The Boston University-UCLA Lung Cancer Biomarker Development Lab

波士顿大学-加州大学洛杉矶分校肺癌生物标志物开发实验室

• 批准号: 9277841
• 负责人: DENISE R. ABERLE
• 金额: $ 56.57万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-20 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9277841
• 关键词: Adoption; Appearance; Benign; Biological Markers; Biology; Blinded; Blood; Blood Circulation; Boston; Caliber; Cancer Detection; Cancerous; Categories; Characteristics; Clinical; Clinical Markers; Data; Development Plans; Diagnostic; Discrimination; Eligibility Determination; Environment; Evaluation; Gene Expression; Goals; Image; Individual; Injury; Lung diseases; Lung nodule; Malignant - descriptor; Malignant Neoplasms; Malignant neoplasm of lung; Measures; Medical; Messenger RNA; Methods; MicroRNAs; Modality; Modeling; Molecular; Molecular Biology; Molecular Profiling; Nasal Epithelium; Nodule; Nose; Patients; Performance; Physicians; Plasma; Population; Predictive Cancer Model; Predictive Value; Process; RNA; Risk; Sampling; Series; Small RNA; Smoker; Solid; Specimen; Staging; Testing; Uncertainty; Universities; Unnecessary Procedures; Validation; Visual; X-Ray Computed Tomography; base; biobank; biomarker development; bronchial epithelium; cancer biomarkers; cancer diagnosis; clinical practice; cohort; design; disorder risk; economic cost; exosome; imaging biomarker; improved; lung cancer screening; mRNA Expression; meetings; molecular imaging; molecular marker; predictive modeling; prospective; quantitative imaging; sample collection; screening; tool; transcriptome sequencing; tumor; validation studies

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.

抽象的 随着计算机断层扫描（CT）作为肺癌筛查工具的越来越多的采用，方法 从大量患者中识别出少数恶性结节的患者 良性CT检测结节是不断增长且紧急的临床需求。我们针对的问题 开发用于检测直径为6 - 25 mm的恶性固体或零件固体结节的生物标志物 通过在风险个人处进行筛查或在符合屏幕资格的个体中偶然发现。能力 在这种临床环境中敏感检测肺癌可能会减少许多潜在有害 目前源于这些不确定的肺结所需要的不确定性产生的后果 最激进的工作。我们方法的核心是测量分子生物标志物的整合 在非侵入性收集的鼻刷和等离子体标本中，以及完整的成像和 临床标记。根据我们的初步数据，我们将使用大和大的RNA测序 小的RNA深层表征了鼻上皮的癌症相关的全面损伤领域； 外部衍生的血浆miRNA捕获有关与肿瘤相关产品的信息 循环;以及定性和定量成像特征，以捕获有关生物学的信息 结节和本地环境，否则只能通过直接采样才能获得。 此外，我们将在具有不确定结节的几个独特的吸烟者中分析这些功能 偶然地检测到代表大多数肺癌的临床人群的筛查 被诊断出。我们使用从临床环境中收集的生物库 最终将使用前瞻性特异性，回顾性 - 评估（探针）设计最大程度地减少了潜在偏见，并提高了预期用途的适用性 人口。我们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 然后将用于构建综合癌症预测模型的功能。性能和 所得模型的临床实用性将在拟议的结束时进行初步验证研究 研究。这将使我们能够对他们是否应随后应进行 /不进行决定 根据对其有效性的严格评估以及是否是否 代表了我们缩小中间风险类别的目标的进步，从而改善了 目前有大量临床的大量患者的诊断检查 不确定。