BIOLOGICALLY BASED CANCER RISK ASSESSMENT FOR MIXTURES

描述 在这个建议中，我们解决的问题，估计和预测 暴露于致癌物混合物的致癌风险。 我们的方法 针对这一问题，将基于两突变克隆扩增（TMCE） 致癌模型。 该模型可以明确地适应这两种情况 在风险评估过程中的发起人和推动者。 在这一提议中， 我们区分简单混合物和复杂混合物。 复杂 混合物，如柴油机废气、焦炉组排放物，以及 香烟烟雾中含有数百种致癌化学物质。 很多时候， 然而，复杂的混合物可以作为单一的致癌物处理， 关于接触整个混合物的数据是可用的。 因此第一 目标解决了估计癌症风险的问题时，小 涉及致癌物质的数量。 关于角色的问题 致癌物类型（作用方式）、接触模式、剂量延长、 以及对曝光开始和停止的依赖性， 对癌症风险的影响。 具体来说，我们关注人类接触 低和高LET辐射和肺癌（或肺癌死亡）， 终点。 三个大型数据集将有助于说明 我们的方法的有效性：科罗拉多高原铀矿工人 队列，包含联合暴露于香烟的详细个体信息 吸烟和氡暴露;中国锡矿工人数据集， 关于三种肺致癌物的详细个人信息：烟草烟雾， 氡子体和砷;以及原子弹寿命研究 幸存者 第二个目标是发展适当的 使用生物学模型分析病例对照数据的方法。 这提供了另一种评估致癌潜力的工具， 混合物。 第三个目标涉及毒性当量系数 (TEF)处理可能含有多种化学物质的复杂混合物的方法 就像上面提到的那样。 为了评估 TEF方法，我们建议分析阿勒格尼/非阿勒格尼焦炉 以队列数据为例。

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.