As members of the Breast Cancer Association Consortium (BCAC), the Consortium for Investigators of Modifiers of BRCA1/2 (CIMBA), and the Ovarian Cancer Association Consortium (OCAC), we have been very successful recently in finding loci associated with cancer risk using genome-wide association studies (GWAS). In total, we have identified more than 200 ‘tagging’ single nucleotide polymorphisms (SNPs) associated with risk of breast and ovarian cancer. However, a major bottleneck in understanding the mechanism underlying these GWAS ‘hits’ has been moving from the tagging SNPs, to identifying the candidate causal SNPs, and their method of action.
Through our international collaborations, we have access to extensive genotyping data from tens of thousands of cancer cases and controls which allow us to perform ‘fine mapping’ to identify the putative causal SNPs at the loci we have found through GWAS. These data put us in a leading position worldwide to move from identifying GWAS ‘hits’ to determining the functional variants and their mechanisms of action. Almost all of these SNPs are in intergenic or non-coding regions of the genome. The challenge is now to identify the target genes on which these SNPs act, and the mechanisms by which they alter risk or prognosis. Once we have narrowed down the list of putative causal variants through statistical analyses, we then use a system we have developed (integrated expression quantitative trait and in silico prediction of GWAS targets – INQUISIT) to rank the likely target gene at each locus. Functional validation of these predicted targets requires a combination of bioinformatic analysis (particularly of data from ENCODE and FANTOM5), chromatin conformation capture, expression quantitative trait loci (eQTL) analysis and luciferase assays. However, this is very labour intensive for so many risk loci, so we are also planning high throughput CRISPR knockout and overexpression screens of all the predicted target genes in mammary cells. In a complementary approach, we are also conducting ‘transcription wide association studies’ in order to identify the likely target genes at these loci, and testing their functionality in vitro.
A major aim of post-GWAS studies is to translate evidence of genetic association into molecular mechanisms which ultimately lead to more effective clinical interventions. A recent study suggests that drugs which target genes that are implicated by GWAS are twice as likely to be effective treatments for the studied trait. For this reason, we are particularly focusing on breast cancer susceptibility loci where we predict that the target gene/protein is one for which an approved drug (for another disease) is already available. In collaboration with Dr Fares Al Ejeh, at QIMR Berghofer, we are starting to evaluate the effects of some of these drugs in animal models.
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