Context and aim: Several risks factors have been identified for cancer, and it has been estimated that more than 40% of cases in developed countries are preventable through the modulation of known modifiable risk factors. The overall objective of this thesis was to demonstrate that the analysis of genomic and epigenomic data integrated with well-characterised exposure and lifestyle data may be used to identify markers of environmental exposures and lifestyle and may contribute to increase our understanding of cancer aetiology.Results: We first describe how genomic and epigenomic signatures can be used to identify markers of exposure and decipher the aetiology of cancer. Then, we adopt the mutational signatures framework to contribute to the debate about the “bad luck” hypothesis for cancer and demonstrate that tobacco-related mutations are more strongly correlated with cancer risk than random mutations. We introduce a probabilistic model for the simulation of mutational signature data and compare the performance of the available methods for the identification of mutational signatures using both simulated and real data. Additionally, we introduce a new method for the identification of such signatures. Finally, we use methylation array data in an epidemiological study within the E3N cohort to investigate the association between exposure to Brominated Flame Retardants and Per- and polyfluoroalkyl substances, two organic pollutants that are known endocrine disrupting chemicals, and methylation in DNA from blood. Overall, our study does not provide evidence of methylation alterations at the level of the whole genome, in regions or in single CpGs. Suggestive evidence of alterations in the methylation of genes within plausible biological pathways (e.g. androgen response) warrants further investigations. Conclusion: Our work on the methodological aspects of mutational signature research introduces an original framework for measuring the performance of tools for the identification of mutational signatures that may serve as reference for future methodological or applied research. Our applications of both mutational signature and methylome research demonstrate the usefulness of such tools to assess exposures and elucidate their role in cancer aetiology.