BIOLOGICALLY BASED CANCER RISK ASSESSMENT FOR MIXTURES

基于生物学的混合物癌症风险评估

• 批准号: 6178391
• 负责人: Georg E. Luebeck
• 金额: $ 24.75万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH CENTER
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-09-01 至 2002-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6178391
• 关键词: cancer risk; carcinogen testing; chemical carcinogen; chemical carcinogenesis; dosage; environmental toxicology; human data; lung neoplasms; toxicant interaction

DESCRIPTION In this proposal we address the problems of estimating and predicting carcinogenic risks from exposure to mixtures of carcinogens. Our approach to this problem will be based on the two mutation clonal expansion (TMCE) model of carcinogenesis. This model can explicitly accommodate both initiators and promoters in the risk assessment process. In this proposal, we make a distinction between simple and complex mixtures. Complex mixtures, such as diesel exhaust, emissions from coke oven batteries, and cigarette smoke, contain hundreds of cancer causing chemicals. Often, however, complex mixtures can be treated as single carcinogens when good data on exposure to the entire mixture are available. Thus, the first objective addresses the problem of estimating cancer risk when a small number of component carcinogens is involved. Questions regarding the roles of the carcinogen type (mode of action), exposure pattern, dose-protraction, and dependency on start and stop of exposures are formulated and their impact on cancer risk explored. Specifically, we focus on human exposures to low and high LET radiation and lung cancer (or death from lung cancer) as the endpoint. Three large data sets will serve to illustrate the usefulness and effectiveness of our approach: the Colorado Plateau Uranium Miners cohort, with detailed individual information on joint exposure to cigarette smoking and exposure to radon; the Chinese Tin Miners data set, with detailed individual information on three lung carcinogens: tobacco smoke, radon progeny and arsenic; and the Life Span Study of the atomic bomb survivors. The second objective concerns the development of appropriate methods for analyzing case-control data using biologically-based models. This provides another tool for assessing the carcinogenic potential of mixtures. The third objective concerns the toxicity equivalency factor (TEF) approach for complex mixtures that may contain numerous chemical components like those mentioned above. To evaluate the usefulness of the TEF approach we propose to analyze the Allegheny/non-Allegheny coke oven cohort data, as an example.

描述 在此提案中，我们解决了估计和预测的问题 暴露于致癌物混合物的致癌风险。 我们的方法 解决这个问题将基于两个突变克隆扩张（TMCE） 癌变模型。 该模型可以明确适应 在风险评估过程中发起人和促进者。 在此提案中， 我们在简单和复杂的混合物之间进行区分。 复杂的 混合物，例如柴油排气，可乐烤箱电池的排放，以及 香烟烟雾，含有数百种引起化学物质的癌症。 经常， 但是，复杂的混合物可以视为单一致癌物 有关暴露于整个混合物的数据。 因此，第一个 目的解决了估计癌症风险的问题 涉及组件致癌物的数量。 有关角色的问题 致癌物类型（作用方式），暴露方式，剂量推论， 并依赖对暴露的起点和停止的依赖，并 对探索癌症风险的影响。 具体而言，我们专注于人类的暴露 低和高辐射和肺癌（或肺癌死亡） 端点。 三个大数据集将有助于说明有用性 我们方法的有效性：科罗拉多高原铀矿工 队列，详细介绍了有关共同暴露于香烟的个人信息 吸烟和暴露于ra;中国锡矿工数据集，带有 有关三种肺癌的详细信息：烟草烟雾， ra子和砷；以及原子弹的寿命研究 幸存者。 第二个目标涉及适当的发展 使用基于生物学的模型来分析病例对照数据的方法。 这提供了评估致癌潜力的另一种工具 混合物。 第三个目标涉及毒性等效因素 （TEF）可能包含大量化学物质的复杂混合物的方法 如上所述的组件。 评估 TEF方法我们建议分析Allegheny/非Allegheny焦炭烤箱 队列数据，例如。