The Boston University-UCLA Lung Cancer Biomarker Development Lab

摘要 随着越来越多地采用计算机断层扫描（CT）作为肺癌的筛查工具， 用于从大量患者中识别少数恶性结节患者 CT检测的良性结节是一个不断增长的和迫切的临床需求。我们针对的问题是 开发用于检测直径为6 - 25 mm的恶性实体或部分实体结节的生物标志物， 通过筛查高危个体或在符合筛查条件的个体中偶然发现。的能力 在这种临床环境中灵敏地检测肺癌可以减少许多潜在的有害因素， 目前由于不确定这些不确定的肺结节中的哪一个需要 最积极的检查我们方法的核心是整合测量的分子生物标志物 在非侵入性收集的鼻刷和血浆样本中， 临床标志物在我们初步数据的基础上，我们将使用大的和 小RNA深入表征鼻上皮中癌症相关的气道损伤范围; 外泌体来源的血浆miRNA来捕获关于在肿瘤细胞中发现的肿瘤相关产物的信息。 循环;以及定性和定量成像特征，以捕获关于 结核和当地环境之间的关系，否则只能通过直接取样获得。 此外，我们将在几个独特的吸烟者不确定的结节队列中分析这些特征 偶然或通过筛查检测到的，代表了大多数肺癌 被诊断出来。我们使用从临床环境中收集的生物储存库， 生物标志物将最终应用，利用前瞻性标本收集，回顾性盲法， 评估（PRoBE）设计最大限度地减少了潜在偏倚，并提高了对预期用途的适用性 人口我们的生物标志物开发计划的一个关键方面是一个两阶段的特征选择过程， 将使我们能够有效地使用患者队列来检测与癌症相关的分子和成像 这些特征将用于构建综合癌症预测模型。性能和 最终模型的临床实用性将在拟议的 问题研究这将使我们能够就是否应随后 在更大的验证试验中进行测试，基于对其有效性的严格评估， 代表着我们朝着缩小中等风险类别的目标取得了进展，从而改善了 对大量患者的诊断检查，目前有相当多的临床 不确定性

ABSTRACT With the increasing adoption of computed tomography (CT) as a screening tool for lung cancer, methods for identifying the small number of patients with malignant nodules from among the large number of patients with benign CT-detected nodules is a growing and urgent clinical need. We have targeted the problem of developing biomarkers for detecting malignant solid or part-solid nodules that are 6 – 25 mm in diameter that are identified by screening at risk individuals or found incidentally in screen-eligible individuals. The ability to sensitively detect lung cancer in this clinical setting could reduce many of the potentially harmful consequences that currently arise from uncertainties about which of these indeterminate lung nodules require the most aggressive workup. The core of our approach is the integration of molecular biomarkers measured in non-invasively collected nasal brushes and plasma specimens together with complementary imaging and clinical markers. On the basis of our preliminary data, we will use total RNA sequencing of both large and small RNA to deeply characterize the cancer-associated airway-wide field of injury in nasal epithelium; exosome-derived plasma miRNA to capture information about tumor-associated products found in the circulation; and qualitative and quantitative imaging characteristics to capture information about the biology of the nodule and the local environment that would otherwise only be available through direct sampling. Further, we will be profiling these features in several unique cohorts of smokers with indeterminate nodules detected either incidentally or by screening that represent the clinical population in which most lung cancers are diagnosed. Our use of biorepositories that have been collected from the clinical settings in which the biomarker would ultimately be applied, utilizing a prospective-specimen-collection, retrospective-blinded- evaluation (PRoBE) design minimizes potential bias and improves applicability to the intended use population. A key aspect of our biomarker development plan is a two-staged feature selection process that will allow us to efficiently use patient cohorts to detect robustly cancer-associated molecular and imaging features that will then be used to construct integrated cancer predictive models. The performance and clinical utility of the resulting models will undergo preliminary validation studies at the end of the proposed studies. This will allow us to make a GO / NO-GO decision about whether they should be subsequently tested in larger validation trials based on a rigorous evaluation of their validity and also whether they represent progress toward our goal of shrinking the intermediate risk category, thereby improving the diagnostic workup of the large number of patients for whom there is currently considerable clinical uncertainty.