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Surface-enhanced Raman spectroscopy of blood serum based on gold nanoparticles for the diagnosis of the oral squamous cell carcinoma

机译:基于金纳米颗粒的血清表面增强拉曼光谱在口腔鳞状细胞癌诊断中的应用

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BackgroundOral squamous cell carcinoma (OSCC) is becoming more common across the globe. The prognosis of OSCC is largely dependent on the early detection. But the routine oral cavity examination may delay the diagnosis because the early oral malignant lesions may be clinically indistinguishable from benign or inflammatory diseases. In this study, the new diagnostic method is developed by using the surface enhanced Raman spectroscopy (SERS) to detect the serum samples from the cancer patients. MethodThe blood serum samples were collected from the OSCC patients, MEC patients and the volunteers without OSCC or MEC. Gold nanoparticles(NPs) were then mixed in the serum samples to obtain the high quality SERS spectra. There were totally 135 spectra of OSCC, 90 spectra of mucoepidermoid carcinoma (MEC) and 145 spectra of normal control group, which were captured by SERS successfully. Compared with the normal control group, the Raman spectral differences exhibited in the spectra of OSCC and MEC groups, which were assigned to the nucleic acids, proteins and lipids. Based on these spectral differences and features, the algorithms of principal component analysis(PCA) and linear discriminant analysis (LDA) were employed to analyze and classify the Raman spectra of different groups. ResultsCompared with the normal groups, the major increased peaks in the OSCC and MEC groups were assigned to the molecular structures of the nucleic acids and proteins. And these different major peaks between the OSCC and MEC groups were assigned to the special molecular structures of the carotenoids and lipids. The PCA-LDA results demonstrated that OSCC could be discriminated successfully from the normal control groups with a sensitivity of 80.7% and a specificity of 84.1%. The process of the cross validation proved the results analyzed by PCA-LDA were reliable. ConclusionThe gold NPs were appropriate substances to capture the high-quality SERS spectra of the OSCC, MEC and normal serum samples. The results of this study confirm that SERS combined PCA-LDA had a giant capability to detect and diagnosis OSCC through the serum sample successfully.
机译:背景技术口腔鳞状细胞癌(OSCC)在全球范围内越来越普遍。 OSCC的预后很大程度上取决于早期发现。但是常规的口腔检查可能会延迟诊断,因为早期的口腔恶性病变在临床上可能与良性或炎性疾病没有区别。在这项研究中,通过使用表面增强拉曼光谱(SERS)来检测癌症患者的血清样品,开发了新的诊断方法。方法从OSCC患者,MEC患者和无OSCC或MEC的志愿者中收集血清样本。然后将金纳米颗粒(NPs)与血清样品混合以获得高质量的SERS光谱。 SERS成功地捕获了OSCC的135个光谱,粘液表皮样癌(MEC)的90个光谱和正常对照组的145个光谱。与正常对照组相比,在OSCC和MEC组的光谱中表现出拉曼光谱差异,它们分别属于核酸,蛋白质和脂质。基于这些光谱差异和特征,采用主成分分析(PCA)和线性判别分析(LDA)算法对不同组的拉曼光谱进行分析和分类。结果与正常组相比,OSCC和MEC组的主要增加峰被分配给核酸和蛋白质的分子结构。 OSCC和MEC组之间的这些不同的主峰被分配给类胡萝卜素和脂质的特殊分子结构。 PCA-LDA结果表明,可以将OSCC与正常对照组成功地区分开,灵敏度为80.7%,特异性为84.1%。交叉验证的过程证明了PCA-LDA分析的结果是可靠的。结论金纳米颗粒是捕获OSCC,MEC和正常血清样品的高质量SERS光谱的合适物质。这项研究的结果证实,结合了PCA-LDA的SERS具有成功检测和诊断血清样品中OSCC的强大能力。

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