Validation and extension of an existing risk model for lung cancer

现有肺癌风险模型的验证和扩展

基本信息

批准号：
7911887
负责人：
RANDA A EL-ZEIN
金额：
$ 61.55万
依托单位：
UNIVERSITY OF TX MD ANDERSON CAN CTR
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-08-12 至 2013-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7911887
关键词：
5 year old Age Apoptosis Area Biological Assay Biological Markers Cancer Center Cancer Etiology Cancer Family Cancer Patient Case-Control Studies Caucasians Caucasoid Race Chemoprevention Chromosomal Breaks Chromosomal Instability Chromosomes Cytogenetics Cytokinesis DNA Sequence Rearrangement Data Data Set Detection Disease End Point Assay Enrollment Epidemiology Ethnic Origin Evaluation Event Family history of Gene Amplification Genetic Genotype Goals Health Benefit Individual Individual Differences Intervention Interview Malignant Neoplasms Malignant neoplasm of lung Measures Medical History Methods Micronucleus Tests Modeling Necrosis Nitrosamines Nuclear Occupational Exposure Participant Phenotype Population Predisposition Probability Public Health Public Health Schools ROC Curve Research Research Personnel Risk Sampling Screening procedure Smoking History Smoking Status Staging Subgroup Survival Rate Tobacco Validation base cancer risk case control design gene environment interaction high risk improved micronucleus mortality novel parent grant programs sex smoking cessation tobacco carcinogenesis tool

项目摘要

The public health implications of reliable risk prediction tools for estimating the probability of lung cancer, the leading cause of cancer mortality in the US, are immense. In this proposal, we build upon an epidemiologic risk model for lung cancer that we recently developed from a lung cancer case-control study of 1851 Caucasian lung cancer patients and 2001 controls, matched to the cases on sex, age (±5 years), smoking status (current, former, never) and ethnicity from the parent grant (ROl CA55679, P1: M. Spitz). This risk model also estimates an individual's absolute risk for lung cancer. Using an independent data set from this study and an external data set of lung cancer cases and controls from Dr. David Christiani (co-investigator, Harvard School of Public Health, CA74386), we propose to validate the lung cancer risk model and extend it by incorporating a genetic biomarker of risk. Specifically: 1). In 800 prospectively accrued cases and 800controls using the recruitment mechanisms of parent grant, we will validate our original model and then assess the added discriminatory ability of a promising novel cytogenetic biomarker, the cytokinesis-block micronucleus (CBMN) assay, a multi-endpoint assay that measures not only chromosome damage (micronuclei reflecting chromosome breaks; nucleoplasmic bridges reflecting chromosome rearrangements and nuclear buds reflecting gene amplification) but also other cellular events (apoptosis and necrosis). We will measure these endpoints at baseline and following challenge with the tobacco-specific nitrosamine, NNK. We will derive a method to integrate these different measures of chromosome/genetic instability into the epidemiologic lung cancer risk model. 2). Using the findings from aim 1, we will construct an extended risk model to include measures of chromosome instability and gene-environment interactions. Our preliminary data show that our current model has moderate discriminatory power (70%), we believe that extending the model to includes these biomarkers of chromosome instability as well as gene environment interactions will only improve the discriminatory power of our model. This newly developed model may be useful to identify high-risk populations who could then be targeted for intensive smoking-cessation programs and could be enrolled into chemopreven-tion screening trials. 3). Internally validate the original and extended lung cancer risk models using an additional set of 500 prospectively enrolled lung cancer cases and 500 controls using the recruitment mechanisms of parent grant and compare the discriminatory power between the extended model to that of the original Spitz model between the two models. This will also include independent, internal, validation of the CBMN assay. Evaluation of these chromosomal endpoints in an independent sample will provide proof-of-principle for subsequent inclusion of additional functional phenotypes and genotypes into the model.

肺癌是美国癌症死亡的主要原因，用于估计肺癌概率的可靠风险预测工具对公共卫生的影响是巨大的。在这项提案中，我们基于最近开发的肺癌流行病学风险模型。肺癌病例对照研究，纳入了 1851 名白人肺癌患者和 2001 名对照者，与性别、年龄（±5 岁）、吸烟状况（当前、以前、从未）和父母资助的种族（ROl CA55679，P1：M. Spitz）该风险模型还使用本研究的独立数据集以及来自 David Christiani 博士（共同研究者）的肺癌病例和对照的外部数据集来估计个体患肺癌的绝对风险。，哈佛大学公共卫生学院，CA74386），我们建议通过纳入风险的遗传生物标志物来验证肺癌风险模型并对其进行扩展，具体而言：1）。 800controls 使用父母资助的招募机制，我们将验证我们的原始模型，然后评估一种有前途的新型细胞遗传学生物标志物的附加辨别能力，即胞质分裂阻断微核 (CBMN) 测定，这是一种多端点测定，不仅测量染色体损伤（反映染色体断裂的微核；反映染色体重排的核质桥和反映基因扩增的核芽）以及其他细胞事件（细胞凋亡和坏死）。我们将得出一种方法，将这些不同的染色体/遗传不稳定性测量方法整合到流行病学肺癌风险模型中。构建一个扩展的风险模型，以包括染色体不稳定性和基因-环境相互作用的测量，我们的初步数据表明，我们当前的模型具有中等的辨别力（70％），我们相信扩展模型以包括染色体不稳定性的这些生物标志物。基因环境相互作用只会提高我们模型的区分能力。这种新开发的模型可能有助于识别高风险人群，然后将其作为强化戒烟计划的目标，并可纳入化学预防筛查试验3)。使用额外的 500 个前瞻性入组肺癌病例和 500 个对照（使用家长资助的招募机制）建立原始和扩展肺癌风险模型，并比较两个模型之间扩展模型与原始 Spitz 模型之间的区分力。这还将包括对独立样本中这些染色体终点的独立、内部验证，将为随后将其他功能表型和基因型纳入模型提供原理证明。