Exhaled microRNAs leveraged for lung cancer risk assessment

呼出的 microRNA 用于肺癌风险评估

基本信息

批准号：
8815714
负责人：
SIMON D SPIVACK
金额：
$ 10.76万
依托单位：
ALBERT EINSTEIN COLLEGE OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-12-08 至 2015-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8815714
关键词：
Age Biological Markers Breath Tests Case-Control Studies Clinical Coupled Data Databases Detection Discrimination Early Diagnosis Enrollment Exhalation Funding Mechanisms Goals Hand Histology Incidence Individual Lesion Literature Lung Malignant Epithelial Cell Malignant Neoplasms Malignant neoplasm of lung Measures MicroRNAs Nested Case-Control Study Non-Small-Cell Lung Carcinoma Performance Phenotype Premalignant Prevalence Prevention strategy Research Design Resected Risk Assessment Risk Factors Risk Marker Sampling Smoking Status Staging Structure of parenchyma of lung Surveys Technology Testing Validation Work X-Ray Computed Tomography base cancer prevention cancer risk case control cohort design follow-up high risk improved indexing innovation low-dose spiral CT lung cancer screening prospective public health relevance screening tool tumor

项目摘要

DESCRIPTION (provided by applicant): Early lung cancer screening by low-dose CT scanning, though apparently effective, is notoriously inefficient as currently devised. In this R21 application, it is proposed that exhaled microRNAs carry a signature that will be useful in identifying those at highest risk for lung malignancy. In previous work, we surveyed the microRNAome of non-small cell lung cancers, compared to adjacent lung tissue. Recently, we generated qualitative pilot data for a 14-miR panel of exhaled microRNAs in 95 individuals, where discrimination of cases from controls in the distilled 4-microRNA test panel entailed an accuracy of 76% (ROC-AUC=0.76), and when coupled with simple clinical factors, improved to 84% (AUC=0.84), an acceptable performance level for risk factor indices. In the interim, we have recently evolved the technology further to be more robust and quantitative. Our hypothesis is: An exhaled microRNA signature will distinguish those individuals that harbor a lung cancer from those who do not. In a broadened Einstein-based case-control study, we now wish to augment discriminant capacity of the microRNA tools by: (1) increasing the microRNA panel to ~35-40 microRNAs, in part from premalignant lesion micro dissected signatures, and also render the exhaled signature to be quantitative; (2) expand the case- control study three-fold to allow covariate analysis, improve case and control phenotype ascertainment, by lengthening our window of immediate post-enrollment follow-up, along with covariate adjustment; and (3) pilot test the best exhaled microRNA biomarkers using a nested case-control design that is accruing in a prospective lung cancer CT screening setting. These three aims will allow a more robust, rigorous testing of the exhaled microRNA approach for both association with the lung cancer phenotype in a case-control study, and validation in a nested case-control study of putative high risk individuals undergoing CT screening. If favorable in these pilots, we would then embed the technology in prospective CT screening cohorts, using other more expansive funding mechanisms. The implications for leveraging early lung cancer detection and prevention strategies are substantial.

描述（由申请人提供）：低剂量CT扫描虽然显然有效，但正如目前所设计的那样效率低下。在此R21中应用，建议呼出的microRNA具有签名，该签名将有助于确定肺部恶性肿瘤风险最高的人。在先前的工作中，我们调查了与邻近的肺组织相比，非小细胞肺癌的微肿瘤组。最近，我们在95个人中生成了一个14电动的呼出microRNA面板的定性试验数据，在其中，从蒸馏蒸馏器4-microrna测试面板中歧视案件的案例需要76％的精度（ROC-AUC = 0.76）（ROC-AUC = 0.76），而与简单的临床因素相关，并提高了对84％（AUC = 0.84）的范围（= 0.84）。在此期间，我们最近进一步发展了这项技术，以更加稳健和定量。我们的假设是：呼出的microRNA签名将使那些怀有肺癌的人与那些没有肺癌的人区分开。在一项基于爱因斯坦的病例对照研究中，我们现在希望通过以下方式提高microRNA工具的判别能力：（1）将microRNA面板提高到〜35-40 microRNA，部分原因是预先陈述性病变微型解剖的签名，并使诱因的签名是定义的；（2）扩展三倍的案例控制研究，以允许协变量分析，改善病例和控制表型确定，并通过延长立即的注册后随访窗口以及协变量调整；（3）使用嵌套的病例对照设计，试点呼出的microRNA生物标志物，该设计在预期的肺癌CT筛查环境中进行。这三个目标将在病例对照研究中对呼出的microRNA方法进行更严格，更严格的测试，以使其与肺癌表型相关联，并在嵌套的病例对照研究中对正在接受CT筛查的假定高风险个体进行验证。如果在这些飞行员中有利，我们将使用其他更广泛的资金机制将技术嵌入潜在的CT筛选队列中。利用早期肺癌检测和预防策略的影响是很大的。