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Trained in molecular and computational biology and jointly appointed in Medicine and Genetics, Dr. Christina Curtis pursues systems biology and computational approaches to establish a quantitative and mechanistic understanding of cancer progression. Dr. Curtis’s laboratory leverages multi-omic data coupled with computational modeling and iterative experimentation in order to define the molecular determinants and dynamics of tumor progression and to identify robust biomarkers. Her research has helped to redefine the molecular map of breast cancer and led to new paradigms in understanding how human tumors progress. Dr. Curtis is the recipient of the awards from the V Foundation for Cancer Research, STOP Cancer, the AACR and is a Kavli Fellow of the National Academy of Sciences. She received the National Institutes of Health Director's Pioneer Award in 2018 and was named a Komen Scholar in 2020. Dr. Curtis is the principal investigator on grants from the NIH/NCI, NHGRI, Department of Defense, American Association for Cancer Research, Breast Cancer Research Foundation, Susan G. Komen Foundation and Emerson Collective. She serves on the Editorial Boards of Breast Cancer Research, Cancer Discovery, Carcinogenesis: Integrative Biology, Cell Systems, JCO Precision Oncology and the Journal of Computational Biology.
Bioinformatics /Translational cancer research/clinical trials
Molecular characterization of cancer and pre-cancer
We are particularly interested in elucidating tumor evolutionary dynamics, novel therapeutic targets, and the genotype to phenotype map in cancer. A unifying theme of our research is to exploit ‘omic’ data derived from clinically annotated samples in robust computational frameworks coupled with iterative experimental validation in order to advance our understanding of cancer systems biology. In particular, we employ advanced genomic techniques, computational and mathematical modeling, and powerful model systems in order to:<br/>1.) Model the evolutionary dynamics of tumor progression and therapeutic resistance and metastasis<br/>2) Elucidate disease etiology and novel molecular targets through integrative analyses of high-throughput omic data<br/>3) Develop techniques for the systems-level interpretation of genotype-phenotype associations in cancer<br/><br/>Our research is funded by the NIH/NCI, NHGRI, Department of Defense, Breast Cancer Research Foundation, American Association for Cancer Research, Susan G. Komen Foundation, Emerson Collective and V Foundation for Cancer Research.