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首页> 外文期刊>Toxicology and Applied Pharmacology >Discriminating between adaptive and carcinogenic liver hypertrophy in rat studies using logistic ridge regression analysis of toxicogenomic data: The mode of action and predictive models
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Discriminating between adaptive and carcinogenic liver hypertrophy in rat studies using logistic ridge regression analysis of toxicogenomic data: The mode of action and predictive models

机译:利用毒灭鼠脊髓瘤回归分析对大鼠研究的适应性和致癌性肝肥大:动作与预测模型模式

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Chemical exposure often results in liver hypertrophy in animal tests, characterized by increased liver weight, hepatocellular hypertrophy, and/or cell proliferation. While most of these changes are considered adaptive responses, there is concern that they may be associated with carcinogenesis. In this study, we have employed a toxicogenomic approach using a logistic ridge regression model to identify genes responsible for liver hypertrophy and hypertrophic hepatocarcinogenesis and to develop a predictive model for assessing hypertrophy-inducing compounds. Logistic regression models have previously been used in the quantification of epidemiological risk factors. DNA microarray data from the Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System were used to identify hypertrophy-related genes that are expressed differently in hypertrophy induced by carcinogens and non-carcinogens. Data were collected for 134 chemicals (72 non-hypertrophy-inducing chemicals, 27 hypertrophy-inducing non-carcinogenic chemicals, and 15 hypertrophy-inducing carcinogenic compounds). After applying logistic ridge regression analysis, 35 genes for liver hypertrophy (e.g.. Acotl and Abcc3) and 13 genes for hypertrophic hepatocarcinogenesis (e.g., Asns and Gpx2) were selected. The predictive models built using these genes were 94.8% and 82.7% accurate, respectively. Pathway analysis of the genes indicates that, aside from a xenobiotic metabolism-related pathway as an adaptive response for liver hypertrophy, amino acid biosynthesis and oxidative responses appear to be involved in hypertrophic hepatocarcinogenesis. Early detection and toxicogenomic characterization of liver hypertrophy using our models may be useful for predicting carcinogenesis. In addition, the identified genes provide novel insight into discrimination between adverse hypertrophy associated with carcinogenesis and adaptive hypertrophy in risk assessment. (C) 2017 Elsevier Inc. All rights reserved.
机译:化学暴露通常导致动物试验中的肝肥大,其特征在于肝脏重量增加,肝细胞肥大和/或细胞增殖。虽然大多数这些变化被认为是适应性的反应,但是担心它们可能与致癌产生相关。在这项研究中,我们使用了使用物流脊回归模型的毒源方法,以鉴定负责肝肥大和肥厚性肝癌发生的基因,并开发用于评估肥大诱导化合物的预测模型。以前已经用于流行病学风险因素的量化逻辑回归模型。来自毒源组虫项目 - 基因组学的DNA微阵列数据辅助毒性评估系统用于鉴定致癌物质和非致癌物质诱导的肥大表达的肥大相关基因。收集了134种化学物质的数据(72个非肥大诱导的化学品,27个肥大诱导的非致癌化学品和15个肥大诱导的致癌化合物)。施用物流脊回归分析后,选择35种用于肝脏肥大(例如ACOT1和ABCC3)和13个基因用于肥大肝癌(例如,ASN和GPX2)。使用这些基因建造的预测模型分别为94.8%和82.7%的准确性。该基因的途径分析表明,除了肝肥大的自适应响应外,该基因的途径表明,肝肥大的适应性响应,氨基酸生物合成和氧化反应似乎参与了肥厚性肝癌发生。使用我们的模型的肝脏肥大的早期检测和毒源性表征可能是可用于预测致癌作用的有用。此外,所识别的基因在风险评估中与致癌和适应性肥厚相关的不良肥大之间的辨别识别提供了新的洞察。 (c)2017年Elsevier Inc.保留所有权利。

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