Jakob Skou Pedersen
Solid tumors release circulating tumor DNA (ctDNA) to the blood, where it can be recovered from the plasma. Detection and analysis of ctDNA may transform cancer care. However, in many clinically relevant settings, it comprises only a minute fraction of the circulating free DNA (cfDNA), with most coming from healthy cells. The cfDNA can be cataloged in vast data sets using DNA sequencing techniques. We will use generative AI statistical modeling techniques to detect subtle ctDNA signals and characterize the underlying cancer biology. Predictive methods will be trained and evaluated on comprehensive public cancer genomics and local cfDNA data sets. The goal is to contribute cancer biology insights and help advance cancer care with methods for early diagnosis, disease surveillance, and cancer characterization.