循环外泌体来源的 microRNAs 作为筛查和诊断肺癌的非侵入性生物标志物。
microRNAs derived from circulating exosomes as noninvasive biomarkers for screening and diagnosing lung cancer.
机构信息
Center of Predictive Molecular Medicine, Center of Excellence on Aging, †Oncological and Cardiovascular Molecular Medicine Unit, University-Foundation, Chieti, Italy.
出版信息
J Thorac Oncol. 2013 Sep;8(9):1156-62. doi: 10.1097/JTO.0b013e318299ac32.
INTRODUCTION
Lung cancer is the highest cause of mortality among tumor pathologies worldwide. There are no validated techniques for an early detection of pulmonary cancer lesions other than low-dose helical computed tomography scan. Unfortunately, this method has some negative effects. Recent studies have laid the basis for development of exosomes-based techniques to screen/diagnose lung cancers. As the isolation of circulating exosomes is a minimally invasive procedure, this technique opens new possibilities for diagnostic applications.
METHODS
We used a first set of 30 plasma samples from as many patients, including 10 patients affected by lung adenocarcinomas, 10 with lung granulomas, and 10 healthy smokers matched for age and sex as negative controls. Wide-range microRNAs analysis (742 microRNAs) was performed by quantitative real time polymerase chain reaction. Data were compared on the basis of lesion characteristics, using WEKA software for statistics and modeling. Subsequently, selected microRNAs were evaluated on an independent larger group of samples (105 specimens: 50 lung adenocarcinomas, 30 lung granulomas, and 25 healthy smokers).
RESULTS
This analysis led to the selection of four microRNAs to perform a screening test (miR-378a, miR-379, miR-139-5p, and miR-200b-5p), useful to divide population into two groups: nodule (lung adenocarcinomas + carcinomas) and non-nodule (healthy former smokers). Six microRNAs (miR-151a-5p, miR-30a-3p, miR-200b-5p, miR-629, miR-100, and miR-154-3p) were selected for a second test on the nodule population to discriminate between lung adenocarcinoma and granuloma.
CONCLUSIONS
The screening test showed 97.5% sensitivity, 72.0% specificity, and area under the curve receiver operating characteristic of 90.8%. The diagnostic test had 96.0% sensitivity, 60.0% specificity, and area under the curve receiver operating characteristic of 76.0%. Further evaluation is needed to confirm the predictive power of these models on larger cohorts of samples.
简介
肺癌是全球肿瘤病理学中死亡率最高的疾病。除了低剂量螺旋 CT 扫描外，目前尚无其他方法可以早期发现肺癌病变。不幸的是，这种方法有一些负面影响。最近的研究为基于外泌体的技术的发展奠定了基础，这些技术可用于筛查/诊断肺癌。由于分离循环外泌体是一种微创程序，因此该技术为诊断应用开辟了新的可能性。
方法
我们使用了第一组 30 个血浆样本，这些样本来自 30 名患者，包括 10 名患有肺腺癌的患者、10 名患有肺肉芽肿的患者和 10 名年龄和性别匹配的健康吸烟者作为阴性对照。通过实时定量聚合酶链反应进行广泛的 microRNA 分析（742 个 microRNA）。根据病变特征，使用 WEKA 软件进行统计和建模来比较数据。随后，在一个更大的独立样本组（105 个标本：50 个肺腺癌、30 个肺肉芽肿和 25 个健康吸烟者）中评估了选定的 microRNAs。
结果
该分析选择了 4 个 microRNA 进行筛选测试（miR-378a、miR-379、miR-139-5p 和 miR-200b-5p），可将人群分为两组：结节（肺腺癌+癌）和非结节（健康前吸烟者）。选择了另外 6 个 microRNA（miR-151a-5p、miR-30a-3p、miR-200b-5p、miR-629、miR-100 和 miR-154-3p）对结节人群进行第二次测试，以区分肺腺癌和肉芽肿。
结论
筛选测试的灵敏度为 97.5%，特异性为 72.0%，ROC 曲线下面积为 90.8%。诊断测试的灵敏度为 96.0%，特异性为 60.0%，ROC 曲线下面积为 76.0%。需要进一步评估以确认这些模型在更大样本队列中的预测能力。
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