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Christina Curtis, PhD, MSc is a Professor of Medicine, Genetics and Biomedical Data Science and an Endowed Scholar at Stanford University where she leads the Cancer Computational and Systems Biology group. Dr. Curtis also serves as the Director of Artificial Intelligence and Cancer Genomics, Director of Breast Cancer Translational Research and Co-Director of the Molecular Tumor Board at the Stanford Cancer Institute. Dr. Curtis’s laboratory leverages computational modeling, high-throughput molecular profiling and experimentation to develop new ways to prevent, diagnose and treat cancer. Her research has helped to redefine the molecular map of breast cancer and led to new paradigms in understanding how human tumors evolve and metastasize. Dr. Curtis is the recipient of numerous awards, including those from the V Foundation for Cancer Research, STOP Cancer and the American Association for Cancer Research (AACR). She received the National Institutes of Health Director's Pioneer Award in 2018, the Stanford Prize in Population Genetics and Society (2020) and was named an In vivo Rising Leader in the Life Sciences (2021) and the Julius B. Kahn Visiting Professor in the Dept of Pharmacology, at Northwestern University (2020). In 2022 she received the AACR Award for Outstanding Achievement in Basic Science. Dr. Curtis is also Kavli Fellow of the National Academy of Sciences, a Susan G. Komen Scholar and a Chan Zuckerberg Biohub Investigator. Dr. Curtis serves as a scientific advisor to multiple academic institutes and biotech as is a member of the AACR Board of Directors. She also serves on the editorial board of journals spanning computational biology to precision oncology.
Breast cancer therapy, metastasis
National Cancer Institute
Bioinformatics /Translational cancer research/clinical trials
Molecular characterization of cancer and pre-cancer
We are 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:1.) Model the evolutionary dynamics of tumor progression and therapeutic resistance and metastasis2) Elucidate disease etiology and novel molecular targets through integrative analyses of high-throughput omic data3) Develop techniques for the systems-level interpretation of genotype-phenotype associations in cancerOur 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.
Study of Infigratinib in Combination With Tamoxifen in Hormone Receptor Positive, HER2 Negative, FGFR Altered Advanced Breast Cancer
The purpose of the study is identify the dose(s) of infigratinib to use in combination with
tamoxifen to treat patients with a particular type of advanced breast cancer (hormone
receptor-positive, HER2-negative, FGFR-altered breast cancer)
Stanford is currently not accepting patients for this trial.
For more information, please contact Lisa Kody, 650-498-8583.
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