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Busulfan and cyclosphamide induce liver inflammation through NLRP3 activation in mice after hematopoietic stem cell transplantation.

ABSTRACT: The aim of this study was to evaluate the role of NLRP3 inflammasome on BU/CY-induced liver inflammation in mice after HSCT. HSCT mice model was established through infusion of 5 × 10(6) bone marrow mononuclear cells after conditioned with BU/CY. On day 7, 14, 21 and 28 after HSCT, mice were sacrificed for analysis of liver inflammation, cytokine secretion, NLRP3 expression and caspase-1 activation as well as release of ATP and high-mobility group protein B1 (HMGB1). Furthermore, NLRP3 selective inhibitor (BAY 11-7082) was administrated into mice after HSCT to evaluate its effects on liver inflammation. Severe liver inflammation and damage with elevated secretion of IL-1β and IL-18 were found in mice after HSCT. Meanwhile, elevated expressions of NLRP3 and caspase-1 activation in liver were found. In addition, increased release of ATP and HMGB1 were observed. Selective inhibition of NLRP3 decreased caspase-1 activation and secretion of IL-1β and IL-18. Furthermore, NLRP3 inhibition also reduced infiltration of macrophages and neutrophils and improved liver function. In conclusion, NLRP3 was involved in BU/CY-induced liver inflammation after HSCT and selectively inhibited it ameliorated liver inflammation and improved liver function, suggesting targeting NLRP3 might be a new approach in the prophylaxis of liver inflammation after HSCT.

SUBMITTER: Qiao J

PROVIDER: S-EPMC4669461 | biostudies-other | 2015 Dec

REPOSITORIES: biostudies-other

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Project description:Objective: Busulfan (BU) is a bi-functional DNA-alkylating agent used in patients undergoing hematopoietic stem cell transplantation (HSCT). Over the last decades, several population pharmacokinetic (pop PK) models of BU have been established, but external evaluation has not been performed for almost all models. The purpose of the study was to evaluate the predictive performance of published pop PK models of intravenous BU in adults using an independent dataset from Chinese HSCT patients, and to identify the best model to guide personalized dosing. Methods: The external evaluation methods included prediction-based diagnostics, simulation-based diagnostics, and Bayesian forecasting. In prediction-based diagnostics, the relative prediction error (PE%) was calculated by comparing the population predicted concentration (PRED) with the observations. Simulation-based diagnostics included the prediction- and variability-corrected visual predictive check (pvcVPC) and the normalized prediction distribution error (NPDE). Bayesian forecasting was executed by giving prior one to four observations. The factors influencing the model predictability, including the impact of structural models, were assessed. Results: A total of 440 concentrations (110 patients) were obtained for analysis. Based on prediction-based diagnostics and Bayesian forecasting, preferable predictive performance was observed in the model developed by Huang et al. The median PE% was -1.44% which was closest to 0, and the maximum F20 of 57.27% and F30 of 72.73% were achieved. Bayesian forecasting demonstrated that prior concentrations remarkably improved the prediction precision and accuracy of all models, even with only one prior concentration. Conclusion: This is the first study to comprehensively evaluate published pop PK models of BU. The model built by Huang et al. had satisfactory predictive performance, which can be used to guide individualized dosage adjustment of BU in Chinese patients.

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Busulfan and cyclosphamide induce liver inflammation through NLRP3 activation in mice after hematopoietic stem cell transplantation.

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