Plasma metabolite biomarkers for the detection of pancreatic cancer.
Plasma metabolite biomarkers for the detection of pancreatic cancer.
复制标题
DOI：
10.1021/pr501135f
复制
发表时间：
2015-02-06
影响因子：
4.4
通讯作者：
Jia, Wei
中科院分区：
文献类型：
--
作者：
Xie, Guoxiang;Lu, Lingeng;Qiu, Yunping;Ni, Quanxing;Zhang, Wei;Gao, Yu-Tang;Risch, Harvey A.;Yu, Herbert;Jia, Wei
关键词：
胰腺癌（PC）患者通常在晚期才被诊断出来，此时该疾病几乎无法治愈。敏感和特异性标记物对于支持诊断和治疗策略至关重要。本研究的目的是利用代谢组学方法来识别潜在的血浆生物标志物，这些生物标志物可以进一步开发用于 PC 的早期检测。在这项研究中，使用气相和液相色谱质谱联用技术对来自美国康涅狄格州 (CT) 的新诊断 PC 患者 (n = 100) 和年龄和性别匹配的对照 (n = 100) 以及来自中国上海 (SH) 的相同数量的病例和对照的血浆代谢物进行了分析。 CT和SH样本中一致表达的代谢物被用来鉴定潜在的标记物，并在两个样本组中测试候选标记物的诊断性能。使用谷氨酸、胆碱、1,5-脱水-d-葡萄糖醇、甜菜碱和甲基胍等五种代谢物构建了诊断模型，该模型以高灵敏度 (97.7%) 和特异度 (83.1%)（接受者操作特征曲线下面积 [AUC] = 0.943，95% 置信区间 [CI] = 0.908–0.977)。然后用 SH 数据集测试这组代谢物，获得令人满意的准确性（AUC = 0.835；95% CI = 0.777–0.893），敏感性为 77.4%，特异性为 75.8%。该模型在 CT 中 0、1 和 2 期 PC 患者中的敏感性为 84.8%，在 SH 中 1 和 2 期 PC 患者中的敏感性为 77.4%。血浆代谢特征显示出作为早期检测 PC 的生物标志物的前景。
Patients with pancreatic cancer (PC) are usually diagnosed at late stages, when the disease is nearly incurable. Sensitive and specific markers are critical for supporting diagnostic and therapeutic strategies. The aim of this study was to use a metabonomics approach to identify potential plasma biomarkers that can be further developed for early detection of PC. In this study, plasma metabolites of newly diagnosed PC patients (n = 100) and age- and gender-matched controls (n = 100) from Connecticut (CT), USA, and the same number of cases and controls from Shanghai (SH), China, were profiled using combined gas and liquid chromatography mass spectrometry. The metabolites consistently expressed in both CT and SH samples were used to identify potential markers, and the diagnostic performance of the candidate markers was tested in two sample sets. A diagnostic model was constructed using a panel of five metabolites including glutamate, choline, 1,5-anhydro-d-glucitol, betaine, and methylguanidine, which robustly distinguished PC patients in CT from controls with high sensitivity (97.7%) and specificity (83.1%) (area under the receiver operating characteristic curve [AUC] = 0.943, 95% confidence interval [CI] = 0.908–0.977). This panel of metabolites was then tested with the SH data set, yielding satisfactory accuracy (AUC = 0.835; 95% CI = 0.777–0.893), with a sensitivity of 77.4% and specificity of 75.8%. This model achieved a sensitivity of 84.8% in the PC patients at stages 0, 1, and 2 in CT and 77.4% in the PC patients at stages 1 and 2 in SH. Plasma metabolic signatures show promise as biomarkers for early detection of PC.
登录
查看更多内容
影响因子：
15.9
作者：
Cheng, LL;Anthony, DC;Gonzalez, RG
通讯作者：
Gonzalez, RG
胃癌的蛋白质组学和代谢组学联合分析揭示了葡萄糖代谢的特征性失调
影响因子：
7
作者：
Cai, Zhen;Zhao, Jiang-Sha;Xie, Dong
通讯作者：
Xie, Dong
DOI：
10.1158/1055-9965.epi-13-0584
发表时间：
2013-12
期刊：
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
影响因子：
--
作者：
Liesenfeld DB;Habermann N;Owen RW;Scalbert A;Ulrich CM
通讯作者：
Ulrich CM
影响因子：
1.8
作者：
Nicholson, JK;Lindon, JC;Holmes, E
通讯作者：
Holmes, E
DOI：
10.1016/j.bpg.2006.01.004
发表时间：
2006-01-01
影响因子：
3.2
作者：
Meier, Remy F.;Beglinger, Christoph
通讯作者：
Beglinger, Christoph