Preston R Julian
Environmental Carcinogenesis Division, National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.
Environ Mol Mutagen. 2005 Mar-Apr;45(2-3):214-21. doi: 10.1002/em.20093.
The cancer risk assessment process as currently proposed by the U.S. Environmental Protection Agency allows for the use of mechanistic data to inform the low-dose tumor response in humans and in laboratory animals. The aim is to reduce the reliance on defaults that introduce a relatively high level of uncertainty to the risk estimates. The types of data required for this purpose are those that help identify key events in tumor formation following exposure to environmental chemicals. Informative biomarkers of tumor responses could then be developed for describing the shape of a dose-response curve at low doses (i.e., a qualitative assessment) and for predicting tumor frequency at these low doses (i.e., a quantitative assessment). A number of recently developed molecular approaches could aid in the development of qualitatively and quantitatively informative biomarkers. An overview of these with examples of their use is presented. These methods include quantitative gene expression array techniques, quantitative proteomic assays, and the assessment of DNA alterations at the single gene level and at the genome level of detection. It is most likely that a combination of approaches at different levels of cellular organization (i.e., DNA, RNA, and protein) will be the most productive for biomarker development. The rapid progress that is being made will make this tool kit even more applicable for the cancer risk assessment process.
美国环境保护局目前提出的癌症风险评估流程允许使用机制数据来了解人类和实验动物的低剂量肿瘤反应。目的是减少对那些给风险评估带来较高不确定性的默认值的依赖。为此所需的数据类型是有助于识别接触环境化学物质后肿瘤形成关键事件的数据。然后可以开发肿瘤反应的信息性生物标志物，用于描述低剂量下剂量反应曲线的形状（即定性评估）以及预测这些低剂量下的肿瘤频率（即定量评估）。一些最近开发的分子方法有助于开发定性和定量的信息性生物标志物。本文将对这些方法及其应用实例进行概述。这些方法包括定量基因表达阵列技术、定量蛋白质组学分析以及在单基因水平和基因组检测水平上对DNA改变的评估。不同细胞组织水平（即DNA、RNA和蛋白质）的方法组合很可能对生物标志物的开发最有成效。正在取得的快速进展将使这个工具包在癌症风险评估过程中更适用。
