A population PK model of TAC was developed in Chinese pediatric patients early after liver transplantation. It identified significant relationships between the PK of TAC and the characteristics of the patients. POD, ALT, and TP were identified as the main factors influencing the PK of TAC. The developed model could be useful to optimize individual pediatric TAC dosing regimen in routine clinical practice.

1. The purpose of this study was to establish a population pharmacokinetic (PK) model of tacrolimus and evaluate the influence of clinical covariates, including the genetic polymorphisms of the cytochrome P450 3A5 gene (CYP3A5) and gene-encoding P-glycoprotein (ABCB1), on the PK parameters in Chinese adult liver transplant recipients. 2. Details of drug dose, sampling times and concentrations were collected retrospectively from routine therapeutic drug monitoring data early after liver transplant. Tacrolimus PKs was studied by a non-linear mixed-effect modeling (NONMEM) method. CYP3A5 genotypes, ABCB1 C3435T and G2677T/A polymorphism and a number of clinical covariates were tested for their influence on TAC PKs. 3. A one-compartment model with first-order absorption and elimination adequately described the data. Apparent clearance (CL/F) and apparent volumes of distribution (V/F) in final population model were 17.6 L/h and 225 L, respectively. The absorption rate constant (Ka) was fixed at 4.48 h(-1). The inter-individual variability in CL/F and V/F was 53.9 and 68%, respectively. In the final model, CYP3A5 genotype, post-operative day, alanine aminotransferase, total bilirubin, hematocrit and blood urea nitrogen were found to significantly influence the CL/F, whereas POD and HB influence V/F. 4. Population PK analysis of tacrolimus in Chinese adult liver transplant patients resulted in identification of the CYP3A5 genotype, POD, BUN, ALP, HCT, TBIL and HB as significant covariates on the PK parameters of tacrolimus.

Background: To investigate the expression of methyltransferase 3 (METTL3) and its relationship with 18 F-FDG uptake in patients with esophageal carcinoma (ESCA). Materials and methods:This study analyzed the expression of METTL3 in ESCA and its relationship with clinicopathological features by The Cancer Genome Atlas (TCGA) database. Immunohistochemical staining was performed on 57 tumor tissues of ESCA patients who underwent PET/CT scan before surgery to evaluate the expression of METTL3, glucose transporter 1 (GLUT1), and hexokinase 2 (HK2) in tumor tissues and peritumoral tissues. Analyze the relationship between SUVmax with METTL3, HK2, and GLUT1 expression. Results: The expression of METTL3, GLUT1, and HK2 was significantly increased in ESCA tissues compared with normal tissues (p < 0.001). The expression of METTL3 was correlated with tumor size and histological differentiation (p < 0.05), and there was no significant difference between age, sex, pathological types, tumor staging, or lymph node metastasis (p > 0.05). The SUVmax was significantly higher in tumors with high METTL3 expression (17.822±6.249) compared to low METTL3 expression (9.573±5.082) (p < 0.001). There was a positive correlation between the SUVmax and METTL3 expression in ESCA (r 2 = 0.647, p < 0.001). Multivariate analysis confirmed the association between SUVmax and METTL3 expression (p < 0.05). GLUT1 and HK2 expression in ESCA was positively correlated with 18 F-FDG uptake and METTL3 status (p < 0.001). Conclusions: The high expression of METTL3 is related to the high SUVmax in ESCA, and METTL3 may increase 18 F-FDG uptake by regulating GLUT1 and HK2.

BackgroundGlucose transporter 1 (GLUT1) is encoded by the solute carrier family 2A1 (SLC2A1) gene and is one of the glucose transporters with the greatest affinity for glucose. Abnormal expression of GLUT1 is associated with a variety of cancers. However, the biological role of GLUT1 in esophageal carcinoma (ESCA) remains to be determined.MethodsWe analyzed the expression of GLUT1 in pan-cancer and ESCA as well as clinicopathological analysis through multiple databases. Use R and STRING to perform GO/KEGG function enrichment and PPI analysis for GLUT1 co-expression. TIMER and CIBERSORT were used to analyze the relationship between GLUT1 expression and immune infiltration in ESCA. The TCGA ESCA cohort was used to analyze the relationship between GLUT1 expression and m6A modification in ESCA, and to construct a regulatory network in line with the ceRNA hypothesis.ResultsGLUT1 is highly expressed in a variety of tumors including ESCA, and is closely related to histological types and histological grade. GO/KEGG functional enrichment analysis revealed that GLUT1 is closely related to structural constituent of cytoskeleton, intermediate filament binding, cell-cell adheres junction, epidermis development, and P53 signaling pathway. PPI shows that GLUT1 is closely related to TP53, GIPC1 and INS, and these three proteins all play an important role in tumor proliferation. CIBERSORT analysis showed that GLUT1 expression is related to the infiltration of multiple immune cells. When GLUT1 is highly expressed, the number of memory B cells decreases. ESCA cohort analysis found that GLUT1 expression was related to 7 m6A modifier genes. Six possible crRNA networks in ESCA were constructed by correlation analysis, and all these ceRNA networks contained GLUT1.ConclusionGLUT1 can be used as a biomarker for the diagnosis and treatment of ESCA, and is related to tumor immune infiltration, m6A modification and ceRNA network.