1 MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
2 HuGeF, Human Genetics Foundation, Torino, Italy
3 International Agency for Research on Cancer, Lyon, France
4 Department of Biobank research, Umeå University, Sweden
5 Department of Community Medicine UiT- The Arctic University of Norway, Tromso, Norway
6 IRAS Environmental Epidemiology Division, Utrecht, The Netherlands
7 Julius Center, Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
Purpose: Lung cancer represents the first cause of death from cancer worldwide, despite advancements in therapies and imaging. Survival improvement remains hampered by the lack of understanding of the molecular mechanisms driving lung carcinogenesis. Building upon recent studies identifying differential dynamics in the epigenetic response to exposure to tobacco smoke, we propose here to explore the contribution of these DNA methylation markers to smoking-induced lung cancer profiles and assess the benefit of their use compared to classical smoking-related metrics in a predictive context.
Methods: We performed a nested case-control study within two prospective cohorts: the Italian component of the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Norwegian Women and Cancer cohort (NOWAC). For each of the participants (N=377 from Italy and N=249 from Norway), genome-wide methylation profiles were acquired from blood samples collected at enrolment using the Illumina-HM450 DNA methylation array. Full-resolution association studies used logistic regressions controlling for technical variations and a set of confounders. The discriminatory performances of the logistic models were subsequently characterized by the area under the receiver operating characteristic curve (AUC). Disease-relevant biomarkers were subsequently explored with respect to their association to smoking exposure, and we investigated the persistence of these signals after smoking cessation.
Results: The methylation at 9 CpG sites was associated with lung cancer risk (FDR5%). Of these, 5 were classified as persistent, 1 as reversible markers of smoking. Comparison of the predictive abilities of these 6 biomarkers with smoking status showed that the inclusion of disease-associated CpG sites moderately but systematically improved discriminatory performances of the logistic models (AUC for smoking=76.3%; AUC for CpGs =83.9%, AUC total=84.4%).
Conclusions: Our work provides leads to possible epigenetic markers related to tobacco induced lung cancer.
Funding sources: COLT foundation, EU FP7-Exposomics grant, EU-ERC advanced grant (ERC-2008-AdG-232997)