The Boston Lung Cancer Survival Cohort

摘要 肺癌是一种异质性疾病，是美国与癌症相关的头号杀手。了解 这种异质性的分子原因是当前基础和翻译研究的重点。《波士顿肺报》 癌症研究(BLCS)是马萨诸塞州登记的11,000多名肺癌病例的癌症流行病学队列 1992年至今，在总医院和达纳-法伯癌症研究所工作。这是第一次也是最全面的 幸存者队列具有最长的随访期，到本拟议周期结束时将增至14 000人以上 通过额外的招募来增强具有致癌驱动器突变状态的样本。通过识别 相关患者，并通过DANA内的合作提供关键的存档肿瘤组织- 法伯/哈佛癌症中心(DF/HCC)肺癌项目，BLCS支持了第一个发现 EGFR突变与EGFR-TKIs治疗反应的相关性开启靶向治疗时代 在肺癌方面。我们现在正在申请支持现有的队列基础设施，并恢复招聘 通过合作协议获得新的案例。主要目标有3个方面：1)维护肺癌核心 对肺癌生存研究的未来科学需求进行分类并最大限度地发挥其潜力；2)使切割- 通过流行病学方法开发方法论和试点方法来解决边缘研究问题 转变为生产性的多学科项目赠款，旨在研究生存的各个方面，以及 治疗毒性；以及3)利用DF/HCC肺计划资源进行创造性的多学科 合作的重点是治疗结果。招募新病例进入大队列的理由包括： 1)促进新疗法与传统疗法的评价和新临床研究设计 在不断变化的治疗环境中进行调查；2)收集更多罕见致癌因素的病例 突变；3)包括有准确的组织学、吸烟史和突变负荷分析的患者 免疫治疗；4)收集适合于发展预后/预测的重复生物样本 生物标志物；以及5)允许更好地评估较少研究的小细胞肺癌(SCLC)。此应用程序 还将支持我们建立一个创新的COPD表型数据库，通过自动图像分析高- 分辨率计算机断层扫描，以及放射组学数据库，以及开发一种新的分析方法 来自电子病历(EMR)的相关遗传流行病学数据和信息 正在进行的R35奖(林锡鸿博士)。BLCS队列是为数不多的做出重大贡献的生存队列之一 关于生存状态的数据，以及可用的肿瘤突变数据和组织。结合生物标记物数据、肿瘤 分子特征、CT成像和传统的流行病学风险因素数据将使强大的 翻译研究并提供独特的机会进一步探索生存和治疗的预测因素 结果。我们的目标是保持BLCS后续行动和相关数据的质量，并制定 将为调查人员提供新机会的方法。

ABSTRACT Lung cancer is a heterogeneous disease and the leading cancer-related killer in the United States. Understanding the molecular causes of this heterogeneity is the focus of current basic and translational research. The Boston Lung Cancer Study (BLCS) is cancer epidemiology cohort of over 11,000 lung cancer cases enrolled at Massachusetts General Hospital and the Dana-Farber Cancer Institute from 1992-present. This is the first and most comprehensive survivor cohort with the longest follow-up period, and will grow to over 14,000 by the end of this proposed cycle with additional recruitment to enhance the samples with oncogenic driver mutation status. By identifying the relevant patients and providing critical archived tumor tissues, through collaboration within the Dana- Farber/Harvard Cancer Center (DF/HCC) Lung Cancer Program, the BLCS supported the first discovery of the association between EGFR mutations and response to therapy with EGFR-TKIs, initiating the era of targeted therapy in lung cancer. We are now applying for support of the existing cohort infrastructure and resume the recruitment of new cases through a cooperative agreement. The overarching aims are 3-fold: 1) To maintain the lung cancer core cohort and maximize its potential for future scientific needs for lung cancer survival research; 2) To enable cutting- edge research questions by epidemiologic methods development methodologic, and piloting approaches that will turn into productive multidisciplinary project grants aimed at studying various aspects of survival, as well as treatment toxicity; and 3) To leverage the DF/HCC lung program resources for creative multidisciplinary collaborations focused on treatment outcomes. The rationale for recruiting new cases into the large cohort include: 1) facilitating the evaluation between new treatments and traditional therapy and the study design of new clinical investigation in an ever-changing therapeutic environment; 2) collecting more cases with rare oncogenic driver mutations; 3) including patients with accurate histology, smoking histories, and mutational load analyses treated with immunotherapy; 4) collecting repeated biological samples suitable for development of prognostic/predictive biomarkers; and 5) allowing better assessment of the less-studied small-cell lung cancer (SCLC). This application will also support us to establish an innovative COPD phenotyping database via automated image analysis of high- resolution computed tomography, as well as a radiomics data base, as well as to develop a new method of analyzing linked genetic epidemiologic data and information from electronic medical records (EMR) with support from an ongoing R35 award (Dr. Xihong Lin). The BLCS cohort is one of the few survival cohorts contributing substantial data on survival status, with tumor mutation data and tissue available. The combination of biomarker data, tumor molecular characterization, CT imaging and traditional epidemiologic risk factor data will allow powerful translational research and provide unique opportunities to further explore predictors of survival and treatment outcomes. We aim to maintain the quality of the BLCS follow-up and associated data as well as to develop approaches that will provide novel opportunities to investigators.