Christina Curtis

Christina Curtis applies her expertise in cancer genomics and computational biology to optimize the sensitivity and specificity of multi-cancer early detection, developing integrative algorithms that combine multiple cfDNA features including methylation, fragmentation patterns, and copy number alterations to maximize cancer detection while minimizing false positives. Her work has characterized how tumor heterogeneity and clonal evolution influence cfDNA shedding and MCED test performance across different cancer stages and types. She has established benchmarks for MCED analytical sensitivity at clinically relevant tumor fractions. Her computational approaches are advancing next-generation MCED tests with improved performance characteristics.