Vintner Grant funded by the V Foundation Wine Celebration in honor of Leslie Rudd and Family
Cancer is one of the leading causes of death across the globe. Early cancer detection can facilitate effective treatment and fewer side effects to improve patient survival and quality of life. Therefore, there is tremendous interest in using recent technological advances in DNA sequencing, medical imaging, and machine learning methods to enable early detection efforts in cancer. Early detection efforts are likely most effective among individuals genetically predisposed to cancer. Moreover, DNA mutations during the aging process can also increase the risk of developing cancer. Therefore, we aim to use population-level sequencing data to build computational methods to assess individualized risk for developing cancer. We envision that the proposed approach will provide novel insights into the role of inherited and acquired DNA mutations toward tumor growth in high-risk individuals. These insights can be employed to facilitate early detection efforts in cancer.