Christina Curtis

Christina Curtis Photo

The Curtis laboratory couples innovative experimental approaches, high-throughput omic technologies, statistical inference and computational modeling to interrogate the evolutionary dynamics of tumor progression and therapeutic resistance. To this end, Dr. Curtis and her team have developed an integrated experimental and computational framework to measure clinically relevant patient-specific parameters and to measure clonal dynamics. Her research also aims to develop a systematic interpretation of genotype/phenotype associations in cancer by leveraging state-of-the-art technologies and robust data integration techniques. For example, using integrative statistical approaches to mine multiple data types she lead a seminal study that redefined the molecular map of breast cancer, revealing novel subgroups with distinct clinical outcomes and subtype-specific drivers.