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，方法 用于从大量患者中识别出少数恶性结节患者 CT检出良性结节是临床日益迫切的需求。我们针对的问题是 开发用于检测直径6-25毫米的恶性固体或半固体结节的生物标志物 通过筛查高危个人或偶然在符合筛查条件的个人中发现。有能力 在这种临床环境中敏感地检测到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 最具攻击性的检查。我们方法的核心是测量的分子生物标记物的集成 在非侵入性收集的鼻刷和血浆样本中，结合补充成像和 临床标志物。在我们初步数据的基础上，我们将使用大和大的总RNA测序 小RNA，以深入表征与癌症相关的鼻腔上皮损伤的呼吸道广泛领域； 外显子衍生的血浆miRNA，以捕获有关在 循环；以及定性和定量成像特征，以获取有关脑血管疾病生物学的信息 结核和当地环境，否则只能通过直接采样获得。 此外，我们将在几组患有不确定结节的吸烟者中分析这些特征 偶然发现或通过筛查检测，代表大多数肺癌的临床人群 都被确诊了。我们对从临床环境中收集的生物信息库的使用 生物标记物最终将被应用，利用前瞻性样本收集，回溯盲法- 评估(探测)设计将潜在的偏差降至最低，并提高了对预期用途的适用性 人口。我们生物标记物开发计划的一个关键方面是分两个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相关的分子和成像 这些特征随后将被用于构建集成的癌症预测模型。表演和表演 所产生的模型的临床实用性将在拟议的结束时进行初步验证研究 学习。这将使我们能够就它们是否应该随后进行进行/不进行决定 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，以及它们是否 代表我们朝着缩小中等风险类别的目标取得进展，从而改善 对目前有相当大临床经验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.