Stanford University School of Medicine Stanford, California
Endowed Professor of Medicine, Genetics, and Biomedical Data Science Director, Breast Cancer Translational Research Co-Director, Molecular Tumor Board Chan Zuckerberg Biohub Investigator
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 can be treated with ER-directed therapies but, while most of these tumors respond well, a substantial number will recur 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—metastasis remains incurable. Dr. Curtis and her colleagues are addressing this unmet clinical need by investigating the underlying molecular drivers of recurrence and metastasis. To accomplish this, her team is creating a detailed multi-modal atlas of ER-positive breast cancer—this involves the integration of genomic and spatial molecular profiles from patients with long-term clinical outcomes, including a subset with paired recurrences. Dr. Curtis’s studies aim to provide an in-depth understanding of the evolutionary dynamics of breast cancer recurrence and the tumor factors—both intrinsic and extrinsic—that drive progression. 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.
Dr. Curtis and her colleagues have developed state-of -the-art laboratory model systems derived from patients with high-risk ER-positive/HER2-negative breast cancers that capture the heterogeneity of patient tumors and the underlying molecular drivers. Using these models and a newly developed machine learning approach, they 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. Four of the ER-positive and all TNBC subgroups persist up to two decades after diagnosis with the high-risk ER-positive subgroups accounting for one-quarter of ER-positive tumors and the majority of recurrences. These subgroups harbor characteristic molecular drivers which can be targeted therapeutically. In fact, expanded analysis identified molecular vulnerabilities in both tumor cells and the surrounding tissue across the high-risk of relapse ER-positive and TNBC subgroups. The team will continue in-depth analysis to characterize the genomic architecture of primary versus metastatic breast cancer in order to investigate if subgroup switching occurs as primary breast cancer metastasizes or in response to treatment. In tandem, they deployed new technologies to generate a spatial and temporal map of breast cancer progression, specifically focusing on the tumor immune microenvironment. They observed specific tumor-associated immune cells called macrophages are enriched in ER-positive/HER2-negative breast tumors that relapse, a finding previously linked to poor outcomes in multiple tumor types. Ongoing studies utilizing the team’s patient-derived organoid models are evaluating if microenvironment interactions are potentially targetable.
The team will continue their work in the patient-derived organoid models. Further, Dr. Curtis and her team developed a powerful computational strategy that enables spatial resolution at a single cell level. They will leverage this strategy to gain a more comprehensive picture of the evolutionary dynamics of breast cancer recurrence and the involvement of the tumor immune microenvironment. They will also continue to validate their previous findings in additional patient cohorts. These studies will advance our understanding of the role of tumor-intrinsic, extrinsic, and other factors in breast cancer initiation and progression. And the results of these studies will enable improved patient stratification and treatment decision-making, paving the way for new strategies to prevent lethal recurrence, tailor therapy to each patient, and 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.
2011
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