Research in the Cao Lab focuses broadly on antibody- and cellular-based therapy in the treatment of cancers and autoimmune diseases using a variety of techniques from pharmacokinetics/pharmacodynamics, molecular imaging, engineering, and computational modeling.

Our research is at the interface of computational modeling and experimental oncology and immunology. Below are selected examples of ongoing projects in his lab. As a young and rapidly growing group, we are also constantly initiating new projects within this research field.

Antibody spatial distribution and interaction with targets in the living systems.

The efficacy of therapeutic antibodies is essentially driven by their interactions with the target cells, which is shaped by many physical and biological factors. However, it remains a “dark spot” in our knowledge of how antibodies interacting with their target cells in the living systems, which limit our abilities to understand the mechanisms of resistance and design effective antibodies.  In this project, we develop a bioluminescence resonance energy transfer (BRET)-based system that leverages the large signal: noise ratio and stringent energy donor-acceptor distance dependency to measure antibody-antigen interactions in a highly selective and temporal fashion. With this technique, we evaluate their interactions in a variety of physiological environments in the living systems.

Interaction between effector cells and pathogens or tumor cells.

Effector cells play an important role in antibody- and cell-based therapies. Unfortunately, the degree and dynamics of the interactions between effector cell and pathogen or tumor cells in the living system have not been well characterized, mostly because an approach for measuring cell-cell interactions directly in vivo is still lacking. In this project, we combine molecular imaging and computational modeling approaches to understand their interactions and the influencing factors, which could potentially help to disclose the mechanisms of resistance to an antibody or cell therapy.

Evolutionary dynamics of pathogens and drug resistance.

Tumor or pathogen resistance to treatment has become one of the major obstacles in effective therapeutics. The promise of antibody therapy has only fulfilled in a small fraction of patients. In this project, we adopt Darwinian’s principles, coupled with computational modeling, to infer the process of resistance. This work is expected to recapitulate the evolutionary dynamics of diseases and improve our current strategies in developing and applying antibody-based therapies.