Genome-wide association studies in cancer
Douglas F. Easton1,?and Rosalind A. Eeles2,3,4
1Cancer Research UK Genetic Epidemiology Unit, University of Cambridge, Strangeways Research Laboratory,
Worts Causeway, Cambridge CB1 8RN, UK,2Translational Cancer Genetics Team, The Institute of Cancer Research,
15 Cotswold Road, Sutton, Surrey SM2 5NG, UK,3The Royal Marsden NHS Foundation Trust, Downs Road, Sutton,
Surrey SM2 5PT, UK and4The Royal Marsden NHS Foundation Trust, Fulham Road, London SW3 6JJ, UK
Received August 27, 2008; Revised and Accepted September 7, 2008
Genome-wide association studies (GWAS) provide a powerful approach to identify common, low-penetrance
disease loci without prior knowledge of location or function. GWAS have been conducted in five of the com-
monest cancer types: breast, prostate, colorectal and lung, and melanoma, and have identified more than 20
novel disease loci, confirming that susceptibility to these diseases is polygenic. Many of these loci were
detected at low power, indicating that many further loci will probably be detected with larger studies. For
the most part, the loci were not previously suspected to be related to carcinogenesis, and point to new dis-
ease mechanisms. The risks conferred by the susceptibility alleles are low, generally 1.3-fold or less. The
combined effects may, however, be sufficiently large to be useful for risk prediction, and targeted screening
and prevention, particularly as more loci are identified.
All common cancer types aggregate in families, with the
disease being typically 2–4-fold more common in the first
degree relatives of cases of the same type than in the
general population (1,2). Twin studies suggest that this famil-
ial clustering is likely to be largely genetic (3), but for the
most part the underlying genetic loci are not known. Some
of the familial risk can be explained by rare mutations in
high-penetrance genes, first identified in the 1990s, of which
the most important are BRCA1 and BRCA2 for breast and
ovarian cancer, mismatch repair genes for colorectal and
endometrial cancer and CDKN2A for melanoma (4–9).
These mutations, however, explain only a small fraction of
the familial risk. The subsequent failure of genetic linkage
studies to identify further susceptibility genes suggests that
most familial clustering of cancer is due to a combination of
multiple lower penetrance alleles.
Association studies, involving direct testing of genetic poly-
morphisms in large series of cases versus controls, provide a
powerful approach to identify lower penetrance alleles that
cannot be detected by genetic linkage studies, and over the
past decade many groups have tried this approach. Since
early technologies were limited to studying one or a few poly-
morphisms at a time, these studies had to focus on particular
genes or pathways. Typically, studies have concentrated on
candidate genes or pathways suspected to be important in car-
cinogenesis, such as DNA repair, carcinogen metabolism,
cell cycle control and hormone synthesis. They initially
concentrated on polymorphisms (usually single nucleotide
polymorphisms or SNPs) thought to be functionally important.
Gradually, these studies were extended to sets of tagged SNPs
correlated with all known common variants across a gene.
However, despite the fact that many genes have been
studied in association studies, very few well-validated associ-
ations have emerged from this approach [the clear examples
perhaps being NAT2 in bladder cancer and CASP8 D302H in
breast cancer (10,11)]. Additional susceptibility genes in
which rare coding variants are associated with a moderate
cancer risk have, however, emerged through candidate gene
resequencing, including ATM, CHEK2, BRIP1, PALB2 in
breast cancer, and MYH in colorectal cancer (12–17).
More recently, genome-wide association studies (GWAS)
have emerged as a powerful new approach to identifying sus-
ceptibility loci. By utilizing genotyping platforms that can
type hundreds of thousands of SNPs simultaneously, it is poss-
ible to conduct association studies using sets of SNPs that tag
most known common variants in the genome, and hence scan
for associations without prior knowledge of function or pos-
ition (18). Over the past 3 years, results from GWAS have
been published for each of the four commonest cancers in
Western populations: breast, prostate, lung and colorectal,
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