Characterizing genetic risk of cancer across diverse populations through multi-ancestry epigenome profiling and chromatin QTL discovery - PROJECT SUMMARY Multi-ancestry genome-wide association studies (GWAS) are beginning to identify cancer risk loci that are associated with genetic ancestry. Most GWAS risk loci affect regulatory DNA, and it remains challenging to determine how genetic variants at these loci alter gene regulation to confer cancer risk. Chromatin QTLs (cQTLs) are emerging as a powerful solution to this challenge. cQTLs are genetic variants whose genotype correlates with the activity of a nearby regulatory element. cQTLs can pinpoint disease-causing genetic variants and capture their effects on gene regulation, overcoming several shortcomings of traditional methods for annotating risk loci. To date, cQTLs have been identified almost exclusively in populations of European Ancestry (EA). Because of this, existing cQTL studies have not assessed hundreds of thousands of genetic variants that are rare in EA populations but common in non-EA populations. Systematic efforts are critically needed to identify cQTLs that account for cancer risk loci in ancestrally diverse populations. Our project will test the central hypothesis that measuring gene regulation in ancestrally diverse cohorts will reveal novel cQTLs that account for risk of common cancers. Aim 1 will identify cQTLs that confer risk of prostate cancer in men of African ancestry by profiling regulatory element activity in a large panel of prostate cancers from Africa. By targeting a profound racial diversity gap in existing cQTL studies, we expect to uncover thousands of novel cQTLs, some of which contribute to the excess risk of prostate cancer in men of African Ancestry. Aim 2 will leverage cQTLs to improve the accuracy of polygenic risk scores (PRS) for cancer in populations of diverse ancestry. Our preliminary data suggest that this innovative approach should improve the poor performance of cancer PRS in non-EA populations, overcoming a critical barrier to the equitable use of PRS. Aim 3 will identify cancer-associated cQTLs from circulating chromatin in plasma samples from diverse US populations. This novel approach will enable cQTL discovery at a speed and scale not previously achievable. It will thereby aid the discovery of cancer-associated cQTLs in underrepresented populations. Completing these aims will deepen our biological understanding of cancer-causing genetic variants that are common in non-EA populations but poorly represented in current cQTL datasets. In turn, this will allow all people to benefit more equitably from the biologic discovery and clinical applications emerging from cancer GWAS.
