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) 作为肺癌筛查工具，方法 用于从大量患者中识别出少数患有恶性结节的患者 CT 检测到的良性结节是一种日益增长且紧迫的临床需求。我们针对的问题是 开发用于检测直径为 6 – 25 毫米的恶性实性或部分实性结节的生物标志物 通过筛查有风险的个体来识别或在符合筛查条件的个体中偶然发现。有能力 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哪些需要进行治疗而产生的后果 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以及补充成像和 临床标志物。根据我们的初步数据，我们将使用大RNA和大RNA的总RNA测序。 小RNA可深入表征鼻上皮中与癌症相关的气道范围内的损伤； 外泌体衍生的血浆 miRNA，用于捕获血浆中发现的肿瘤相关产物的信息 流通；以及定性和定量成像特征，以捕获有关生物学的信息 结核和当地环境，否则只能通过直接采样获得。 此外，我们将在几个具有不确定结节的独特吸烟者群体中分析这些特征 偶然或通过筛查发现的代表大多数肺癌的临床人群 被确诊。我们使用从临床环境中收集的生物样本库，其中 最终将利用前瞻性样本收集、回顾性盲法应用生物标记物 评估（PRoBE）设计最大限度地减少潜在偏差并提高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利用患者队列来检测与癌症密切相关的分子和成像 然后将用于构建综合癌症预测模型的特征。性能和 由此产生的模型的临床效用将在拟议的研究结束时进行初步验证研究 研究。这将使我们能够做出是否应该随后进行的决定 在更大规模的验证试验中进行了测试，基于对其有效性的严格评估以及它们是否 代表我们在缩小中等风险类别的目标方面取得了进展，从而改善了 对目前有大量临床资料的大量患者进行诊断检查 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.