Drug-induced cardiotoxicity is one of the main causes of drug failure, which leads to subsequent withdrawal from pharmaceutical development. Therefore, identifying the potential toxic candidate in the early stages of drug development is important. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are a useful tool for assessing candidate compounds for arrhythmias. However, a suitable model using hiPSC-CMs to predict the risk of torsade de pointes (TdP) has not been fully established. The present study aimed to establish a predictive TdP model based on hiPSC-CMs. In the current study, 28 compounds recommended by the Comprehensive in vitro Proarrhythmia Assay (CiPA) were used as training set and models were established in different risk groups, high-and intermediate-risk versus low-risk groups. Subsequently, six endpoints of electrophysiological responses were used as potential model predictors. Accuracy, sensitivity and area under the curve (AUC) were used as evaluation indices of the models and seven compounds with known TdP risk were used to verify model differentiation and calibration. The results showed that among the seven models, the AUC of logistic regression and AdaBoost model was higher and had little difference in both training and test sets, which indicated that the discriminative ability and model stability was good and excellent, respectively. Therefore, these two models were taken as submodels, similar weight was configured and a new TdP risk prediction model was constructed using a soft voting strategy. The classification accuracy, sensitivity and AUC of the new model were 0.93, 0.95 and 0.92 on the training set, respectively and all 1.00 on the test set, which indicated good discrimination ability on both training and test sets. The risk threshold was defined as 0.50 and the consistency between the predicted and observed results were 92.8 and 100% on the training and test sets, respectively. Overall, the present study established a risk prediction model for TdP based on hiPSC-CMs which could be an effective predictive tool for compound-induced arrhythmias.
Drug-induced cardiotoxicity is a leading cause of failure in drug development and predicting its occurrence in non-clinical studies is the primary preventive measure. The present study aimed to evaluate the changes in biomarkers during acute and chronic myocardial injury induced by doxorubicin (DOX) in rats. A rat model of acute myocardial injury was established through a single-dose, intraperitoneal injection of DOX (40 mg/kg), the changes in biomarkers were measured at 2, 4, 8 and 24 h after administration, following DOX administration, creatine kinase (CK) and fatty acid-binding protein 3 (FABP3) levels increased between 8 and 24 h, whereas cardiac troponin I (cTnI) peaked at 8 h. To establish a chronic myocardial injury model, rats received 1, 2 or 3 mg/kg DOX weekly by caudal vein injection for 2, 4, 6 or 7 weeks, the changes in biomarkers were detected at 2, 4, 6 and 8 weeks, the results showed that cTnI increased significantly after 2 and 8 weeks of administration. A significant increase in FABP3 and microRNA (miR)-146b levels was observed after 8 weeks of administration. Receiver operating characteristic curve and correlation analysis showed that cTnI and miR-146b had relatively high predictive values for chronic myocardial injury (area under the curve, 0.83 and 0.71, respectively) and were closely correlated with myocardial damage. These data suggested that CK, cTnI and FABP3 were relatively sensitive to DOX-induced acute myocardial injury, whereas cTnI and miR-146b were relatively sensitive to DOX-induced chronic myocardial injury.
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