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Study on gastric cancer blood plasma based on surface-enhanced Raman spectroscopy combined with multivariate analysis

机译:基于表面增强拉曼光谱结合多元分析的胃癌血浆研究

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A surface-enhanced Raman spectroscopy ( SERS ) method combined with multivariate analysis was developed for non-invasive gastric cancer detection. SERS measurements were performed on two groups of blood plasma samples: one group from 32 gastric patients and the other group from 33 healthy volunteers. Tentative assignments of the Raman bands in the measured SERS spectra suggest interesting cancer-specific biomolecular changes, including an increase in the relative amounts of nucleic acid, collagen, phospholipids and phenylalanine and a decrease in the percentage of amino acids and saccharide in the blood plasma of gastric cancer patients as compared with those of healthy subjects. Principal components analysis (PCA) and linear discriminant analysis (LDA) were employed to develop effective diagnostic algorithms for classification of SERS spectra between normal and cancer plasma with high sensitivity (79.5%) and specificity (91%). A receiver operating characteristic (ROC) curve was employed to assess the accuracy of diagnostic algorithms based on PCA-LDA. The results from this exploratory study demonstrate that SERS plasma analysis combined with PCA-LDA has tremendous potential for the non-invasive detection of gastric cancers.
机译:开发了一种表面增强拉曼光谱(SERS)方法和多变量分析相结合的方法,用于无创胃癌的检测。对两组血浆样品进行SERS测量:一组来自32位胃病患者,另一组来自33位健康志愿者。暂时在测量的SERS光谱中分配拉曼谱带表明有趣的癌症特异性生物分子变化,包括核酸,胶原蛋白,磷脂和苯丙氨酸的相对量增加以及血浆中氨基酸和糖类百分比的减少与健康受试者的胃癌患者相比。采用主成分分析(PCA)和线性判别分析(LDA)来开发有效的诊断算法,以高灵敏度(79.5%)和特异性(91%)对正常和癌症血浆之间的SERS光谱进行分类。接收器工作特性(ROC)曲线用于评估基于PCA-LDA的诊断算法的准确性。这项探索性研究的结果表明,SERS血浆分析结合PCA-LDA具有巨大的潜力,可以无创地检测胃癌。

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