Principal Investigator: Dr Ioanna Tzoulaki
Department: Epidemiology and Biostatistics, London, W2 1PG, United Kingdom
Institution: Imperial College London
Lead Collaborators: 1) Dr Konstantinos Tsilidis 2) Dr Marc Gunter
Collaborating Institutions and Addresses:
1) University of Ioannina, School of Medicine, Department of Hygiene and Epidemiology, S. Niarchos Avenue, Ioannina, 45110, Greece
2) International Agency for Research on Cancer, Nutrition and Metabolism, 150 Cours Albert Thomas, Lyon, 69372, France.
Tags: 19266, cancer, environment, EWAS, exposome, risk prediction
1a: Within the United Kingdom cancer is a leading cause of mortality, estimated to contribute to over a quarter of deaths, and is the leading cause of death before the age of 75. Our lifestyle is known to play an important role in our predisposition to cancer and often acts in concert with inherited genetic risk factors. However exactly which components of the environment contribute towards cancer and their magnitude is yet to be elucidated across many cancer types. This project aims to further refine this understanding and to ascertain if this can be translated into improved cancer risk prediction models.
1b: The furthering of our knowledge of which components of our environmental exposure contribute towards the risk of cancer, and their relative contribution, would provide substantial benefits to the public in terms of both the prevention and the treatment of cancer. In terms of the former it would help provide greater information and clarity to health professionals and the public on how best to minimise the future risk of developing cancer. While for the later it would provide further information for allied researchers investigating the mechanistic aspects of cancer development, which itself is important in the development of cancer treatments.
1c: We will undertake this project by ascertaining if there are statistically significant differences in the historic environmental exposure and biomarkers of subjects subsequently diagnosed with cancer compared to those who were not. These results will then be incorporated into cancer specific risk prediction models, utilising other risk factors as well as genetic risk factors from consortia studies.
1d: This project will require access to the full cohort.