J Biomed Nanotechnol. 2014 Mar;10(3):478-84. doi: 10.1166/jbn.2014.1750.
A surface-enhanced Raman spectroscopy (SERS) based on silver nanoparticle technology was applied to analyze and classify human blood plasma with the aim to develop a simple and label-free blood test for esophageal cancer detection. High quality SERS spectra in the range of 400-1800 cm(-1) can be acquired from 36 esophageal cancer patients and 50 healthy volunteers' blood plasma samples. Tentative assignments of the SERS bands indicated specific biomolecular changes associated with cancer transformation, including an increase in the relative amounts of nucleic acid and phenylalanine, a decrease in the percentage of saccharide and proteins contents in the cancer blood plasma compared to that of healthy subjects. Furthermore, both SVM and PCA-LDA diagnostic algorithm were employed to analyze and classify the obtained blood plasma SERS spectra between normal and cancer plasma with a high diagnostic accuracy (around 90%). This exploratory work demonstrates that the label-free plasma SERS analysis technique in conjunction with SVM and PCA-LDA diagnostic algorithms has great potential for improving esophageal cancer detection and screening.
基于银纳米粒子技术的表面增强拉曼光谱(SERS)被应用于分析和分类人血浆,旨在开发一种简单且无需标记的血液检测方法用于食管癌检测。从 36 名食管癌患者和 50 名健康志愿者的血浆样本中可以获得范围在 400-1800 cm(-1)的高质量 SERS 光谱。SERS 带的初步归属表明与癌症转化相关的特定生物分子变化,包括与健康受试者相比,癌症血浆中核酸和苯丙氨酸的相对含量增加,而糖和蛋白质的含量百分比降低。此外,还采用 SVM 和 PCA-LDA 诊断算法对正常和癌症血浆的获得的血浆 SERS 光谱进行分析和分类,具有很高的诊断准确性(约 90%)。这项探索性工作表明,无需标记的血浆 SERS 分析技术与 SVM 和 PCA-LDA 诊断算法相结合,具有提高食管癌检测和筛查的巨大潜力。