The Lung EArly Proteins project: A LEAP toward implementing biomarkers in lung cancer screening

肺早蛋白项目：在肺癌筛查中实施生物标志物的飞跃

• 批准号: 10700985
• 负责人: Hilary A. Robbins
• 金额: $ 45.17万
• 依托单位: INTERNATIONAL AGENCY FOR RES ON CANCER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-08 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10700985
• 关键词: Address; All-Trans-Retinol; American College of Radiology; Benign; Biological Assay; Biological Markers; Biopsy; Blood; Blood specimen; Cancer Etiology; Carotene; Cessation of life; Classification; Clinical; Decision Aid; Decision Making; Detection; Development; Diagnosis; Diagnostic; Diagnostic Procedure; Early identification; Ensure; Equilibrium; Future; Harm Reduction; Histologic; Intervention; Lung; Lung nodule; Malignant - descriptor; Malignant Neoplasms; Malignant neoplasm of lung; Malignant neoplasm of prostate; Measurement; Measures; Mission; Modeling; Nodule; Participant; Patients; Persons; Primary Care; Prospective, cohort study; Proteins; Risk; Risk Reduction; Sampling; Scanning; Scheme; Screening for Ovarian Cancer; Smoking; Technology; Testing; Time; Translating; Validation; cancer risk; case control; clinical predictors; design; early detection biomarkers; efficacy trial; follow-up; former smoker; high risk; high risk population; improved; innovation; low dose computed tomography; lung cancer screening; lung development; model development; mortality; novel; predictive modeling; predictive tools; prospective; protein biomarkers; risk prediction; screening; screening program; tool; translational study; tv watching

Summary: The Lung EArly Proteins (LEAP) Project Lung cancer is the most common cause of cancer death worldwide. Screening by low-dose CT can reduce lung cancer mortality among current and former smokers, but the balance of benefits and harms could be improved by leveraging novel tools to optimize decision making. Our objective is to translate a novel panel of protein biomarkers to optimize the decision (1) to initiate screening and (2) to biopsy a nodule. We developed the INTEGRAL panel within the Integrative Analysis of Lung Cancer Risk and Etiology U19 project. We identified proteins to include on the panel by analyzing pre-diagnostic samples collected up to 3 years before diagnosis among over 700 lung cancer case-control pairs in prospective cohort studies. The proteins improved the AUC of a smoking-based model by 0.15, with improvements across histological types. The Lung EArly Proteins (LEAP) project will carry out two late-stage translational studies to evaluate the potential to implement this panel in two key contexts. Aim 1 will determine whether repeated measurements of protein markers over time can better predict development of lung cancer than a single measurement. A repeat-measures model for lung cancer will be developed using blood samples (up to 5 per participant) from 546 lung cancer cases and 546 controls in the Prostate, Lung, and Ovarian Cancer Screening Trial, and independently validated using samples from 539 cases and 539 controls from the Carotene and Retinol Efficacy Trial. We hypothesize that the AUC of the model with repeat measurements will be higher than for a model with a single measurement. Aim 2 will determine whether the protein markers can identify cancers among high-risk screen-detected lung nodules. A biomarker-based prediction model for nodule malignancy will be developed using blood samples from 685 participants (131 cancers) in the Pittsburgh Lung Screening Study, and then validated among 830 participants (213 cancers) in the Multicentric Italian Lung Detection (bioMILD) trial and the St Elizabeth Lung Cancer Screening program. We hypothesize that the AUC of the biomarker model will be higher than for an established, validated nodule malignancy prediction model (the Brock model). The LEAP project will clearly define the contexts in which the INTEGRAL panel is clinical useful. Our mission is to reduce lung cancer mortality by optimizing a proven and effective screening intervention, using novel tools to extend its benefits to all high-risk individuals and reduce screening harms.

摘要：肺早期蛋白质（LEAP）项目 肺癌是全球癌症死亡的最常见原因。低剂量CT筛查可以减少 当前和前吸烟者中的肺癌死亡率，但福利和危害的平衡可能是 通过利用新颖的工具来优化决策来改进。我们的目标是翻译一个新颖的面板 蛋白质生物标志物的优化（1）启动筛选的决策和（2）进行活检A结节。 我们在肺癌风险和病因U19的综合分析中开发了整体面板 项目。我们通过分析收集到3个的诊断前样品来鉴定蛋白质在面板上包括在面板上 在前瞻性队列研究中，超过700个肺癌病例对照对的诊断前几年。这 蛋白质将基于吸烟的模型的AUC提高了0.15，组织学的改善 类型。肺早期蛋白质（LEAP）项目将进行两项后期翻译研究以评估 在两个关键上下文中实现此面板的潜力。 AIM 1将确定随着时间的推移重复测量蛋白质标记物是否可以更好地预测 肺癌的发展比单一测量。肺癌的重复测量模型将是 从546例肺癌病例和546个对照中使用血液样本（每个参与者最多5）开发 前列腺，肺和卵巢癌筛查试验，并使用来自 从胡萝卜素和视黄醇疗效试验中进行了539例和539例对照。我们假设AUC的AUC 重复测量的模型将比单个测量值的模型高。 AIM 2将确定蛋白质标志物是否可以识别高风险筛查中的癌症 肺结节。基于生物标志物的结节恶性肿瘤的预测模型将使用血液开发 来自匹兹堡肺部筛查研究中685名参与者（131个癌症）的样本，然后验证 在多中心意大利肺检测（Biomild）试验中的830名参与者（213个癌症）和ST 伊丽莎白肺癌筛查计划。我们假设生物标志物模型的AUC将是 高于已建立的，经过验证的结节恶性预测模型（BROCK模型）。 LEAP项目将清楚地定义整体面板临床有用的上下文。我们的 使命是通过优化经过验证有效的筛查干预措施来降低肺癌死亡率 使用新颖的工具将其收益扩展到所有高危个人并减少筛查危害。