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Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral breast and pancreatic cancer-specific profiles

机译:基于毛细管电泳质谱的唾液代谢组学确定了口腔癌乳腺癌和胰腺癌的特定特征

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摘要

Saliva is a readily accessible and informative biofluid, making it ideal for the early detection of a wide range of diseases including cardiovascular, renal, and autoimmune diseases, viral and bacterial infections and, importantly, cancers. Saliva-based diagnostics, particularly those based on metabolomics technology, are emerging and offer a promising clinical strategy, characterizing the association between salivary analytes and a particular disease. Here, we conducted a comprehensive metabolite analysis of saliva samples obtained from 215 individuals (69 oral, 18 pancreatic and 30 breast cancer patients, 11 periodontal disease patients and 87 healthy controls) using capillary electrophoresis time-of-flight mass spectrometry (CE-TOF-MS). We identified 57 principal metabolites that can be used to accurately predict the probability of being affected by each individual disease. Although small but significant correlations were found between the known patient characteristics and the quantified metabolites, the profiles manifested relatively higher concentrations of most of the metabolites detected in all three cancers in comparison with those in people with periodontal disease and control subjects. This suggests that cancer-specific signatures are embedded in saliva metabolites. Multiple logistic regression models yielded high area under the receiver-operating characteristic curves (AUCs) to discriminate healthy controls from each disease. The AUCs were 0.865 for oral cancer, 0.973 for breast cancer, 0.993 for pancreatic cancer, and 0.969 for periodontal diseases. The accuracy of the models was also high, with cross-validation AUCs of 0.810, 0.881, 0.994, and 0.954, respectively. Quantitative information for these 57 metabolites and their combinations enable us to predict disease susceptibility. These metabolites are promising biomarkers for medical screening.Electronic supplementary materialThe online version of this article (doi:10.1007/s11306-009-0178-y) contains supplementary material, which is available to authorized users.
机译:唾液是一种易于获取且信息丰富的生物流体,使其非常适合早期发现各种疾病,包括心血管,肾脏和自身免疫性疾病,病毒和细菌感染,以及重要的是癌症。基于唾液的诊断,特别是基于代谢组学技术的诊断正在出现,并提供了一种有前途的临床策略,可表征唾液分析物与特定疾病之间的关联。在这里,我们使用毛细管电泳飞行时间质谱法(CE-TOF)对215名个体(69名口服,18名胰腺癌和30名乳腺癌患者,11名牙周病患者和87名健康对照)的唾液样本进行了全面的代谢物分析-多发性硬化症)。我们确定了57种主要代谢产物,可用于准确预测每种疾病所致的可能性。尽管在已知的患者特征和量化的代谢物之间发现了很小但显着的相关性,但与那些牙周疾病患者和对照组相比,这些特征表明在所有三种癌症中检测到的大多数代谢物的浓度相对较高。这表明唾液代谢产物中嵌入了癌症特有的特征。多个逻辑回归模型在受试者工作特征曲线(AUC)下产生了较大的区域,以区分每种疾病的健康对照。口腔癌的AUC为0.865,乳腺癌的AUC为0.973,胰腺癌的AUC为0.993,牙周疾病的AUC为0.969。模型的准确性也很高,交叉验证的AUC分别为0.810、0.881、0.994和0.954。这57种代谢物及其组合的定量信息使我们能够预测疾病的易感性。这些代谢物是用于医学筛查的有前途的生物标志物。电子补充材料本文的在线版本(doi:10.1007 / s11306-009-0178-y)包含补充材料,授权用户可以使用。

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