The research team successfully established a biological sample bank of organ like organisms (PDO) from pancreatic cancer patients and developed a high-throughput drug screening platform. This model can accurately predict the treatment response of patients to targeted drugs, and clinical validation shows a prediction accuracy rate of 92%. By integrating genomics and pharmacodynamics data, a personalized drug map for pancreatic cancer was drawn for the first time. This technological breakthrough has significantly improved clinical translation efficiency and provided a reliable tool for precision medicine. It has now entered the stage of multi center clinical trials.

A study on a mouse model of chronic pancreatitis constructed based on gene editing technology found that anti fibrotic drugs can effectively block the process of inflammation carcinogenesis transformation. Through multi omics analysis, the key role of pancreatic stellate cell activation in carcinogenesis has been revealed. Preclinical trials have confirmed that early intervention can reduce the incidence of tumors by 67%. This study provides an important basis for the primary prevention of pancreatic cancer, and the relevant treatment scheme has obtained the FDA rapid approval qualification.

Five liver cancer specific new antigens were screened and identified using a humanized PDX model, among which HCC-AG3 antigen exhibited strong immunogenicity. Research has confirmed that bispecific antibodies developed against this antigen can significantly enhance T cell killing activity. Animal experiments showed that the complete tumor regression rate in the treatment group reached 40%, and no significant toxic side effects were found. This discovery provides a new target for immunotherapy of liver cancer, and related drugs have entered the IND application stage.