A blood-based proteomic classifier for the molecular characterization of pulmonary nodules.
A blood-based proteomic classifier for the molecular characterization of pulmonary nodules.
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DOI：
10.1126/scitranslmed.3007013
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发表时间：
2013-10-16
影响因子：
17.1
通讯作者：
Kearney P
中科院分区：
文献类型：
--
作者：
Li XJ;Hayward C;Fong PY;Dominguez M;Hunsucker SW;Lee LW;McLean M;Law S;Butler H;Schirm M;Gingras O;Lamontagne J;Allard R;Chelsky D;Price ND;Lam S;Massion PP;Pass H;Rom WN;Vachani A;Fang KC;Hood L;Kearney P
每年有数以百万计的肺结节被计算机断层扫描发现，随后进行活检。由于大多数结节是良性的，许多患者接受不必要的和昂贵的侵入性手术。我们提出了一种基于13种蛋白质血液的分类器，该分类器以高置信度区分恶性和良性结节，从而提供了一种诊断工具，以避免对良性结节进行侵入性活检。使用系统生物学策略，确定了371种候选蛋白，并为每种蛋白开发了多反应监测（MRM）测定。MRM测定法应用于三位点发现研究（n = 143）中，该研究对来自良性和IA期癌症患者的血浆样品进行结节大小、年龄、性别和临床位点匹配，产生13蛋白分类器。该分类器在一组独立的血浆样品（n = 104）上进行了验证，表现出90%的高阴性预测值（NPV）。来自非发现临床研究中心的样本的验证性能显示NPV为94%，表明分类器的一般有效性。通路分析表明，分类器蛋白可能受到与肺癌、肺部炎症和氧化应激网络相关的一些转录调节因子（NF 2L2、AHR、MYC、FOS）的调节。分类器评分与患者结节大小、吸烟史和年龄无关，这些是用于肺结节临床管理的风险因素。因此，这种分子检测可以为医生在肺癌诊断中提供强有力的补充工具。
Each year millions of pulmonary nodules are discovered by computed tomography and subsequently biopsied. As the majority of these nodules are benign, many patients undergo unnecessary and costly invasive procedures. We present a 13-protein blood-based classifier that differentiates malignant and benign nodules with high confidence, thereby providing a diagnostic tool to avoid invasive biopsy on benign nodules. Using a systems biology strategy, 371 protein candidates were identified and a multiple reaction monitoring (MRM) assay was developed for each. The MRM assays were applied in a three-site discovery study (n = 143) on plasma samples from patients with benign and Stage IA cancer matched on nodule size, age, gender and clinical site, producing a 13-protein classifier. The classifier was validated on an independent set of plasma samples (n = 104), exhibiting a high negative predictive value (NPV) of 90%. Validation performance on samples from a non-discovery clinical site showed NPV of 94%, indicating the general effectiveness of the classifier. A pathway analysis demonstrated that the classifier proteins are likely modulated by a few transcription regulators (NF2L2, AHR, MYC, FOS) that are associated with lung cancer, lung inflammation and oxidative stress networks. The classifier score was independent of patient nodule size, smoking history and age, which are risk factors used for clinical management of pulmonary nodules. Thus this molecular test can provide a powerful complementary tool for physicians in lung cancer diagnosis.
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影响因子：
11.5
作者：
Iizasa, T;Chang, H;Fujisawa, T
通讯作者：
Fujisawa, T
影响因子：
3.4
作者：
Deutsch, EW;Eng, JK;Aebersold, R
通讯作者：
Aebersold, R
DOI：
10.1073/pnas.1013699108
发表时间：
2011-02-22
影响因子：
11.1
作者：
Cima, Igor;Schiess, Ralph;Krek, Wilhelm
通讯作者：
Krek, Wilhelm
影响因子：
3
作者：
Brusniak, Mi-Youn;Bodenmiller, Bernd;Watts, Julian D.
通讯作者：
Watts, Julian D.
影响因子：
5.3
作者：
Jones, J. Mark;McGonigle, Niall C.;Graham, Alastair N.
通讯作者：
Graham, Alastair N.