• Added Value of Serum Hormone Measurements in Risk Prediction Models for Breast Cancer for Women Not Using Exogenous Hormones: Results from the EPIC Cohort.

      Hüsing, Anika; Fortner, Renée T; Kühn, Tilman; Overvad, Kim; Tjønneland, Anne; Olsen, Anja; Boutron-Ruault, Marie-Christine; Severi, Gianluca; Fournier, Agnes; Boeing, Heiner; Trichopoulou, Antonia; Benetou, Vassiliki; Orfanos, Philippos; Masala, Giovanna; Pala, Valeria; Tumino, Rosario; Fasanelli, Francesca; Panico, Salvatore; Bueno de Mesquita, H Bas; Peeters, Petra H; van Gills, Carla H; Quirós, J Ramón; Agudo, Antonio; Sánchez, Maria-Jose; Chirlaque, Maria-Dolores; Barricarte, Aurelio; Amiano, Pilar; Khaw, Kay-Tee; Travis, Ruth C; Dossus, Laure; Li, Kuanrong; Ferrari, Pietro; Merritt, Melissa A; Tzoulaki, Ioanna; Riboli, Elio; Kaaks, Rudolf (2017-08-01)
      Purpose: Circulating hormone concentrations are associated with breast cancer risk, with well-established associations for postmenopausal women. Biomarkers may represent minimally invasive measures to improve risk prediction models.Experimental Design: We evaluated improvements in discrimination gained by adding serum biomarker concentrations to risk estimates derived from risk prediction models developed by Gail and colleagues and Pfeiffer and colleagues using a nested case-control study within the EPIC cohort, including 1,217 breast cancer cases and 1,976 matched controls. Participants were pre- or postmenopausal at blood collection. Circulating sex steroids, prolactin, insulin-like growth factor (IGF) I, IGF-binding protein 3, and sex hormone-binding globulin (SHBG) were evaluated using backward elimination separately in women pre- and postmenopausal at blood collection. Improvement in discrimination was evaluated as the change in concordance statistic (C-statistic) from a modified Gail or Pfeiffer risk score alone versus models, including the biomarkers and risk score. Internal validation with bootstrapping (1,000-fold) was used to adjust for overfitting.Results: Among women postmenopausal at blood collection, estradiol, testosterone, and SHBG were selected into the prediction models. For breast cancer overall, model discrimination after including biomarkers was 5.3 percentage points higher than the modified Gail model alone, and 3.4 percentage points higher than the Pfeiffer model alone, after accounting for overfitting. Discrimination was more markedly improved for estrogen receptor-positive disease (percentage point change in C-statistic: 7.2, Gail; 4.8, Pfeiffer). We observed no improvement in discrimination among women premenopausal at blood collection.Conclusions: Integration of hormone measurements in clinical risk prediction models may represent a strategy to improve breast cancer risk stratification. Clin Cancer Res; 23(15); 4181-9. ©2017 AACR.
    • Do pancreatic cancer and chronic pancreatitis share the same genetic risk factors? A PANcreatic Disease ReseArch (PANDoRA) consortium investigation.

      Campa, Daniele; Pastore, Manuela; Capurso, Gabriele; Hackert, Thilo; Di Leo, Milena; Izbicki, Jakob R; Khaw, Kay-Tee; Gioffreda, Domenica; Kupcinskas, Juozas; Pasquali, Claudio; Macinga, Peter; Kaaks, Rudolf; Stigliano, Serena; Peeters, Petra H; Key, Timothy J; Talar-Wojnarowska, Renata; Vodicka, Pavel; Valente, Roberto; Vashist, Yogesh K; Salvia, Roberto; Papaconstantinou, Ioannis; Shimizu, Yasuhiro; Valsuani, Chiara; Zambon, Carlo Federico; Gazouli, Maria; Valantiene, Irena; Niesen, Willem; Mohelnikova-Duchonova, Beatrice; Hara, Kazuo; Soucek, Pavel; Malecka-Panas, Ewa; Bueno-de-Mesquita, H B As; Johnson, Theron; Brenner, Herman; Tavano, Francesca; Fogar, Paola; Ito, Hidemi; Sperti, Cosimo; Butterbach, Katja; Latiano, Anna; Andriulli, Angelo; Cavestro, Giulia Martina; Busch, Olivier R C; Dijk, Frederike; Greenhalf, William; Matsuo, Keitaro; Lombardo, Carlo; Strobel, Oliver; König, Anna-Katharina; Cuk, Katarina; Strothmann, Hendrik; Katzke, Verena; Cantore, Maurizio; Mambrini, Andrea; Oliverius, Martin; Pezzilli, Raffaele; Landi, Stefano; Canzian, Federico (2018-01-15)
      Pancreatic ductal adenocarcinoma (PDAC) is a very aggressive tumor with a five-year survival of less than 6%. Chronic pancreatitis (CP), an inflammatory process in of the pancreas, is a strong risk factor for PDAC. Several genetic polymorphisms have been discovered as susceptibility loci for both CP and PDAC. Since CP and PDAC share a consistent number of epidemiologic risk factors, the aim of this study was to investigate whether specific CP risk loci also contribute to PDAC susceptibility. We selected five common SNPs (rs11988997, rs379742, rs10273639, rs2995271 and rs12688220) that were identified as susceptibility markers for CP and analyzed them in 2,914 PDAC cases, 356 CP cases and 5,596 controls retrospectively collected in the context of the international PANDoRA consortium. We found a weak association between the minor allele of the PRSS1-PRSS2-rs10273639 and an increased risk of developing PDAC (ORhomozygous  = 1.19, 95% CI 1.02-1.38, p = 0.023). Additionally all the SNPs confirmed statistically significant associations with risk of developing CP, the strongest being PRSS1-PRSS2-rs10273639 (ORheterozygous  = 0.51, 95% CI 0.39-0.67, p = 1.10 × 10-6 ) and MORC4-rs 12837024 (ORhomozygous  = 2.07 (1.55-2.77, ptrend  = 0.7 × 10-11 ). Taken together, the results from our study do not support variants rs11988997, rs379742, rs10273639, rs2995271 and rs12688220 as strong predictors of PDAC risk, but further support the role of these SNPs in CP susceptibility. Our study suggests that CP and PDAC probably do not share genetic susceptibility, at least in terms of high frequency variants.
    • Plasma microRNAs as biomarkers of pancreatic cancer risk in a prospective cohort study.

      Duell, Eric J; Lujan-Barroso, Leila; Sala, Núria; Deitz McElyea, Samantha; Overvad, Kim; Tjonneland, Anne; Olsen, Anja; Weiderpass, Elisabete; Busund, Lill-Tove; Moi, Line; Muller, David; Vineis, Paolo; Aune, Dagfinn; Matullo, Giuseppe; Naccarati, Alessio; Panico, Salvatore; Tagliabue, Giovanna; Tumino, Rosario; Palli, Domenico; Kaaks, Rudolf; Katzke, Verena A; Boeing, Heiner; Bueno-de-Mesquita, H B As; Peeters, Petra H; Trichopoulou, Antonia; Lagiou, Pagona; Kotanidou, Anastasia; Travis, Ruth C; Wareham, Nick; Khaw, Kay-Tee; Ramon Quiros, Jose; Rodríguez-Barranco, Miguel; Dorronsoro, Miren; Chirlaque, María-Dolores; Ardanaz, Eva; Severi, Gianluca; Boutron-Ruault, Marie-Christine; Rebours, Vinciane; Brennan, Paul; Gunter, Marc; Scelo, Ghislaine; Cote, Greg; Sherman, Stuart; Korc, Murray (2017-09-01)
      Noninvasive biomarkers for early pancreatic ductal adenocarcinoma (PDAC) diagnosis and disease risk stratification are greatly needed. We conducted a nested case-control study within the Prospective Investigation into Cancer and Nutrition (EPIC) cohort to evaluate prediagnostic microRNAs (miRs) as biomarkers of subsequent PDAC risk. A panel of eight miRs (miR-10a, -10b, -21-3p, -21-5p, -30c, -106b, -155 and -212) based on previous evidence from our group was evaluated in 225 microscopically confirmed PDAC cases and 225 controls matched on center, sex, fasting status and age/date/time of blood collection. MiR levels in prediagnostic plasma samples were determined by quantitative RT-PCR. Logistic regression was used to model levels and PDAC risk, adjusting for covariates and to estimate area under the receiver operating characteristic curves (AUC). Plasma miR-10b, -21-5p, -30c and -106b levels were significantly higher in cases diagnosed within 2 years of blood collection compared to matched controls (all p-values <0.04). Based on adjusted logistic regression models, levels for six miRs (miR-10a, -10b, -21-5p, -30c, -155 and -212) overall, and for four miRs (-10a, -10b, -21-5p and -30c) at shorter follow-up time between blood collection and diagnosis (≤5 yr, ≤2 yr), were statistically significantly associated with risk. A score based on the panel showed a linear dose-response trend with risk (p-value = 0.0006). For shorter follow-up (≤5 yr), AUC for the score was 0.73, and for individual miRs ranged from 0.73 (miR-212) to 0.79 (miR-21-5p).
    • Pre-diagnostic copper and zinc biomarkers and colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition cohort.

      Stepien, Magdalena; Jenab, Mazda; Freisling, Heinz; Becker, Niels-Peter; Czuban, Magdalena; Tjønneland, Anne; Olsen, Anja; Overvad, Kim; Boutron-Ruault, Marie-Christine; Mancini, Francesca Romana; Savoye, Isabelle; Katzke, Verena; Kühn, Tilman; Boeing, Heiner; Iqbal, Khalid; Trichopoulou, Antonia; Bamia, Christina; Orfanos, Philippos; Palli, Domenico; Sieri, Sabina; Tumino, Rosario; Naccarati, Alessio; Panico, Salvatore; Bueno-de-Mesquita, H B As; Peeters, Petra H; Weiderpass, Elisabete; Merino, Susana; Jakszyn, Paula; Sanchez, Maria-Jose; Dorronsoro, Miren; Huerta, José María; Barricarte, Aurelio; Boden, Stina; van Guelpen, Behany; Wareham, Nick; Khaw, Kay-Tee; Bradbury, Kathryn E; Cross, Amanda J; Schomburg, Lutz; Hughes, David J (2017-07-01)
      Adequate intake of copper and zinc, two essential micronutrients, are important for antioxidant functions. Their imbalance may have implications for development of diseases like colorectal cancer (CRC), where oxidative stress is thought to be etiologically involved. As evidence from prospective epidemiologic studies is lacking, we conducted a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort to investigate the association between circulating levels of copper and zinc, and their calculated ratio, with risk of CRC development. Copper and zinc levels were measured by reflection X-ray fluorescence spectrometer in 966 cases and 966 matched controls. Multivariable adjusted odds ratios (OR) and 95% confidence intervals (CI) were calculated using conditional logistic regression and are presented for the fifth versus first quintile. Higher circulating concentration of copper was associated with a raised CRC risk (OR = 1.50; 95% CI: 1.06, 2.13; P-trend = 0.02) whereas an inverse association with cancer risk was observed for higher zinc levels (OR = 0.65; 95% CI: 0.43, 0.97; P-trend = 0.07). Consequently, the ratio of copper/zinc was positively associated with CRC (OR = 1.70; 95% CI: 1.20, 2.40; P-trend = 0.0005). In subgroup analyses by follow-up time, the associations remained statistically significant only in those diagnosed within 2 years of blood collection. In conclusion, these data suggest that copper or copper levels in relation to zinc (copper to zinc ratio) become imbalanced in the process of CRC development. Mechanistic studies into the underlying mechanisms of regulation and action are required to further examine a possible role for higher copper and copper/zinc ratio levels in CRC development and progression.