportional hazards regression. One hundred twenty-four incident EAC, 193 GCC and 224 GNCC were accrued. After mutual adjustment, BMI was unrelated to EAC, while WC showed a strong positive association (highest vs. lowest quintile HR = 1.19; 95% CI, 0.63-2.22 and HR = 3.76; 1.72-8.22, respectively). Hip circumference (HC) was inversely related to EAC after controlling for WC, while WC remained positively associated (HR = 0.35; 0.18-0.68, and HR=4.10; 1.94-8.63, respectively). BMI was not associated with GCC or GNCC. WC was related to higher risks of GCC after adjustment for BMI and more strongly after adjustment for HC (highest vs. lowest quintile HR = 1.91; 1.09-3.37, and HR = 2.23; 1.28-3.90, respectively). Our study demonstrates that abdominal, rather than general, obesity is an indisputable risk factor for EAC and also provides evidence for a protective effect of gluteofemoral (subcutaneous) adipose tissue in EAC. Our study further shows that general obesity is not a risk factor for GCC and GNCC, while the role of abdominal obesity in GCC needs further investigation.
  2. Carayol M, Leitzmann MF, Ferrari P, Zamora-Ros R, Achaintre D, Stepien M, et al.
    J Proteome Res, 2017 Sep 01;16(9):3137-3146.
    PMID: 28758405 DOI: 10.1021/acs.jproteome.6b01062
    Metabolomics is now widely used to characterize metabolic phenotypes associated with lifestyle risk factors such as obesity. The objective of the present study was to explore the associations of body mass index (BMI) with 145 metabolites measured in blood samples in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolites were measured in blood from 392 men from the Oxford (UK) cohort (EPIC-Oxford) and in 327 control subjects who were part of a nested case-control study on hepatobiliary carcinomas (EPIC-Hepatobiliary). Measured metabolites included amino acids, acylcarnitines, hexoses, biogenic amines, phosphatidylcholines, and sphingomyelins. Linear regression models controlled for potential confounders and multiple testing were run to evaluate the associations of metabolite concentrations with BMI. 40 and 45 individual metabolites showed significant differences according to BMI variations, in the EPIC-Oxford and EPIC-Hepatobiliary subcohorts, respectively. Twenty two individual metabolites (kynurenine, one sphingomyelin, glutamate and 19 phosphatidylcholines) were associated with BMI in both subcohorts. The present findings provide additional knowledge on blood metabolic signatures of BMI in European adults, which may help identify mechanisms mediating the relationship of BMI with obesity-related diseases.
  3. Obón-Santacana M, Lujan-Barroso L, Travis RC, Freisling H, Ferrari P, Severi G, et al.
    Cancer Epidemiol Biomarkers Prev, 2016 Jan;25(1):127-34.
    PMID: 26598536 DOI: 10.1158/1055-9965.EPI-15-0822
    BACKGROUND: Acrylamide was classified as "probably carcinogenic to humans (group 2A)" by the International Agency for Research on Cancer. Epithelial ovarian cancer (EOC) is the fourth cause of cancer mortality in women. Five epidemiological studies have evaluated the association between EOC risk and dietary acrylamide intake assessed using food frequency questionnaires, and one nested case-control study evaluated hemoglobin adducts of acrylamide (HbAA) and its metabolite glycidamide (HbGA) and EOC risk; the results of these studies were inconsistent.

    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.

    IMPACT: It is unlikely that dietary acrylamide exposure increases ovarian cancer risk; however, additional studies with larger sample size should be performed to exclude any possible association with EOC risk.

  4. Fortner RT, Hüsing A, Kühn T, Konar M, Overvad K, Tjønneland A, et al.
    Int J Cancer, 2017 Mar 15;140(6):1317-1323.
    PMID: 27935083 DOI: 10.1002/ijc.30560
    Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimination. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigated for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selection process; biomarkers were retained at p 
  5. Duarte-Salles T, Misra S, Stepien M, Plymoth A, Muller D, Overvad K, et al.
    Cancer Prev Res (Phila), 2016 Sep;9(9):758-65.
    PMID: 27339170 DOI: 10.1158/1940-6207.CAPR-15-0434
    We previously identified osteopontin (OPN) as a promising marker for the early detection of hepatocellular carcinoma (HCC). In this study, we investigated the association between prediagnostic circulating OPN levels and HCC incidence in a large population-based cohort. A nested case-control study was conducted within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. During a mean follow-up of 4.8 years, 100 HCC cases were identified. Each case was matched to two controls and OPN levels were measured in baseline plasma samples. Viral hepatitis, liver function, and α-fetoprotein (AFP) tests were also conducted. Conditional logistic regression models were used to calculate multivariable odds ratio (OR) and 95% confidence intervals (95% CI) for OPN levels in relation to HCC. Receiver operating characteristics curves were constructed to determine the discriminatory accuracy of OPN alone or in combination with other liver biomarkers in the prediction of HCC. OPN levels were positively associated with HCC risk (per 10% increment, ORmultivariable = 1.30; 95% CI, 1.14-1.48). The association was stronger among cases diagnosed within 2 years of follow-up. Adding liver function tests to OPN improved the discriminatory performance for subjects who developed HCC (AUC = 0.86). For cases diagnosed within 2 years, the combination of OPN and AFP was best able to predict HCC risk (AUC = 0.88). The best predictive model for HCC in this low-risk population is OPN in combination with liver function tests. Within 2 years of diagnosis, the combination of OPN and AFP best predicted HCC development, suggesting that measuring OPN and AFP could identify high-risk groups independently of a liver disease diagnosis. Cancer Prev Res; 9(9); 758-65. ©2016 AACR.
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