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学术报告
题 目: Computational efforts towards immune-based early cancer detection
Associate Professor, Department of Pathology and Laboratory Medicine,University of Pennsylvania
时 间: 8月12日(周一)10:00-11:00
地 点: 吕志和楼B101
主持人: 曾泽贤 研究员
摘要:
Cancer is a leading cause of death worldwide. Early detection of most cancer types results in reduced mortality, and hence many clinical approaches have been developed to identify malignancies at early-stage. However, conventional diagnostic methods, such as serum protein biomarkers or imaging scans, remain insensitive at this stage due to limited tumor size and cancer-derived molecular materials. In the past decade, we have explored, developed and optimized a novel approach to detect cancer from the host adaptive immune responses. Specifically, we search for the T cells in the blood repertoire that are associated with cancer and use their T cell receptors (TCR) as sensors of malignancies. In this talk, I will cover the rationale of this approach and the collection of computational tools we have developed to progressively dissect the blood TCR repertoire to find cancer signals. At the end of this talk, I will present a recent study that we implemented this approach to high-grade serous ovarian carcinoma, a task considered as the ‘holy-grail’ of early cancer detection. By analyzing the TCR repertoires of HGSOC patients using our cutting-edge computational tools, we were able to identify a strong, yet transient signal in the blood that is up to 4 years prior to conventional HGSOC diagnosis.
Dr. Li received his bachelor’s degree in physics from Peking University, China (2009), and developed a fascination with complex, yet highly organized biological systems. He then pursued a PhD degree in Bioinformatics at the University of Michigan, Ann Arbor, under the supervision of Dr. Jun Li. He joined the Dr. Xiaole Shirley Liu lab at Dana-Farber Cancer Institute for a postdoctoral fellowship, where he was jointly supervised by Drs. Shirley Liu and Jun S. Liu at Harvard Department of Statistics. Li’s research interests are in developing novel bioinformatics methods for investigating high-throughput genomics data to understand disease etiology and biological processes, with a particular interest in cancer. From 2017 to 2023, Li worked at UT Southwestern Medical Center. In 2023, Li joined in Upenn/CHOP to continue his research in cancer genomics and computational cancer immunology.