Yong Li Lab

About the Lab

The Yong Li Laboratory integrates artificial intelligence, computational biology, and experimental validation to advance the fundamental understanding of cancer and develop innovative molecular and cellular therapeutics. Our research focuses on targeting mutant p53 proteins and other clinically relevant tumor antigens, with the goal of translating biological discoveries into transformative cancer therapies.

Cancer Prevention and Interception

Dr. Li directs a U54 Cancer Prevention and Interception Center, funded by the National Cancer Institute's Division of Cancer Prevention. The Center is dedicated to preventing the progression of monoclonal gammopathy of undetermined significance (MGUS), a premalignant condition characterized by the presence of abnormal monoclonal immunoglobulin (M protein) in the blood. Individuals with MGUS face an approximately 6.5-fold higher risk of developing hematologic malignancies than the general population. MGUS can progress to multiple myeloma, Waldenström macroglobulinemia, non-Hodgkin lymphoma, chronic lymphocytic leukemia, AL amyloidosis, or plasmacytoma. Through multidisciplinary collaboration, the Center develops and evaluates immunologically and chemically targeted interventions aimed at preventing or intercepting malignant transformation in patients with MGUS and related smoldering disorders.

Targeting Hotspot p53 Mutants

The p53 tumor suppressor gene is the most frequently mutated gene in human cancer. Despite decades of effort, effective therapies targeting intracellular mutant p53 proteins remain elusive. Most drug discovery programs have focused on restoring mutant p53 to its native, wild-type conformation using small molecules, an objective that has proven exceptionally challenging. The Li Laboratory pursues a fundamentally different strategy: rather than attempting to repair mutant p53, we seek to directly target mutant p53 proteins in their existing conformations using highly specific monoclonal antibodies. Our vision is to develop antibody-based therapeutics that selectively recognize cancer-associated p53 mutants while sparing wild-type p53, thereby enabling precision treatment for patients whose tumors harbor these mutations.

Artificial Intelligence in Antibody Discovery

Artificial intelligence is transforming antibody discovery by shifting the field from labor-intensive, empirical experimentation to predictive, data-driven design. Conventional approaches, including phage display, hybridoma technology, and single B-cell sequencing, are often characterized by lengthy development timelines and high attrition rates. The Li Laboratory combines AI-driven design with automated high-throughput screening and experimental validation to discover next-generation antibodies against both intracellular and cell-surface tumor antigens. This integrated approach accelerates the development of novel cancer immunotherapies and expands the range of druggable targets in oncology.