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Serum metabolic fingerprinting to detect human nasopharyngeal carcinoma based on gas chromatography-mass spectrometry and partial least squares-linear discriminant analysis

机译:基于气相色谱-质谱和偏最小二乘-线性判别分析的血清代谢指纹图谱检测人鼻咽癌

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摘要

In this paper, metabolic fingerprints were obtained from 102 nasopharyngeal carcinoma (NPC) patients and 107 healthy adults by gas chromatography-mass spectrometry (GC/ MS). Partial least squares-discriminant analysis (PLS-DA) has revealed a pattern recognition discriminating the patients from controls, which sensitivity is 89.72% (96/107) and specificity is 85.29% (87/102). Furthermore, double-blind experiment was carried out and satisfactory results were obtained (total correct rate 87.30%). In addition, metabolites that most strongly influence this separation were obtained. The results indicated that a metabonomic approach is feasible and efficient and deserves further evaluation as a potential novel strategy for the detection of nasopharyngeal carcinoma.
机译:本文通过气相色谱-质谱法(GC / MS)从102例鼻咽癌(NPC)患者和107例健康成年人获得了代谢指纹。偏最小二乘判别分析(PLS-DA)揭示了一种模式识别,可将患者与对照区分开,其敏感性为89.72%(96/107),特异性为85.29%(87/102)。此外,进行了双盲实验,获得了满意的结果(总正确率为87.30%)。另外,获得了最强烈影响该分离的代谢物。结果表明,一种代谢组学方法是可行和有效的,值得作为检测鼻咽癌的潜在新策略进行进一步评估。

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