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-  2019 

Pharmacometabolomic prediction of individual differences of gastrointestinal toxicity complicating myelosuppression in rats induced by irinotecan

DOI: 10.1016/j.apsb.2018.09.006

Keywords: AUC-ROC, area under receiver operating characteristic, BHB, β-hydroxybutyric acid, C, control group, CA, cholic acid, CPT-11, irinotecan, DBIL, direct bilirubin, DCA, deoxycholic acid, FDR, false discovery rate, GCA, glycocholic acid, IBIL, indirect bilirubin, IT-TOF/MS, ion trap/time-offlight hybrid mass spectrometry, Lys, lysine, MSTFA, N-methyl-N-trifluoroacetamide, NS, non-sensitive group, NSgt, non-sensitive for gastrointestinal toxicity, NSmt, non-sensitive for myelosuppression toxicity, OPLS-DA, orthogonal partial least-squares-discriminant analysis, PCA, principal component analysis, pFDR, false-discovery-rate-adjusted P value, Phe, phenylalanine, PLS-DA, partial least-squares-discriminant analysis, QC, quality control, RSD, relative standard deviation, S, sensitive group, Sgt, sensitive for gastrointestinal toxicity, Smt, sensitive for myelosuppression toxicity, T, CPT-11 treated group, Trp, tryptophan, UFLC, ultrafast liquid chromatography, VIP, variable importance in the projection Irinotecan, Individual differences, Complicating toxicity, Prediction, Metabolomics, Gastrointestinal toxicity, Biomarkers, Diarrhea

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Abstract:

Pharmacometabolomics has been already successfully used in toxicity prediction for one specific adverse effect. However in clinical practice, two or more different toxicities are always accompanied with each other, which puts forward new challenges for pharmacometabolomics. Gastrointestinal toxicity and myelosuppression are two major adverse effects induced by Irinotecan (CPT-11), and often show large individual differences. In the current study, a pharmacometabolomic study was performed to screen the exclusive biomarkers in predose serums which could predict late-onset diarrhea and myelosuppression of CPT-11 simultaneously. The severity and sensitivity differences in gastrointestinal toxicity and myelosuppression were judged by delayed-onset diarrhea symptoms, histopathology examination, relative cytokines and blood cell counts. Mass spectrometry-based non-targeted and targeted metabolomics were conducted in sequence to dissect metabolite signatures in predose serums. Eventually, two groups of metabolites were screened out as predictors for individual differences in late-onset diarrhea and myelosuppression using binary logistic regression, respectively. This result was compared with existing predictors and validated by another independent external validation set. Our study indicates the prediction of toxicity could be possible upon predose metabolic profile. Pharmacometabolomics can be a potentially useful tool for complicating toxicity prediction. Our findings also provide a new insight into CPT-11 precision medicine

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