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Christina Curtis, PhD, MSc

Stanford University School of Medicine
Stanford, California

Titles and Affiliations

Endowed Professor of Medicine, Genetics, and Biomedical Data Science
Director, Breast Cancer Translational Research
Co-Director, Molecular Tumor Board
Chan Zuckerberg Biohub Investigator

Research area

Understanding the drivers of breast cancer recurrence and metastasis in order to develop more effective treatments for patients with metastatic estrogen receptor-positive breast cancer.


Estrogen receptor (ER)-positive breast cancer is the most common type of breast cancer and can be treated with ER-directed therapies. Unfortunately, while most women with ER-positive breast cancer respond well, a substantial number experience recurrence at distant sites such as the lungs, brain, liver, or bones. This process, called metastasis, is the major cause of breast cancer mortality and can occur more than five years after the initial diagnosis. When metastasis occurs, current therapies can prolong survival, but metastatic breast cancer is not curable. Therefore, preventing and treating metastasis in ER-positive breast cancer remains a major unmet medical need. Dr. Curtis and her colleagues are investigating the underlying molecular drivers of recurrence and metastasis and through this work have identified subgroups of patients within ER-positive and other breast cancers. Dr. Curtis’ team is seeking unique tumor targets within these subgroups that may be therapeutically actionable. Her results will help inform strategies for personalized breast cancer treatment and risk prediction with the goal of improving outcomes for women diagnosed with breast cancer and at high-risk of recurrence.

Progress Thus Far

Dr. Curtis and her colleagues have developed and characterized laboratory model systems derived from patients with high-risk ER-positive/HER2-negative breast cancers. These models provide unique tools that capture the heterogeneity of patient tumors and the underlying molecular drivers. They assembled and profiled an additional 250 patient-derived samples to expand their database of tumor information. Using a newly developed machine learning approach, Dr. Curtis and her colleagues described 11 genomically distinct breast cancer subgroups: eight subgroups of ER-positive disease, two subgroups of triple-negative breast cancer (TNBC), and one HER2-positive subgroup. In addition, they showed that four of the ER-positive that of TNBC and persists up to two decades after diagnosis. Collectively, these four high-risk ER-positive subgroups account for one-quarter of ER-positive tumors and the majority of recurrences. Additionally, these subgroups harbor characteristic molecular drivers, which can be targeted therapeutically. They have expanded the analysis and identified molecular vulnerabilities in both tumor cells and the surrounding tissue across the high-risk of relapse ER-positive and TNBC subgroups.

What’s next

The team will continue to examine the association between the identified high-risk groups and treatment response. Specifically, by characterizing the genomic architecture of primary versus metastatic breast cancer, Dr. Curtis’ team will investigate if subgroup switching occurs as primary breast cancer metastasizes or in response to treatment. In tandem, they are deploying new technologies to generate a spatial and temporal map of breast cancer progression. The results of these studies will enable improved patient stratification and treatment decision-making as well as pave the way for new strategies to prevent lethal recurrence and tailor therapy to each patient to improve their breast cancer outcome.


Christina Curtis, PhD MSc is an Endowed Professor of Medicine and Genetics at Stanford University where she leads the Cancer Computational and Systems Biology group and serves as the Director of Breast Cancer Translational Research and Co-Director of the Molecular Tumor Board at the Stanford Cancer Institute. She received her doctorate in Molecular and Computational Biology in 2007 and completed a postdoctoral fellowship in Computational Biology at the University of Cambridge in 2010.

Dr. Curtis’s research leverages data analytics, high-throughput molecular profiling, and experimentation to develop new ways to prevent, diagnose, and treat cancer. Her research has redefined the molecular map of breast cancer and led to predictive biomarkers. Additionally, she developed new paradigms in understanding how human tumors evolve and metastasize.

Dr. Curtis was the recipient of the National Institutes of Health Director’s Pioneer Award in 2018 and the American Association for Cancer Research Award for Outstanding Achievement in Basic Science in 2022. She is a 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 and is a member of the AACR Board of Directors, as well as an editor for journals spanning computational biology to precision oncology.

BCRF Investigator Since


Donor Recognition

The Ulta Beauty Award