A medium-term gpt delta rat model as an in vivo system for analysis of renal carcinogenesis and the underlying mode of action

作者:Matsushita Kohei; Ishii Yuji; Takasu Shinji; Kuroda Ken; Kijima Aki; Tsuchiya Takuma; Kawaguchi Hiroaki; Miyoshi Noriaki; Nohmi Takehiko; Ogawa Kumiko; Nishikawa Akiyoshi; Umemura Takashi*
来源:Experimental and Toxicologic Pathology, 2015, 67(1): 31-39.
DOI:10.1016/j.etp.2014.09.006

摘要

The kidney is a major target site of chemical carcinogenesis. However, a reliable in vivo assay for rapid identification of renal carcinogens has not been established. The purpose of this study was to develop a new medium-term gpt delta rat model (the GNP model) to facilitate identification of renal carcinogens. In this model, we carried out an in vivo mutation assay using unilaterally nephrectomized kidney tissue and a tumor-promoting assay using residual kidney tissue, with diethylnitrosamine (DEN) as the renal tumor initiator. To clarify the optimal time of DEN injection after nephrectomy, time-dependent changes in bromodeoxyuridine-labeling indices in the tubular epithelium of nephrectomized rats were examined. The optimal dose of DEN injection and sufficient duration of subsequent nitrilotriacetic acid treatment were determined for detection of renal preneoplastic lesions. The standard protocol for the GNP model was determined as follows. Six-week-old female gpt delta rats were treated with test chemicals for 4 weeks, followed by a 2-week washout period, and 40 mg/kg DEN was administered intraperitoneally to initiate renal carcinogenesis. Unilateral nephrectomy was performed 48 h before DEN injection, followed by gpt assays using excised kidney tissues. One week after DEN injection, rats were further exposed to test chemicals for 12 weeks, and histopathological analysis of renal preneoplastic lesions was performed as an indicator of tumor-promoting activity in residual kidney tissue. Validation studies using aristolochic acid, potassium dibasic phosphate, phenylbutazone, and d-limonene indicated the reliability of the GNP model for predicting renal carcinogens and the underlying mode of action.

  • 出版日期2015-1