On the morning of June 6th, 2018, Beijing Advanced Innovation Center for Structural Biology invited Arnold J. Levine, Member of the National Academy of Sciences and Professor Emeritus of School of Natural Sciences, Institute for Advanced Study to present an academic report titled -Algorithms for Predicting Responses to Cancer Immunotherapy and Long-Term Survival. The lecture took place in the reception hall of Tsinghua University’s main building. Prof. Yigong Shi, Director of the Advanced Innovation Center, hosted the lecture.
Prof. Levine was born in Brooklyn, New York, USA in 1939, and acquired a bachelor’s degree in biology from New York State University and doctorate in microbiology from University of Pennsylvania. Dr. Levine’s brilliant scientific research career has spanned 50 years. He has taught in many world-class institutions such as Princeton University, New York State University, Rockefeller University, etc. He is now a Professor Emeritus at the School of Natural Sciences, Institute for Advanced Study. Prof. Levine’s outstanding academic achievements are further enhanced by the countless awards and prizes he has won. He was elected as Member of the National Academy of Sciences in 1991 and as Member of The Institute of Medicine of the National Academy of Sciences in 1995, and awarded the Louisa Gross Horwitz prize in 1998 (for outstanding contribution in biology or biochemistry), the first Albany Medical Center Prize in Medicine and Biomedical Research in 2001, the Kirk A. Landon-AACR Prize for Basic Cancer Research by the American Cancer Research Institute in 2008, and the American Cancer Society Medal of Honor in 2009.
Professor Arnold J. Levine
Prof. Levine is a highly commended and revered leader in the field of cancer research and is one of the persons who discovered the p53 tumor suppressor gene. This gene participates in cell cycle regulation and is also one of the most common mutations in human cancer. Prof. Levine has made great contributions to the discovery of p53. Prof. Levine is focused on relevant studies on molecular biology and physical sciences at Simons Center of Systems Biology established by Princeton Institute for Advanced Study. The study scope includes genetics and genomics, gene polymorphism and molecular evolution, signal transduction pathways, and pharmacogenomics in cancer biology.
In today’s report, Prof. Levine introduced relevant research on cancer immunotherapy and long-term survival prediction algorithm, with vivid and detailed explanation. In the past 10 years, checkpoint immunotherapy has been used to activate autoimmune system of the patient to kill cancer cells, and about 20% of patients treated can achieve a survival period of 5 years or even longer. Although checkpoint immunotherapy can be considered great progress in the history of cancer treatment, there are still many problems that need to be solved. For example, why this therapy is only effective in 20-30% patients? Can we differentiate the responsive cases and non-responsive cases? Why do some patients have autoimmune diseases? Can the immune system produce effects without checkpoint therapy under specific conditions to control tumor growth and division, ultimately achieving long-term survival of cancer patients? Can we find and prove the role of the immune system in survival of cancer patients?
Professor Arnold J. Levine
Prof. Levine answered the above questions in the report, one by one and in detail. He also introduced a prediction algorithm invented by his team to differentiate responsive and non-responsive population for checkpoint therapy against melanoma in the metastasis stage. According to him, this algorithm has an accuracy of about 85%. Prof. Levine’s study is helpful to further explore potential antigen candidates in common tumor suppressor genes, explain phenomena about mutant, immunogen and HLA types, and can be used to further explore potential new therapies in future.
In the scientific report that lasted an hour, Prof. Levine was full of spirit and lively, bringing a wonderful and rich scientific feast to everyone who attended the lecture.
