Integrating Biomarkers into Lung Cancer Risk Profiling

项目2：将生物标志物纳入肺癌风险分析 总结 低剂量计算机断层扫描（LDCT）筛查彻底改变了肺癌的早期检测， 癌症死亡的主要原因。然而，目前的资格标准要求参与者有以下病史： 大量吸烟。戒烟多年的人被排除在外，那些从未戒烟的人也是如此。 吸烟。目前，30-50%的肺癌发生在不符合筛查条件的个体中， 吸烟率下降，这些数字将增加。项目2的总体目标是解决这一问题 通过利用血液生物标志物的补充信息来识别个体的挑战 尽管不符合筛查资格标准，但肺癌风险较高。 我们的项目是最初的INTEGRAL计划的自然延伸，我们在那里开发了小说 INTEGRAL蛋白质生物标志物组，测量关键风险生物标志物的绝对浓度。在 INTEGRAL-AT项目2，我们的目标是将INTEGRAL面板推向临床实施， 用从不吸烟者的肺癌风险标志物更新小组。我们先建立一个生物标记物- 吸烟相关肺癌的知情风险预测模型。这将涉及使用INTEGRAL面板 对1,700例肺癌病例和2,900例肺癌队列代表的蛋白质测量 队列联盟（LC 3）开发并独立验证一个模型，该模型估计3年绝对值 肺癌的风险。第二，我们会评估是否可以接受采用以生物标记为基础的资格 筛选参与者的标准。这将涉及招募1,000名“接近合格”的人， 美国预防服务工作组在圣伊丽莎白社区的LDCT筛查标准 程序.最后，我们将对616例从不吸烟的病例进行从头蛋白质组学发现分析 和616名来自LC 3的匹配对照，以鉴定从不吸烟者肺癌的新蛋白质标记物， 更新INTEGRAL面板以包含这些标记。 我们的长期愿景是，通过使用个性化的信息， 可实施多重蛋白质组，肺癌筛查可以更精确地针对 患肺癌的风险很高。这将使更高比例的肺癌病例能够早期发现， 让更多的人接受LDCT筛查，从而优化获益与危害的比例。我们还设想 这个小组将是非常有用的筛选范围以外的工作，从不吸烟的患者， 肺癌家族史、职业暴露或出现症状的患者。

Project 2: Integrating Biomarkers into Lung Cancer Risk Profiling Summary Screening by low-dose computed tomography (LDCT) has revolutionized early detection of lung cancer, the leading cause of cancer death. However, current eligibility criteria require participants to have a history of heavy smoking exposure. People with many years of cessation are excluded, as are those who never smoked. Currently, 30-50% of lung cancers occur in individuals who are not eligible for screening, and with decreasing smoking rates, these numbers will increase. The overarching aim of Project 2 is to address this challenge by leveraging complementary information from blood-based biomarkers to identify individuals who have high lung cancer risk despite not meeting screening eligibility criteria. Our project is a natural extension of the initial INTEGRAL program where we developed the novel INTEGRAL protein biomarker panel which measures absolute concentrations of key risk biomarkers. In INTEGRAL-AT Project 2, we aim to move the INTEGRAL panel towards clinical implementation, and also update the panel with risk markers of lung cancer in never smokers. We will first establish a biomarker- informed risk prediction model for smoking-related lung cancer. This will involve using the INTEGRAL panel protein measurements on 1,700 lung cancer cases and 2,900 cohort representatives from the Lung Cancer Cohort Consortium (LC3) to develop and independently validate a model that estimates the 3-year absolute risk of lung cancer. Second, we will evaluate the acceptability of applying such a biomarker-based eligibility criterion to screening participants. This will involve recruiting 1,000 individuals who are ‘nearly eligible’ by US Preventive Services Task Force criteria within the St Elizabeth community based LDCT screening program. Finally, we will carry out a de-novo proteomics discovery analysis on 616 never-smoking cases and 616 matched controls from LC3 to identify novel protein markers for lung cancer in never smokers and update the INTEGRAL panel to include these markers. Our long-term vision is that by using personalized information from a risk-informative and readily implementable multiplex protein-panel, lung cancer screening can be more precisely targeted to people at high risk of lung cancer. This would allow a higher fraction of lung cancer cases to be detected early without subjecting more individuals to LDCT screening, thus optimizing the benefit-to-harm ratio. We also envisage that this panel will be highly useful outside the screening context to work up never-smoking patients with a family history of lung cancer, with occupational exposures, or who present with symptoms.