Detection of liver cancer and prostate cancer by serum surface- enhanced Raman spectroscopy

In recent years, cancer has become a common health problem faced by all mankind. Liver cancer and prostate cancer are the most common malignant tumors in the world. Early diagnosis is of great significance for the effective treatment of cancer patients and prolonging their life. Therefore, there is an urgent need to develop a powerful method to detect multiple types of cancer. In this work, we developed a surface enhanced Raman spectroscopy combined with principal component analysis (PCA) and linear discriminant analysis (LDA) multivariate statistical method to detect and screen patients with prostate cancer and liver cancer. In order to further verify the validity of PCA-LDA, the receiver operating characteristic(ROC)curve is used to evaluate the effectiveness of the algorithm. The comparison of the average spectra showed that there was a significant difference between the serum samples of patients with liver cancer and patients with prostate cancer. This may be related to the changes of molecular structure and composition of human serum caused by diseases. PCA-LDA algorithm was used to classify SERS in serum of patients with liver cancer and serum of patients with prostate cancer. The sensitivity and specificity were 100% and 90%, respectively. the receiver operating characteristic(ROC)curve shows that the area under the curve is 1. The results show that the combination of SERS and PCA-LDA algorithm has high accuracy in the discrimination and classification of liver cancer and prostate cancer, and the detection is fast and sensitive, which is a potential detection and screening method.