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基于 LC-MS 的血清代谢组学在泌尿生殖系统癌症分类和癌症类型特异性生物标志物发现中的应用。

LC-MS-based serum metabolic profiling for genitourinary cancer classification and cancer type-specific biomarker discovery.

机构信息

Department of Chemistry, Key Laboratory of Analytical Sciences, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China.

出版信息

Proteomics. 2012 Aug;12(14):2238-46. doi: 10.1002/pmic.201200016.

Abstract

Bladder cancer (BC) and kidney cancer (KC) are the first two commonly occurring genitourinary cancers in China. In this study, a comprehensive LC-MS-based method, which utilizes both reversed phase liquid chromatography (RPLC) and hydrophilic interaction chromatography (HILIC) separations, has been carried out in conjunction with multivariate data analysis to discriminate the global serum profiles of BC, KC, and noncancer controls. An independent test set consisting of different patients has been used to objectively evaluate the predictive ability of the analysis platform. Excellent sensitivity and specificity have been achieved in detection of KC and BC. The results suggest that serum metabolic profiling could be used for different types of genitourinary cancer diagnosis. Furthermore, cancer type-specific biomarkers were found through a critical selection criterion. As a result, eicosatrienol, azaprostanoic acid, docosatrienol, retinol, and 14'-apo-beta-carotenal  were found as specific biomarkers for BC; and PE(P-16:0e/0:0), glycerophosphorylcholine, ganglioside GM3 (d18:1/22:1), C17 sphinganine, and SM(d18:0/16:1(9Z)) were found as specific biomarkers for KC. Receiver operating characteristic (ROC) analysis was used for the preliminary evaluation of the biomarkers. These biomarkers have great potential to be used in the clinical diagnosis after further rigorous assessment.

摘要

膀胱癌(BC)和肾癌(KC)是中国前两种常见的泌尿生殖系统癌症。在本研究中,我们结合多元数据分析,采用基于 LC-MS 的综合方法,同时利用反相液相色谱(RPLC)和亲水相互作用色谱(HILIC)分离,对 BC、KC 和非癌症对照者的全球血清谱进行区分。我们使用由不同患者组成的独立测试集来客观评估分析平台的预测能力。该分析平台在检测 KC 和 BC 方面具有优异的灵敏度和特异性。结果表明,血清代谢组学可用于不同类型的泌尿生殖系统癌症的诊断。此外,我们还通过严格的筛选标准找到了癌症类型特异性的生物标志物。结果表明,二十碳三烯醇、氮杂前列烷酸、二十二碳三烯醇、视黄醇和 14'-脱-β-胡萝卜素可作为 BC 的特异性生物标志物;而 PE(P-16:0e/0:0)、甘油磷酸胆碱、神经节苷脂 GM3(d18:1/22:1)、C17 神经酰胺和 SM(d18:0/16:1(9Z))可作为 KC 的特异性生物标志物。我们使用接收者操作特征(ROC)分析对生物标志物进行了初步评估。这些生物标志物在经过进一步严格评估后,有可能用于临床诊断。

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