Integrative analysis of lung cancer etiology and risk

摘要-总体 自1985年以来，肺癌（LC）一直是最常见的癌症，导致超过180万人死亡 每年全球。LC的生存率很低，5年死亡率约为90%，这主要是因为其通常的晚期死亡率。 分期诊断低剂量CT（LDCT）可降低高剂量肺癌患者的总体和肺癌特异性死亡率。 暴露吸烟者，但产生过多的阳性结果，目前无法识别许多病例。这个程序 该项目追求一套全面和互补的研究议程，以了解 吸烟与肺癌通过整合吸烟领域的一整套研究， ILCCO、TRICL和LC 3联合体中的生物标志物，并在NLST背景下对其进行评价 和其他5项肺癌筛查试验，可以在肺癌的早期发现方面取得实质性进展。 项目1：吸烟肺癌风险的基因组预测研究大样本，以确定不常见的 变异，低风险的变异，以及通过基因-环境相互作用或 干扰的途径，并进一步使用这一信息研究环境的影响。项目二： 肺癌风险的生物标志物评估了广泛的风险生物标志物，这些生物标志物被认为是 有前景的肺癌风险生物标志物，包括miRNA、代谢、免疫、蛋白质和表观遗传标志物， 使用来自肺癌队列联盟（LC 3）的诊断前生物标本，并将确定一组 用于风险预测模型的经验证的风险生物标志物项目3：翻译分子和临床 肺癌风险评估建立了一个综合风险预测模型， 美国、加拿大和欧洲的肺癌CT筛查人群，结合个人健康和暴露 历史，靶向分子和基因组谱以及肺功能数据，并建立全面的 基于两种方法的LDCT检测非钙化肺结节个体的结节评估模型 基于直径和基于体积的概率模型。这些研究得到了整合 行政和生物统计核心。项目之间的科学协同作用创造了效率 以及共享样本和数据的使用。我们认为，P01与三个 一个互补的项目朝着统一的目标努力，将产生关于肺癌的新的观察结果。 开发并提供独特的转化机会，以完善筛选资格标准， 有助于提高筛查效率，进一步降低肺癌死亡率。

Abstract – Overall Lung Cancer (LC) has been the most common cancer since 1985, resulting in over 1.8 million deaths worldwide per year. LC survival is dismal with a 5 year mortality of about 90%, largely because of its usual late stage diagnosis. Low dose CT (LDCT) reduces overall and lung cancer specific mortality among highly exposes smokers but yields excess positive findings and currently fails to identify many cases. This program project pursues a comprehensive and complementary set of research agendas to understand predictors of smoking and lung cancer. By integrating a comprehensive set of studies in the domains of smoking, genomics and biomarkers in the ILCCO, TRICL and LC3 consortia, and evaluating them together in the context of NLST and 5 other lung cancer screening trials, substantial progress can be made in early detection of lung cancer. Project 1: Genomic Predictors of Smoking Lung Cancer Risk studies large samples to identify uncommon variants, variants with low risk, and variants that affect risk through gene-environment interactions or through perturbations of pathways and further uses this information for studying environmental exposures. Project 2: Biomarkers of Lung Cancer Risk evaluates a wide range of risk biomarkers that have been implicated as promising lung cancer risk biomarkers, including miRNAs, metabolic, immune, protein, and epigenetic markers, using pre-diagnostic biospecimen from the Lung Cancer Cohort Consortium (LC3), and will identify a panel of validated risk biomarkers for use in risk prediction models Project 3: Translating Molecular and Clinical Data to Population Lung Cancer Risk Assessment establishes an integrated risk prediction model-based on lung cancer CT screening populations in US, Canada and Europe, combining personal health and exposure history, targeted molecular and genomic profiles and lung function data, and establishes comprehensive nodule assessment models for individuals with LDCT-detected non-calcified pulmonary nodules based on both diameter-based and volume-based probability models . These research studies are supported by integrating Administrative and Biostatistics cores. Efficiency is created from the scientific synergies among the projects and the use of shared samples and data. We believe that this level of integration across the P01 with three complementary projects working towards a unifying goal will yield novel observations about lung cancer development and provide unique translational opportunities to refine screening eligibility criteria and ultimately help improve screening efficiency and further reduce lung cancer mortality.