| 袁道祎,韩 骏,韩敏露,刘武纬,谢 瑛.基于UPLC-QTOF/MS的胆囊癌血清非靶向代谢组学研究[J].,2020,(17):3201-3206 |
| 基于UPLC-QTOF/MS的胆囊癌血清非靶向代谢组学研究 |
| UPLC-QTOF/MS Based Serum Untargeted Metabolomics Study of Gallbladder Carcinoma |
| 投稿时间：2020-02-27 修订日期：2020-03-23 |
| DOI：10.13241/j.cnki.pmb.2020.17.001 |
| 中文关键词: 胆囊癌 代谢组学 标志物 |
| 英文关键词: Gallbladder Carcinoma Metabolomics Biomarker |
| 基金项目:国家重点研发计划项目（2017YFC1309701）；国家十三五科技重大专项（2017ZX09304016）；十三五新药创制重大专项（2018ZX09734005） |
|
| 摘要点击次数: 735 |
| 全文下载次数: 442 |
| 中文摘要: |
| 摘要 目的：胆囊癌（Gallbladder carcinoma，GBC）是一种常见的胆道系统恶性肿瘤，五年生存率极低，目前临床上缺少有效的诊断标志物。故本研究探索胆囊癌患者与健康人血清的差异性小分子代谢物，用于胆囊癌的定性诊断。方法：本研究以超高效液相色谱联用四极杆飞行时间质谱（UPLC-QTOF/MS）技术为平台，以32例胆囊癌患者和32例健康人血清为研究对象，进行非靶向代谢组学研究分析，用SIMCA-P软件进行PCA和OPLS-DA建模分析，结合T检验结果和代谢物在两组中的差异倍数来筛选潜在小分子代谢标志物，并通过二元逻辑回归分析建立联合诊断模型。结果：溶血磷脂酰胆碱(18:1)（LysoPC(18:1)）和十八烷胺（Octadecylamine，ODA）两个代谢物在胆囊癌患者和健康对照组血清中具有显著性差异, 差异倍数达到2倍以上。经过二元逻辑回归分析建立诊断模型，两者构建联合诊断的诊断模型为Logit[P=GBC]=26.090*[LysoPC(18:1)]-8.877*[ODA]-113.075，据此建立受试者工作特征曲线（Receiver operating characteristic，ROC）曲线，曲线下面积（Area under the curve，AUC）为0.986，灵敏度为97.1%，特异性为94.6%。结论：LysoPC(18:1)和ODA可作为胆囊癌的潜在诊断标志物，为胆囊癌的诊断提供参考。 |
| 英文摘要: |
| ABSTRACT Objective: Gallbladder carcinoma (GBC) is a common malignancy of the biliary tract system, with a poor five-year survival rate and for lack of effective diagnostic biomarkers. Thus the aim of this study is to explore the different small metabolites in serum of GBC patients and healthy subjects. Methods: Based on the Ultra-performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) technique, serum untargeted metabolomics studies of 32 GBC patients and 32 healthy controls were developed. Potential biomarkers were screened by PCA and OPLS-DA analysis using SIMCA-P software, followed by t-test and fold change analysis. Then a diagnostic model was established. Results: The levels of LysoPC(18:1) and Octadecylamine (ODA) in GBC patients serum had changed (>2-fold change). A diagnostic panel based on these two metabolites for the detection of GBC was constructed as follows: Logit[P=GBC]=26.090*[LysoPC(18:1)]-8.877*[ODA]-113.075. The receiver operating characteristic (ROC) curve analysis of a combination of LysoPC(18:1) and ODA was then conducted. Outstanding discrimination has been achieved with area under the curve (AUC) of 0.986, sensitivity of 97.1% and specificity of 94.6%. Conclusion: LysoPC(18:1) and ODA can be used for discrimination between GBC patients and healthy subjects. |
|
查看全文
查看/发表评论 下载PDF阅读器 |
| 关闭 |
