Within any cancer types (e.g, breast, prostate), there is a mix of cancers with varying behavior. Some cancers have poor prognosis, meaning they are more prone to spreading and causing death. Others may stay dormant or progress very slowly. Thus, risk prediction models are needed to determine who is at risk of developing poor prognosis cancers as these individuals may need more intensive screening. In this project, we will build genetic-based models (polygenic risk scores, or PRS) for poor prognosis cancers, or those causing death and/or presenting at advanced stages. We will then test the performance of these PRS’s in UK Biobank data. Furthermore, we will examine additional biomarkers such as circulating metabolites to see if they cause poor prognosis cancers. In this case, we will examine causation using genetic methods that address other factors that can affect this relationship and cause spurious results. Lastly, we will examine the performance of newly discovered genetic variants and PRS for cancer survival and determine whether these variants are associated with any other diseases or clinical measures. Together, the knowledge gained from our project will improve our understanding of how genetic and metabolic markers are related to risk and prognosis of cancer and shed light on how these measures can be used to inform clinical decision-making. Specifically, our findings could inform targeted screening and prevention for cancers while shedding light on the mechanisms behind cancer risk and prognosis. We expect this project to last for 36 months.
