• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

比较方法在开放式 TG-GATEs 中的应用:一种用于检测化学风险评估中作用模式的有用毒理学工具。

Application of the comparison approach to open TG-GATEs: A useful toxicogenomics tool for detecting modes of action in chemical risk assessment.

机构信息

Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands; Neurotoxicology Research Group, Toxicology and Pharmacology Division, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands.

Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.

出版信息

Food Chem Toxicol. 2018 Nov;121:115-123. doi: 10.1016/j.fct.2018.08.007. Epub 2018 Aug 8.

DOI:10.1016/j.fct.2018.08.007
PMID:30096367
Abstract

Mode of action information is one of the key components for chemical risk assessment as mechanistic insight leads to better understanding of potential adverse health effects of a chemical. This insight greatly facilitates assessment of human relevance and enhances the use of non-animal methods for risk assessment, as it ultimately enables extrapolation from initiating events to adverse effects. Recently, we reported an in vitro toxicogenomics comparison approach to categorize (non-)genotoxic carcinogens according to similarities in their proposed modes of action. The present study aimed to make this comparison approach generally applicable, allowing comparison of outcomes across different studies. The resulting further developed comparison approach was evaluated through application to toxicogenomics data on 18 liver toxicants in human and rat primary hepatocytes from the Open TG-GATEs database. The results showed sensible matches between compounds with (partial) overlap in mode of action, whilst matches for compounds with different modes of action were absent. Comparison of the results across species revealed pronounced and relevant differences between primary rat and human hepatocytes, underpinning that information on mode of action enhances assessment of human relevance. Thus, we demonstrate that the comparison approach now is generally applicable, facilitating its use as tool in mechanism-based risk assessment.

摘要

作用模式信息是化学风险评估的关键组成部分之一,因为机制理解有助于更好地了解化学物质潜在的不良健康影响。这种理解极大地促进了对人类相关性的评估,并增强了对非动物方法在风险评估中的使用,因为它最终能够从引发事件推断出不良反应。最近,我们报告了一种体外毒理学基因组学比较方法,根据其提议的作用模式的相似性对(非)遗传毒性致癌物进行分类。本研究旨在使这种比较方法具有普遍适用性,允许跨不同研究比较结果。通过将进一步开发的比较方法应用于来自 Open TG-GATEs 数据库的人类和大鼠原代肝细胞中 18 种肝毒物的毒理学基因组学数据,对其进行了评估。结果表明,作用模式部分重叠的化合物之间存在合理的匹配,而作用模式不同的化合物之间则没有匹配。对跨物种的结果进行比较表明,大鼠和人原代肝细胞之间存在明显且相关的差异,这表明作用模式信息增强了对人类相关性的评估。因此,我们证明该比较方法现在具有普遍适用性,可作为基于机制的风险评估的工具。

相似文献

1
Application of the comparison approach to open TG-GATEs: A useful toxicogenomics tool for detecting modes of action in chemical risk assessment.比较方法在开放式 TG-GATEs 中的应用:一种用于检测化学风险评估中作用模式的有用毒理学工具。
Food Chem Toxicol. 2018 Nov;121:115-123. doi: 10.1016/j.fct.2018.08.007. Epub 2018 Aug 8.
2
Relevance of Transcriptomics for Mode of Action Assessment.转录组学在作用模式评估中的相关性。
Chem Res Toxicol. 2021 Feb 15;34(2):452-459. doi: 10.1021/acs.chemrestox.0c00313. Epub 2020 Dec 30.
3
A novel transcriptomics based in vitro method to compare and predict hepatotoxicity based on mode of action.一种基于转录组学的新型体外方法,用于基于作用模式比较和预测肝毒性。
Toxicology. 2015 Feb 3;328:29-39. doi: 10.1016/j.tox.2014.11.008. Epub 2014 Dec 2.
4
A novel toxicogenomics-based approach to categorize (non-)genotoxic carcinogens.一种基于毒代动力学基因组学的新型方法来对(非)遗传毒性致癌物进行分类。
Arch Toxicol. 2015 Dec;89(12):2413-27. doi: 10.1007/s00204-014-1368-6. Epub 2014 Oct 2.
5
DTNI: a novel toxicogenomics data analysis tool for identifying the molecular mechanisms underlying the adverse effects of toxic compounds.DTNI:一种用于识别有毒化合物不良反应潜在分子机制的新型毒理基因组学数据分析工具。
Arch Toxicol. 2017 Jun;91(6):2343-2352. doi: 10.1007/s00204-016-1922-5. Epub 2016 Dec 28.
6
Toxicogenomics directory of rat hepatotoxicants in vivo and in cultivated hepatocytes.大鼠在体和原代肝细胞肝毒物毒理学基因组目录。
Arch Toxicol. 2018 Dec;92(12):3517-3533. doi: 10.1007/s00204-018-2352-3. Epub 2018 Dec 3.
7
Comparison of toxicogenomics and traditional approaches to inform mode of action and points of departure in human health risk assessment of benzo[a]pyrene in drinking water.毒理基因组学与传统方法在告知饮用水中苯并[a]芘的人类健康风险评估作用机制和起始点方面的比较
Crit Rev Toxicol. 2015 Jan;45(1):1-43. doi: 10.3109/10408444.2014.973934.
8
The human hepatocyte TXG-MAPr: gene co-expression network modules to support mechanism-based risk assessment.人类肝细胞 TXG-MAPr:支持基于机制的风险评估的基因共表达网络模块。
Arch Toxicol. 2021 Dec;95(12):3745-3775. doi: 10.1007/s00204-021-03141-w. Epub 2021 Oct 9.
9
Parallelogram approach using rat-human in vitro and rat in vivo toxicogenomics predicts acetaminophen-induced hepatotoxicity in humans.采用大鼠-人类体外和大鼠体内毒理基因组学的平行四边形法可预测对乙酰氨基酚诱导的人类肝毒性。
Toxicol Sci. 2009 Feb;107(2):544-52. doi: 10.1093/toxsci/kfn237. Epub 2008 Nov 12.
10
Use of toxicogenomics to understand mechanisms of drug-induced hepatotoxicity during drug discovery and development.在药物发现和开发过程中利用毒理基因组学来理解药物性肝损伤的机制。
Toxicol Lett. 2009 Apr 10;186(1):22-31. doi: 10.1016/j.toxlet.2008.09.017. Epub 2008 Oct 17.

引用本文的文献

1
A strategy to detect metabolic changes induced by exposure to chemicals from large sets of condition-specific metabolic models computed with enumeration techniques.一种利用枚举技术计算的针对特定条件的代谢模型的大集合来检测暴露于化学物质引起的代谢变化的策略。
BMC Bioinformatics. 2024 Jul 11;25(1):234. doi: 10.1186/s12859-024-05845-z.
2
An Adverse Outcome Pathway Network for Chemically Induced Oxidative Stress Leading to (Non)genotoxic Carcinogenesis.化学诱导氧化应激导致(非)遗传毒性致癌的不良结局途径网络。
Chem Res Toxicol. 2023 Jun 19;36(6):805-817. doi: 10.1021/acs.chemrestox.2c00396. Epub 2023 May 8.
3
A multi-label learning model for predicting drug-induced pathology in multi-organ based on toxicogenomics data.
基于毒代动力学数据的多器官药物诱导病变多标签学习模型。
PLoS Comput Biol. 2022 Sep 7;18(9):e1010402. doi: 10.1371/journal.pcbi.1010402. eCollection 2022 Sep.
4
Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology.在监管毒理学中转录组学和代谢组学的经合组织报告框架的进展。
Regul Toxicol Pharmacol. 2021 Oct;125:105020. doi: 10.1016/j.yrtph.2021.105020. Epub 2021 Jul 29.