Genome wide association studies (GWAS) have so far identified more than 20 common low penetrance
variants for ovarian cancer; but it is estimated that thousands more risk variants await discovery. In the
post-GWAS era a complex set of challenges for the identification, functional characterization and utility of
susceptibility alleles have emerged including: (i) Identifying the causal genetic variants and regulatory
targets driving cancer development at risk loci; (ii) Identifying the susceptibility genes associated with risk
variants; (iii) Establishing if there are common biological networks that explain the functional mechanisms
underlying multiple risk loci. Clinically, identifying the genetic risk component of ovarian cancer will likely
lead to improved disease prevention through population screening and disease prevention strategies; and
understanding the function of risk loci may lead to the discovery of clinical biomarkers and novel targeted
therapies, analogous to the paradigm of PARP therapy for BRCA1 or BRCA2 mutation carriers.
The current proposal is designed to address many of these challenges for ovarian cancer in the post-
GWAS era including: (1) Identifying additional novel, common variant susceptibility alleles for the different
histological subtypes of ovarian cancer; (2) Establishing the functional mechanisms driving disease at
ovarian cancer risk loci based on the identification and characterization of the likely casual SNPs and
targets susceptibility genes are risk loci; (3) Using genome wide profiling of functional models based on
perturbation of ovarian cancer susceptibility genes, to identify common mechanisms and biological
pathways driving tumorigenesis; (4) To integrate functional datasets with genetic association datasets to
improve the power of these studies to identify additional ovarian cancer susceptibility loci.
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