| Background and objective:Liver cancer is one of the digestive tract malignant tumors that seriously endanger human health.Human-derived tumor xenograft（patient-derived tumor xenograft,PDX）models can overcome the defects of tumor cell line models to a certain extent.However,the current PDX model has low tumor formation rate and long tumor formation time,which limits the application of this model.Therefore,the purpose of this study was to explore the relevant factors that affect the establishment of liver cancer PDX models,and to establish liver cancer with high tumor formation rate and short tumor formation time.PDX model.Provide effective individualized treatment plan for liver cancer patients.Methods:A total of 20 patients with liver cancer were included in this study.Of these,10 underwent surgery and 10 underwent liver biopsy.（1）The fresh tumor tissues of these patients were implanted in NOD/SCID mice,the tumor formation rate,tumor growth,and survival status of the mice were observed,and the method of tumor tissue sampling,implantation site,tissue type,and degree of tissue differentiation were analyzed.,Tissue isolation time,patient age,gender,blood cell index,whether chemotherapy,tumor differentiation degree and proliferation index Ki67,blood coagulation index,liver function index,tumor markers on model construction.（2）Use magnetic resonance imaging（MRI）to observe the blood supply and growth status of the tumor,and to judge the tumor infiltration and metastasis.（3）When the tumor tissue grew to 300-500 mm3,the mice were sacrificed by cervical dislocation,and the transplanted tumor（P1）was taken out and subcultured（P2,P3,P4）by pathological HE staining,immunohistochemical staining and whole-body staining.Exome sequencing was used to compare the morphological,molecular and gene expression similarity between PDX model tumor tissue and patient tumor tissue.Results:By implanting the tumor tissues of 16patients into NOD/SCID mice,9patients developed tumors with a tumor formation rate of 56%.A total of 49 models were established for all patients,and 16 were successful,with a total tumor formation rate of 33%.The clinical data of the patients were statistically analyzed,and it was found that the age,Ki67,and the number of lymphocytes were statistically significant.The patients younger than 55 years old had a high tumor formation rate,and the patients with Ki67≥50%had a high tumor formation rate,and the number of lymphocytes was less than 1.2×10~9/L had a higher tumor formation rate.Four implant sites were selected:renal capsule,inguinal,omentum,and liver in situ.Only renal capsule and inguinal tumor were formed.The average time of renal capsule tumor formation was 33 days,the average time of inguinal tumor formation was 49days,and the renal capsule tumor formation rate was 30%.The groin tumor formation rate was 6%.There was no tumor in situ of the omentum and liver.The tumor formation rate is higher when implanted within 2 hours（88%tumor formation rate）.The growth of PDX tumors was observed under MIR.The tumor tissue volume gradually increased after 9 days of transplantation.The tumor tissue grew the fastest at about 15 days,and the tumor tissue growth stopped at about 30 days.Through HE staining,immunohistochemical analysis and whole-exome sequencing,the PDX model maintained tumor cell differentiation,morphological and structural characteristics,gene mutation,tumor mutation coincidence,microsatellite instability,mismatch repair deficiency,and PDL-1 expression.It has a high similarity with human tumors and can be used in the research of clinical individualized treatment.Conclusion:Age less than 55 years old,Ki67 greater than or equal to 50%,and lymphocyte count less than 1.2×10~9/L were the factors affecting the tumorigenic rate.Subcapsular transplantation,tissue transplantation 2 hours after ex vivo,and poorly differentiated tumor tissue are the key factors affecting the success of the PDX model.MRI is an effective method for dynamic and non-invasive detection of liver cancer PDX models.This model has good fidelity in the passage. |
