Exosomal proteins as potential diagnostic markers in advanced non-small cell lung carcinoma.
Exosomal proteins as potential diagnostic markers in advanced non-small cell lung carcinoma.
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DOI：
10.3402/jev.v4.26659
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发表时间：
2015
影响因子：
16
通讯作者：
Jørgensen MM
中科院分区：
文献类型：
--
作者：
Jakobsen KR;Paulsen BS;Bæk R;Varming K;Sorensen BS;Jørgensen MM
肺癌是癌症相关死亡的主要原因之一。在诊断时，超过一半的患者将有播散性疾病，然而，诊断可能具有挑战性。需要新的方法来改进诊断检查。外泌体是细胞衍生的囊泡，在其膜表面显示各种蛋白质。此外，它们很容易在血液样本中获得，在那里它们构成人类疾病（如癌症）的潜在生物标志物。在这里，我们研究了基于外泌体蛋白标记物的差异显示区分非小细胞肺癌（NSCLC）患者与对照组的潜力。从109名晚期（IIIa-IV） NSCLC患者和110名匹配的对照组中分离出血浆，这些患者最初怀疑患有癌症，但被诊断为无癌症。使用细胞外囊泡阵列（EV Array）直接从血浆样品中对外泌体进行表型分析。该阵列包含37种靶向肺癌相关蛋白的抗体，用于捕获外泌体，并用生物素结合的CD9、CD63和CD81抗体的混合物将其可视化。EV Array分析能够仅从10µL未纯化血浆中检测所有样品中的外泌体并对其进行表型分析。使用随机森林方法进行多变量分析，产生了一个30个标记的联合模型，将两组患者分开，曲线下面积为0.83,CI: 0.77-0.90。30个标记模型的敏感性为0.75，特异性为0.76，对患者的分类准确率为75.3%。EV阵列技术是一种简单、微创的工具，具有鉴别肺癌患者的潜力。
Lung cancer is one of the leading causes of cancer-related death. At the time of diagnosis, more than half of the patients will have disseminated disease and, yet, diagnosing can be challenging. New methods are desired to improve the diagnostic work-up. Exosomes are cell-derived vesicles displaying various proteins on their membrane surfaces. In addition, they are readily available in blood samples where they constitute potential biomarkers of human diseases, such as cancer. Here, we examine the potential of distinguishing non-small cell lung carcinoma (NSCLC) patients from control subjects based on the differential display of exosomal protein markers. Plasma was isolated from 109 NSCLC patients with advanced stage (IIIa–IV) disease and 110 matched control subjects initially suspected of having cancer, but diagnosed to be cancer free. The Extracellular Vesicle Array (EV Array) was used to phenotype exosomes directly from the plasma samples. The array contained 37 antibodies targeting lung cancer-related proteins and was used to capture exosomes, which were visualised with a cocktail of biotin-conjugated CD9, CD63 and CD81 antibodies. The EV Array analysis was capable of detecting and phenotyping exosomes in all samples from only 10 µL of unpurified plasma. Multivariate analysis using the Random Forests method produced a combined 30-marker model separating the two patient groups with an area under the curve of 0.83, CI: 0.77–0.90. The 30-marker model has a sensitivity of 0.75 and a specificity of 0.76, and it classifies patients with 75.3% accuracy. The EV Array technique is a simple, minimal-invasive tool with potential to identify lung cancer patients.