DESCRIPTION (provided by applicant): Prostate cancer is the most common cancer and the second leading cause of cancer deaths among men in the U.S.
Epidemiological data and segregation analyses support the hypothesis that
genetic components contribute strongly to susceptibility, particularly in men
diagnosed at younger ages or men with a family history of disease. We have
conducted a genome-wide scan of 254 high-risk prostate cancer families
collected, characterized, and genotyped largely in the past 3 years. We now
propose to utilize the resulting data to identify putative susceptibility genes
through the following aims. Initially, we will assign priorities for follow-up
of provocative regions by refined mapping. Analyses derived from the entire
data set as well as stratified subsets of families grouped by age at onset,
family history, and clinical features of disease will be considered. Regions
for which the most compelling and consistent data are observed using a set of
stated criteria will be selected for detailed follow-up and verification. Once
loci of interest are prioritized, we will define a minimum critical region for
each by genotyping additional markers and identifying recombinants relative to
markers and known genes. A physical map of BACs across regions of interest will
be constructed using publicly available data, with gaps filled In by additional
screening and sequencing as needed. Oligoarrays of exons across the minimum
region will then be constructed and probed with mRNA isolated from both normal
prostate and tumor to identify genes from the region of interest. Additional
information will likely be derived from analysis of tumors from putatively
linked families on the same oligoarrays. Final selection of candidate genes
will be made using array data, functional information, and publicly available
expression data. Full-length cDNA clones will be isolated and sequenced as
needed. These genes, together with any identified by other investigators, will
be fully analyzed for disease-associated mutations and polymorphisms, including
SNPs, in the 254 family data set. The resulting data will provide information
about the type and distribution of mutations in high-risk families as well as
provide useful information for understanding genetic heterogeneity of prostate
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