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Cytotoxicity of 34 FDA approved small-molecule kinase inhibitors in primary rat and human hepatocytes

细胞毒性 最大值 肝细胞 乳酸脱氢酶 药理学 毒性 化学 丙氨酸转氨酶 生物化学 生物 药代动力学 体外 内分泌学 有机化学
作者
Jun Zhang,Lijun Ren,Xi Yang,Matthew White,James Greenhaw,Tashika Harris,Qiangen Wu,Matthew Bryant,Thomas Papoian,William B. Mattes,Qiang Shi
出处
期刊:Toxicology Letters [Elsevier]
卷期号:291: 138-148 被引量:27
标识
DOI:10.1016/j.toxlet.2018.04.010
摘要

Of the 34 FDA approved oral small-molecule kinase inhibitors (KI), 23 (68%) have warnings for hepatotoxicity in product labeling. To better understand the mechanisms of KI hepatotoxicity and whether such effects can be predicted, we examined 34 KIs for cytotoxicity in primary rat and human hepatocytes. The hepatocytes were treated with KIs at ten concentrations normalized to maximal therapeutic blood levels (Cmax). At 5 and 24 h post treatment, lactate dehydrogenase or alanine aminotransferase leakage, caspase 3/7 activities and cellular adenosine triphosphate levels were measured. At 1 to 100-fold Cmax, while 5 KIs were neither toxic to human nor rat hepatocytes, 3 KIs showed similar cytotoxicity in both species and 26 KIs showed species-biased cytotoxicity, with 16 KIs being more toxic to human hepatocytes and 10 KIs being more toxic to rat hepatocytes. At concentrations of 1-, 2.5-, 5-, 10-, 100-fold Cmax, the number of cytotoxic KIs in human hepatocytes was 4, 8, 11, 14 and 27, respectively, and the corresponding number in rat hepatocytes was 1, 4, 9, 12 and 27, respectively. When hepatocyte cytotoxicity at 100-fold Cmax was used to predict KI clinical hepatotoxicity reflected in product labeling, the accuracy was 0.65 with human hepatocytes and 0.59 with rat cells. When the criterion of daily dose ≥100 mg or Cmax ≥1.1 μM was used to predict KI hepatotoxicity, the accuracy was 0.56 or 0.47, respectively. These results suggest both indirect and direct drug-induced hepatocyte toxicity may contribute to the mechanisms of KI-induced hepatotoxicity seen clinically and use of primary hepatocytes is a useful in vitro model to help predict such toxicity.
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