Background Family history is a risk factor of many diseases. Genome-wide sequencing efforts have identified naturally occurring genetic variations such as copy number variations (CNV) and single nucleotide polymorphisms (SNPs) across the human genome that could account for the risk associated with family history (1). In fact, genome-wide association studies (GWAS) have linked numerous SNPs with an increased risk of developing specific diseases, such as breast and prostate cancer (2-13). Interestingly, most risk-associated SNPs (raSNPs) map to non-coding genomic regions, which excludes their role in protein sequence/structure alterations (2-13). This has significantly complicated the understanding of how SNPs can contribute to cancer development and has hindered the development of therapeutic strategies based on SNP profiling. Genome-wide assays revealed the preferential recruitment of transcription factors to non-coding regions surrounding actively transcribed genes in breast and prostate cancer cells (14-17). In addition, changes to the genomic distribution of these transcription factors directly impacts transcriptional programs (18, 19). Hypothesis We hypothesize that raSNPs associate with cancer development by promoting transcriptional programs favorable to oncogenesis by altering transcription factor recruitment. Approach Combining multiple genomics datasets from different cancer types, we will determine the role of breast and prostate cancer raSNPs on transcription factor activity by 1) determining the cancer type- specificity of raSNPs and transcription factor recruitment, 2) defining the role of raSNPs on transcription factor recruitment and by 3) determining how raSNPs modulating transcription factor recruitment affects transcriptional programs. Relevance to the mission While breast and prostate cancer raSNPs serve important diagnostic and prognostic purposes, they lack therapeutic value. Defining the function of these raSNPs, as we currently propose, will reveal the therapeutic applicability of SNP profiling in breast and prostate cancer. Hence, our research will be of direct and rapid benefit to the clinic.
While single nucleotide polymorphism (SNP) profiling has identified specific genetic variations as risk factors for cancer development, the mechanisms responsible for the increased risk are ill defined. This hinders the therapeutic value of SNP profiling. Therefore, by defining the mechanism driving the risk associated with SNPs in breast and prostate cancer, as we currently propose, we will identify the therapeutic benefit of SNP profiling.
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