Asst. Prof. Clive Yik-Sham Chung
The University of Hong Kong, Hong Kong

Dr. Clive Yik-Sham CHUNG received his BSc and PhD degrees from the Department of Chemistry, The University of Hong Kong (HKU). He then did his postdoctoral research on inorganic medicines and nano-formulations at HKU. In 2016, he received Croucher Postdoctoral Fellowship and moved to UC Berkeley, working on molecular imaging to unravel roles of reactive oxygen species (ROS) and copper in biology. In 2018, he moved to Novartis-Berkeley Center for Proteomics and Chemistry Technologies in UC Berkeley, working on chemoproteomics and mass spectrometry (MS) for discovering covalent ligands that can modulate autophagy and mTORC1 signaling. In May 2020, Dr CHUNG re-joined HKU as an Assistant Professor in the School of Biomedical Sciences and Department of Pathology, School of Clinical Medicine. His lab is now actively working in the field of chemical biology, particularly interested in: (1) developing new chemical tools to advance chemoproteomics experiments; (2) developing new therapeutic covalent ligands for targeted cancer therapy; (3) studying redox biology.

Speech Title: "Chemoproteomics Enable Identification of New Druggable Hotspots in Cancers and Discovery of New Therapeutic Covalent Ligands"

Abstract: Chemoproteomics is an advanced proteomics technology using chemical probes to study functions and activities of proteins. Since many functional proteins are associated with disease development and progression, the applications of chemoproteomics have been extended to drug target identification and covalent drug development. In this talk, I will first illustrate how the development of new chemoproteomics probes can significantly expand the pool of targetable hotspots, even on proteins which were once considered as undruggable. Then, I will showcase how covalent ligand screening experiments can be coupled with chemoproteomics to discover novel lead compounds targeting the new hotspots on cancer-related proteins. Finally, I will discuss the promising anticancer and anti-metastatic properties of the identified lead compounds in 2D and 3D cancer cell culture, as well as in vivo. All these results should highlight the powerful application of chemoproteomics in biomedical studies and drug research.

Assoc. Prof. Jin-Ku Lee
Seoul National University College of Medicine, South Korea

Jin-Ku Lee is an associate professor at Seoul National University College of Medicine (SNUCM), Korea. He achieved both M.D. (2003) and Ph.D. (2013) at SNU. His research fields of interests were cancer genomics and pharmacogenomic analysis using patient-derived tumor models for precision oncology. In respect to these research areas, he has published many SCI(E) articles, including Nature genetics (2017, 2018), Genome Biology (2019) and Biomaterials (2023). In particular, his lab is focused on developing cutting-edge technologies in patient tumor organoid cultures and 3D-based drug screening accompanied with systemic identification of genomic biomarkers for drug sensitivity.

Speech Title: "Genomics of Drug Sensitivity in Cancer"

Abstract: Outcomes of anticancer therapy vary dramatically among patients, which may be caused by the specific molecular alterations in each patient’s tumor. The development of ex vivo drug test-guided clinical response prediction platform has elicited clinical and industrial interests for precision cancer therapy. We have established a resource reporting the genomic and transcriptomic profiles of 462 patient tumor-derived cells across 14 cancer types, together with responses to 60 targeted agents. We identified molecular factors to induce resistance to EGFR inhibitors, and suggested repurposing ibrutinib for EGFR-specific therapy in gliomas. In addition, we discovered lineage-specific drug sensitivities based on subcategorization of gynecologic tumors. We also have manufactured an automated organo-spotter-integrated high throughput organo-on-pillar (High-TOP) drug test platform, demonstrating considerable robustness, consistency, reproducibility, and clinical relevancies in three-dimensional drug sensitivity analyses.