Predicting ovarian cancer recurrence by plasma metabolic profiles before and after surgery
Predicting ovarian cancer recurrence by plasma metabolic profiles before and after surgery
复制标题
通过手术前后血浆代谢谱预测卵巢癌复发
DOI：
10.1007/s11306-018-1354-8
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发表时间：
2018-05-01
期刊：
影响因子：
3.6
通讯作者：
Li, Kang
中科院分区：
文献类型：
--
作者：
Zhang, Fan;Zhang, Yuanyuan;Li, Kang
背景：先前的代谢组学研究显示血浆代谢特征可以预测上皮性卵巢癌（EOC）的复发。然而，很少有研究进行代谢分析的术前和术后标本调查EOC预后biologicals.Objective我们的研究的目的是比较术前和术后标本的预测性能，并建立一个更好的模型复发相结合的生物标志物从两个代谢signature.Methods三十五配对血浆样本收集35例EOC患者手术前后。患者随访至2016年12月，以获得复发信息。采用快速分辨液相色谱-质谱法进行代谢组学，以确定与EOC复发相关的代谢特征。支持向量机模型被用来预测EOC复发，使用确定的生物标志物。结果全球代谢组学概况区分复发性和非复发性EOC使用术前和术后血浆。10种常见的重要生物标志物，羟苯乳酸，尿酸，肌酐，赖氨酸，3-（3，5-二碘-4-羟基苯基）乳酸，磷酸羟基丙酮酸，肉毒碱，粪卟啉原，1-β-乙酰基-L-谷氨酸和24，25-羟基维生素D3，被确定为EOC复发的预测生物标志物。术前和术后血浆AUC值的曲线下面积分别为0.815和0.909，合并后AUC值为0.964。结论血浆代谢组学分析可用于预测卵巢癌复发。虽然术后生物标志物比术前生物标志物具有预测优势，但术前和术后生物标志物的组合显示出最佳的预测性能，并且具有预测复发性EOC的巨大潜力。
Background Previous metabolomic studies have revealed that plasma metabolic signatures may predict epithelial ovarian cancer (EOC) recurrence. However, few studies have performed metabolic profiling of pre- and post-operative specimens to investigate EOC prognostic biomarkers.Objective The aims of our study were to compare the predictive performance of pre- and post-operative specimens and to create a better model for recurrence by combining biomarkers from both metabolic signatures.Methods Thirty-five paired plasma samples were collected from 35 EOC patients before and after surgery. The patients were followed-up until December, 2016 to obtain recurrence information. Metabolomics using rapid resolution liquid chromatography-mass spectrometry was performed to identify metabolic signatures related to EOC recurrence. The support vector machine model was employed to predict EOC recurrence using identified biomarkers.Results Global metabolomic profiles distinguished recurrent from non-recurrent EOC using both pre- and post-operative plasma. Ten common significant biomarkers, hydroxyphenyllactic acid, uric acid, creatinine, lysine, 3-(3,5-diiodo-4-hydroxyphenyl) lactate, phosphohydroxypyruvic acid, carnitine, coproporphyrinogen, l-beta-aspartyl-l-glutamic acid and 24,25-hydroxyvitamin D3, were identified as predictive biomarkers for EOC recurrence. The area under the receiver operating characteristic (AUC) values in pre- and post-operative plasma were 0.815 and 0.909, respectively; the AUC value after combining the two sets reached 0.964.Conclusion Plasma metabolomic analysis could be used to predict EOC recurrence. While post-operative biomarkers have a predictive advantage over pre-operative biomarkers, combining pre- and post-operative biomarkers showed the best predictive performance and has great potential for predicting recurrent EOC.