Chepelev Nikolai L, Meek M E Bette, Yauk Carole Lyn
Environmental and Radiation Health Sciences Directorate, Health Canada, Ottawa, ON, K1A 0K9, Canada.
J Appl Toxicol. 2014 Nov;34(11):1115-21. doi: 10.1002/jat.3071. Epub 2014 Sep 22.
Reliable quantification of gene and protein expression has potential to contribute significantly to the characterization of hypothesized modes of action (MOA) or adverse outcome pathways for critical effects of toxicants. Quantitative analysis of gene expression by benchmark dose (BMD) modeling has been facilitated by the development of effective software tools. In contrast, protein expression is still generally quantified by a less robust effect level (no or lowest [adverse] effect levels) approach, which minimizes its potential utility in the consideration of dose-response and temporal concordance for key events in hypothesized MOAs. BMD modeling is applied here to toxicological data on testicular toxicity to investigate its potential utility in analyzing protein expression relevant to the proposed MOA to inform human health risk assessment. The results illustrate how the BMD analysis of protein expression in animal tissues in response to toxicant exposure: (1) complements other toxicity data, and (2) contributes to consideration of the empirical concordance of dose-response relationships, as part of the weight of evidence for hypothesized MOAs to facilitate consideration and application in regulatory risk assessment. Lack of BMD analysis in proteomics has likely limited its use for these purposes. This paper illustrates the added value of BMD modeling to support and strengthen hypothetical MOAs as a basis to facilitate the translation and uptake of the results of proteomic research into risk assessment.
对基因和蛋白质表达进行可靠的定量分析,有可能为表征假设的作用模式(MOA)或毒物关键效应的不良结局途径做出重大贡献。有效的软件工具的开发促进了通过基准剂量(BMD)建模对基因表达进行定量分析。相比之下,蛋白质表达通常仍通过一种不太可靠的效应水平(无或最低[不良]效应水平)方法进行定量,这使其在考虑假设的作用模式中关键事件的剂量反应和时间一致性时的潜在效用降至最低。本文将BMD建模应用于睾丸毒性的毒理学数据,以研究其在分析与拟议的作用模式相关的蛋白质表达方面的潜在效用,从而为人类健康风险评估提供信息。结果表明,对动物组织中因接触毒物而产生的蛋白质表达进行BMD分析如何:(1)补充其他毒性数据,以及(2)有助于考虑剂量反应关系的经验一致性,作为假设的作用模式证据权重的一部分,以促进在监管风险评估中的考虑和应用。蛋白质组学中缺乏BMD分析可能限制了其在这些方面的应用。本文阐述了BMD建模的附加价值,以支持和强化假设的作用模式,作为促进将蛋白质组学研究结果转化并应用于风险评估的基础。