报告题目：Computer the Cure to Cancer
摘要：Recent progression of cancer genome projects has uncovered the mutational landscapes of many cancers, but how cancer cell evolves with and without therapy is still unclear. Scientists believe one major reason of treatment failure is the temporal-spatial dynamics of cancer cells. Actually, cancer cells are constantly evolving, with different groups of cells accumulating distinctive mutations. As the search for more effective cancer diagnostics and therapies continues, remained key questions include a) how to interpret intratumor heterogeneity (ITH); b) how to understand the tumors change over time and how to predict the impact of ITH on tumor progression; and c) how to disentangle the order in which mutations occur. Being able to predict how a tumor will behave based on signs seen early in the course of disease could enable the development of new diagnostics that could better inform treatment planning.
报告人简介: Prof Jiguang Wang joined The Hong Kong University of Science and Technology in 2016, having previously spent five years subsequently as Postdoctoral Research Scientist and Associate Research Scientist at Columbia University, where he focused on studying cancer genomics and developed a computational method for tracing the evolution of chronic lymphocytic leukemia. In 2015, he was named as an Irving Institute Precision Medicine Fellow. He received his Ph.D. in Applied Mathematics from the Chinese Academy of Sciences. He has substantial contribution to the reconstruction and elucidation of RNA Exosome regulated transcriptome (Nature 2014 and Cell 2015), and the discovery of MGMT fusion in recurrent glioblastoma (GBM) (Nature Genetics 2016), PIK3CA mutation in multi-focal GBM (Nature Genetics 2017), as well as the deletion of exon 14 in MET oncogene in secondary GBM (Cell 2018).