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Keywords | Breast | prostate | gene | association studies |<br />
POLYGENE<br />
Inherited risk of breast<br />
and prostate cancer<br />
Summary<br />
Studies of cancer families have identifi ed high-penetrance<br />
cancer genes such as BRCA1 and BRCA2. However,<br />
although these genes have resulted in novel insights into<br />
cancer genes and pathways, it is clear that a large component<br />
of inherited cancer risk remains unaccounted for. It<br />
has been proposed that common low penetrance cancer<br />
susceptibility genes contribute signifi cantly to the genetic<br />
predisposition of cancer in a polygenic model of inheritance.<br />
Association studies have been suggested as the<br />
method of choice for fi nding susceptibility alleles of high<br />
frequency but low penetrance. Here we propose to take<br />
advantage of accumulating genomic data and two European<br />
populations of diff erent history and structure<br />
to determine the contribution of candidate cancer susceptibility<br />
genes to diff erent clinical forms of breast and<br />
prostate cancer. We will use a population-based association<br />
study in Iceland and Holland to map the risk profi les<br />
associated with common polymorphic variants in and near<br />
candidate cancer susceptibility genes in breast and prostate<br />
cancer patients. We will also develop methods for<br />
statistical analysis of the resulting data. The proposed<br />
study has the potential to cast light on how genetic variants<br />
aff ect the risk of cancer initiation, and how it aff ects<br />
progression and response to treatment. Finally, the results<br />
may serve as a starting point for building models of genetic<br />
risk of these cancers.<br />
Problem<br />
Although several important genes have been shown to contribute<br />
to cancer susceptibility, multiple studies suggest that<br />
a major portion of such genes remain to be found. This is particularly<br />
true for prostate cancer. The major obstacles to fi nding<br />
those genes are the limited size of most studies and the inadequacy<br />
of the statistical methods available. Here we will address<br />
these problems by studying samples from two large populations<br />
of breast and prostate cancer patients and developing<br />
novel methods for the analysis of the resulting data.<br />
Aim<br />
This project has two major aims: to determine the contribution<br />
of polymorphic variants in a large number of candidate<br />
genes to the risk of breast and prostate cancer, and to<br />
develop effi cient statistical and computational methods for<br />
the analysis of genetic and association data.<br />
Expected results<br />
We expect to confi rm or exclude the association of multiple<br />
candidate cancer genes with breast and prostate cancer<br />
in the Icelandic and Dutch populations. Also, the study may<br />
identify novel candidate cancer genes, which can translate<br />
into novel diagnostic markers for breast or prostate cancer<br />
and possible targets for therapy. In addition, we expect to<br />
develop novel statistical algorithms and software for analysis<br />
of genetic association data.<br />
Potential applications<br />
Potential applications include a commercial software package<br />
for the analysis of complex genetic data and novel<br />
cancer genes to be used as predictive markers for breast or<br />
prostate cancer risk, or for developing drugs.<br />
AETIOLOGY 95
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