Titles and Affiliations
Clinical Fellow
Conquer Cancer, the ASCO Foundation
Research Area
Using advanced genetic sequencing to improve detection and interpretation of inherited breast cancer risk.
Impact
Genetic testing can identify people who have inherited changes in cancer-risk genes, allowing patients and their families to receive earlier screening, prevention, and treatment. But current testing often leaves many patients with uncertain results known as variants of uncertain significance. These findings can create anxiety and limit clinicians’ ability to give clear recommendations to patients and their relatives. For her Conquer Cancer research supported by BCRF, Dr. Wu is using long-read sequencing, an advanced genomic technology that can read much longer stretches of DNA than standard testing, to better detect complex genetic changes that are often missed by current approaches.
What’s Next
Using patient genetic data linked with clinical features, family history, and tumor characteristics, Dr. Wu will evaluate whether long-read sequencing can provide more accurate results for hereditary breast cancer risk assessment and will work to improve interpretation of uncertain variants by combining genomic findings with real-world clinical and tumor data. The long-term goal is to build a more accurate and equitable framework for hereditary cancer testing, helping more patients and families get clear, actionable information about their cancer risk, particularly those from populations that have been underrepresented in genomic research.
Biography
Sulin Wu, MD, PhD is a physician–scientist, board-certified clinical geneticist, and clinical fellow in Hematology and Oncology at the University of Chicago, with a background in human genomics and systems biology. Her Conquer Cancer Young Investigator Award (YIA) research focuses on applying long-read sequencing to improve the detection and reclassification of germline variants in breast cancer, particularly in underrepresented populations. This work addresses a critical barrier in precision oncology— uncertainty in genetic testing—and establishes a scalable framework for more accurate, clinically actionable risk assessment.
