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基于金纳米颗粒的血清表面增强拉曼光谱法检测结直肠癌及统计分析

Colorectal cancer detection by gold nanoparticle based surface-enhanced Raman spectroscopy of blood serum and statistical analysis.

作者信息

Lin Duo, Feng Shangyuan, Pan Jianji, Chen Yanping, Lin Juqiang, Chen Guannan, Xie Shusen, Zeng Haishan, Chen Rong

机构信息

Key Laboratory of OptoElectronic Science and Technology for Medicine, Ministry of Education, Fujian Normal University, Fuzhou, China.

出版信息

Opt Express. 2011 Jul 4;19(14):13565-77. doi: 10.1364/OE.19.013565.

Abstract

The capabilities of using gold nanoparticle based surface-enhanced Raman spectroscopy (SERS) to obtain blood serum biochemical information for non-invasive colorectal cancer detection were presented in this paper. SERS measurements were performed on two groups of blood serum samples: one group from patients (n = 38) with pathologically confirmed colorectal cancer and the other group from healthy volunteers (control subjects, n = 45). Tentative assignments of the Raman bands in the measured SERS spectra suggested interesting cancer specific biomolecular changes, including an increase in the relative amounts of nucleic acid, a decrease in the percentage of saccharide and proteins contents in the blood serum of colorectal cancer patients as compared to that of healthy subjects. Both empirical approach and multivariate statistical techniques, including principal components analysis (PCA) and linear discriminant analysis (LDA) were employed to develop effective diagnostic algorithms for classification of SERS spectra between normal and colorectal cancer serum. The empirical diagnostic algorithm based on the ratio of the SERS peak intensity at 725 cm(-1) for adenine to the peak intensity at 638 cm(-1) for tyrosine achieved a diagnostic sensitivity of 68.4% and specificity of 95.6%, whereas the diagnostic algorithms based on PCA-LDA yielded a diagnostic sensitivity of 97.4% and specificity of 100% for separating cancerous samples from normal samples. Receiver operating characteristic (ROC) curves further confirmed the effectiveness of the diagnostic algorithm based on PCA-LDA technique. The results from this exploratory study demonstrated that gold nanoparticle based SERS serum analysis combined with PCA-LDA has tremendous potential for the non-invasive detection of colorectal cancers.

摘要

本文介绍了利用基于金纳米颗粒的表面增强拉曼光谱(SERS)获取血清生化信息以用于非侵入性结直肠癌检测的能力。对两组血清样本进行了SERS测量:一组来自经病理确诊的结直肠癌患者(n = 38),另一组来自健康志愿者(对照受试者,n = 45)。对测得的SERS光谱中拉曼谱带的初步归属表明存在有趣的癌症特异性生物分子变化,包括与健康受试者相比,结直肠癌患者血清中核酸相对含量增加,糖类和蛋白质含量百分比降低。采用经验方法和多元统计技术,包括主成分分析(PCA)和线性判别分析(LDA),来开发有效的诊断算法,用于对正常和结直肠癌血清的SERS光谱进行分类。基于腺嘌呤在725 cm(-1)处的SERS峰强度与酪氨酸在638 cm(-1)处的峰强度之比的经验诊断算法,诊断灵敏度为68.4%,特异性为95.6%,而基于PCA-LDA的诊断算法在区分癌性样本和正常样本时,诊断灵敏度为97.4%,特异性为100%。受试者工作特征(ROC)曲线进一步证实了基于PCA-LDA技术的诊断算法的有效性。这项探索性研究的结果表明,基于金纳米颗粒的SERS血清分析结合PCA-LDA在结直肠癌的非侵入性检测方面具有巨大潜力。

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