动物造模,原发性肝癌模型 z-bio 2022-08-26 379

　　Objective: To establish a mouse primary liver cancer model using three modeling methods, and to compare the advantages and disadvantages of each.

　　Methods: Eighty 14-16-day-old C57BL/6 male mice were randomly divided into 4 groups (low-dose DEN group, high-dose DEN group, DEN+CCl4 group, control group): mice in the low-dose DEN group were injected intraperitoneally. The concentration of 25mg/kg of diethylnitrosamine (DEN) exposure; high-dose DEN group mice intraperitoneal injection of 40mg/kg DEN exposure; DEN+CCl4 group mice intraperitoneal injection of 2mg/kg After DEN exposure, mice were intraperitoneally injected with 20% carbon tetrachloride (CCl4) at a dose of 5 mL/kg twice a week for 16 weeks; the control group did not receive any treatment. The survival of the mice in each group, the mice in each group were sacrificed by central anesthesia at the 24th week after modeling, and the livers were dissected. Levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), Golgi transmembrane glycoprotein 73 (GP73) and alpha fetoprotein (AFP).

　　Results: Compared with the control group, the three experimental groups had ALT (P<0.001), AST (P<0.001), GP73 (P<0.001), AFP (P<0.01), tumor incidence (P<0.001) and The number of tumors increased significantly (P<0.001). As of 24 weeks after modeling, the mortality rate of mice in the low-dose DEN group was 15%, and the incidence of liver cancer was 35%; the mortality rate of mice in the high-dose DEN group was 30%, and the incidence of liver cancer was 30%. The incidence rate was 86%; the mortality rate of the mice in the DEN+CCl4 group was 20%, and the incidence of liver cancer was 56%; all the mice in the control group survived and no abnormality was found in the liver.

　　Conclusion: The modeling methods of each experimental group can successfully establish the mouse liver cancer model, but the high-dose DEN group shows obvious advantages, it can successfully establish a high incidence and stable mouse liver cancer in a short time. It provides a new way for mouse liver cancer modeling.