The Molecular and Environmental Epidemiology of Cancer

1
The Molecular and Environmental Epidemiology of
Cancer
Wei Xun, James Ellis, Laura Thomas, Lars Jarup,
Jake Bundy, Hector Keun, Paolo Vineis - Imperial
College London.
Background Within the EPIC prospective study
(N520,000) extensive research on cancer and
biomarkers has been conducted. A new gene has
been identified thanks to a GWAS (Hung et al,
Nature 2008, 1). In the GENAIR subproject, a
EU-funded project (P.I. P Vineis), we have
assessed the effect of exposure to environmental
pollutants on biological endpoints, such as DNA
adducts and mutations in p53 and Ras genes
(analyzed in plasma DNA), according to genotypes
for metabolism of the relevant carcinogens and
DNA repair (2-5).
Future plans
ESCAPE To investigate long-term effects on human
health of exposure to air pollution in Europe.
Involving 10 centres and 645,800 individual
participants across the region. Lung cancer
ESCAPE will estimate the effect of ambient air
pollution on life expectancy using data from
several cohorts with approximately 4000 incident
lung cancers. Exposure assessment current
spatial variation of long-term (annual) average
ambient PM(2.5 and 10), PM composition and NOx
concentrations in 23 European cities/areas (see
Figure 1).

Figure 1 ESCAPE exposure assessment locations
Validation of biomarkers in Europe ECNIS ECNIS
(Environmental Cancer Risk, Nutrition and
Individual Susceptibility) is a Network of
Excellence operating in the context of the 6th EU
Framework Programme for Research and Development
(FP6).The vision of ECNIS is the creation of a
dynamic research network which will work to
decrease cancer incidence by  Identifying
chemicals or other factors in the environment
which cause cancer,  Elucidating the mechanisms
by which lifestyle patterns increase or decrease
cancer risk,  Discovering genetic (hereditary)
factors which make individuals more or less
susceptible to cancer We maintain and update a
website (Figure 2) that includes a Molecular
Epidemiology database on biomarker research in
Europe.
Background work Log DNA adducts as dependent
variable and air pollutants as independent
variables (N928), GENAIR study. Multivariate
models adjusted by age, gender, education level,
country and batch (ref. 3)
Figure 2 Screenshot of Episat website homepage
Metabonomics Building upon the already
conducted GWAS, showing an association with
regions in chromosome 15 (possibly the nicotinic
acetylcholine receptor), we wish to investigate
carefully interactions with smoking, ETS, diet
and environmental exposures. We plan to conduct
a metabonomic study to identify profiles that
(a) are more typical of smokers than non-smokers
(see preliminary work in Figure 3) , (b) can
predict lung cancer onset, (c) are involved in
the nicotinic acetylcholine receptor pathway. We
will also measure cotinine, NNK and
1-hydroxypyrene in relation to genetic
predisposition and the risk of lung cancer. We
will explore the role of oxidative damage in lung
carcinogenesis.

• REFERENCES
• 1. Hung R et al. Nature. 2008 Apr
  3452(7187)633-7 2. Vineis P et al. BMJ. 2005
  Feb 5330(7486)277. 3. Peluso M et al. Cancer
  Res. 2005 Sep 165(17)8042-8 4. Vineis P et
  al. JNCI 2004 Jan 2196(2)99-106. 5. Vineis P
  et al. Environ Health. 2007 Feb 1567.

Figure 3 Correlation of urinary (male) metabolic
profiles to smoking status. Log spectra vs dummy
Y matrix (0never smoked, 1past and present
smokers) n57, never smoker n30, past smoker
n17, current smoker n10.