Biomarkers of lung cancer risk

项目2-肺癌风险的生物标志物 项目摘要/摘要 美国国家肺癌筛查试验(NLST)在2011年表明，使用计算机进行筛查 体层摄影术(CT)扫描可以将肺癌死亡率降低20%，但成本很高，包括 误检率达95%。这项研究还表明，筛查的益处在以下方面存在重要差异 根据潜在肺癌风险界定的不同参与者群体，从而突出了迫切需要 开发改进的风险预测模型，以确定符合条件的筛查对象。 肺癌的生物标记物研究报告了一系列标记物，这些标记物似乎强烈表明肺癌 个人罹患癌症的潜在风险可能与以下信息相结合 以传统问卷为基础的风险因素，特别是烟草接触史。我们假设一个 包含风险信息循环的全面且经过广泛验证的风险预测模型 生物标记物有可能大幅改进现有的风险预测模型，而我们关于 有限的风险生物标记物强烈支持这一假说。我们的项目将集中于系统地 评估一组全面的肺癌风险生物标记物，这些生物标记物与以前的 研究并评估它们可以改进风险预测的程度。这将会实现的 通过汇集正在进行的大规模生物标记物研究的数据，并进行全面的 肺癌队列联盟(LC3)内有前景的风险生物标记物的NOVO分析。 我们将评估我们或其他研究发现的与肺癌有关的一系列有前景的风险生物标记物。 包括miRNAs、代谢、免疫和蛋白质生物标记物以及表观遗传标记物。这个 最初阶段将包括在一个中央实验室对850例病例进行一组有前景的风险生物标志物的分析。 来自美国、欧洲和亚洲的三个预期队列的控制对，随后进行大规模 对来自LC3联盟的另外16个预期队列中最具信息量的标记进行验证， 包括另外1,750对病例对照。个别LC3组的多功能性也将使我们能够 彻底评估重要的美国少数民族，包括非洲裔美国人和西班牙裔美国人。全是肺癌 将纳入的病例是在采血后5年内确诊的。我们预计这将导致 建立用于肺癌风险预测的有效和信息丰富的风险生物标记物的独特小组 模型，这将在与项目3合作的CT筛查研究中得到进一步验证。

Project 2 – Biomarkers of lung cancer risk Project Summary / Abstract The US National Lung Cancer Screening Trial (NLST) demonstrated in 2011 that screening with computed tomography (CT) scans can reduce lung cancer mortality by 20%, but with important costs including a high false-detection rate of 95%. The study also indicated important differences in the benefit of screening in different participant groups as defined by their underlying risk of lung cancer, thus highlighting the urgent need to develop improved risk prediction models for identifying eligible subjects to screen. Biomarker studies of lung cancer have reported a wide range of markers that appear strongly indicative of an individual's underlying risk of developing a cancer that may be combined with information afforded by traditional questionnaire based risk factors, in particular history of tobacco exposure. We hypothesize that a comprehensive and extensively validated risk prediction model that incorporates risk-informative circulating biomarkers has the potential to substantially improve existing risk prediction models, and our pilot data on a limited set of risk biomarkers strongly supports this hypothesis. Our project will focus on systematically assessing a comprehensive panel of biomarkers of lung cancer risk that have been implicated in previous studies, and evaluate the extent to the extent to which they can improve risk prediction. This will be achieved by bringing together data from ongoing large-scale biomarker studies, and conducting a comprehensive de novo analysis of promising risk biomarkers within the Lung Cancer Cohort Consortium (LC3). We will evaluate a wide range of promising risk biomarkers implicated in lung cancer by us or other research groups, including miRNAs, metabolic, immune, and protein biomarkers, as well as epigenetic markers. The initial stage will involve assaying a panel of Promising risk biomarkers at a centralized laboratory for 850 case- control pairs from three prospective cohorts from the US, Europe and Asia, with subsequent large-scale validation of the most informative markers in another 16 prospective cohorts from the LC3 consortium, including 1,750 additional case-control pairs. The versatility of the individual LC3 cohorts will also allow us to thoroughly assess important US minorities, including African American and Hispanic subjects. All lung cancer cases that will be included were diagnosed within 5 years of blood collection. We expect that this will result in establishing a distinct panel of validated and informative risk biomarkers for use in lung cancer risk prediction models, which will be further validated in CT screening studies in collaboration with Project 3.