SERS光谱技术在结直肠癌诊断中的应用效果

Application Effect of Surface-Enhanced Raman Scattering Spectrum Technology in Diagnosis of Colorectal Cancer

选取扬州大学附属江都人民医院收集的50例结直肠癌组血清和50例健康组血清。以金纳米星(AuNS)为基底,利用Renishaw inVia Reflex激光共焦Raman光谱仪,对血清样本的表面增强Raman散射(SERS)光谱进行测定。借助Origin 2021对Min-Max归一化后平均光谱的特征峰分析,并用主成分分析(PCA)-K最邻近(KNN)模型对关键特征提取、分类。结果表明AuNS基底具有良好的均匀性、灵敏度和洁净性。结直肠癌患者在572、633、873、1065、1314、1417和1655 cm^(-1)特征峰处强度明显高于健康组,在1000和1536 cm^(-1)特征峰处强度低于健康组。PCA-KNN模型的准确率达到95%,灵敏度、特异性和曲线下的面积(AUC)分别达到90.0%、96.7%和0.933。结合PCA-KNN模型和SERS光谱技术可实现对结直肠癌快速、准确的识别,为诊断结肠癌提供了一种探索性的新方法。

The 50 serum samples of colorectal cancer group and 50 serum samples of healthy group collected from Jiangdu People's Hospital Affiliated to Yangzhou University were selected.With Au nanostars(AuNSs)as the substrate,the surface-enhanced Raman scattering(SERS)spectra of serum samples were measured by the Renishaw inVia Reflex laser confocal Raman spectrometer.Origin 2021 was used to analyze the characteristic peaks of the Min-Max normalized average spectrum,and principal components analysis(PCA)-K-nearest neighbor(KNN)model was used to extract and classify the key features.The results show that AuNSs substrate has good uniformity,sensitivity and cleanliness.The characteristic peak intensities of colorectal cancer patients at 572,633,873,1065,1314,1417 and 1655 cm^(-1)are significantly higher than those of healthy group,and the characteristic peak intensities at 1000 and 1536 cm^(-1)are lower than those of healthy group.The accuracy of PCA-KNN model reaches 95%,and the sensitivity,specificity and area under curve(AUC)reach 90.0%,96.7%and 0.933,respectively.The combination of PCA-KNN model and SERS spectrum technology can realize the rapid and accurate identification of colorectal cancer,which provides an exploratory new method for the diagnosis of colorectal cancer.