Research On Blood From Colorectal Cancer And Gastric Cancer Patients Based On Surface-enhanced Raman Spectroscopy

Surface-enhanced Raman Scattering technique is widely employed in the field of biomedicine, due to it’s high sensitivity, strong specificity and good stability. In this study, we applied the SERS technique for detection of serum and serum RNA obtained from colorectal cancer and gastric cancer patients. The main research contents as follows:1. We explored the feasibility of discriminating the colorectal cancer patients (n=133) and from healthy controls (n=90) by blood serum based on surface-enhanced Raman spectroscopy (SERS). Silver nanoparticles as the SERS-active substrate were presented to effectively enhance the Raman signals. Principal component analysis (PCA) combined with linear discriminate analysis (LDA) was introduced to differentiate colorectal cancer from normal and achieved sensitivity of97.7%and specificity of97.8%.2. SERS technique was applied to analyze the serum obtained from gastric cancer patients (n=136) and healthy volunteers (n=90). Using PCA-LDA multivariate analysis, we were able to differentiate gastric cancer from normal with sensitivity of93.4%and specificity of86.7%. To improve the diagnostic accuracy, we employed the partial least squares (PLS) analysis for differentiating the SERS spectra of gastric cancer from normal. The prediction accuracy is up to100%. The results demonstrated a great potential of using SERS combined with PLS for non-invasive detection and screening of gastric cancer.3. We used MgSO4-aggregated silver nanoparticles as the SERS-active substrate for detection of serum RNA from colorectal cancer patients. PCA-LDA multivariate analysis of the SERS spectra obtained from colorectal cancer (n=55) can be differentiated from normal (n=45) with good sensitivity of89.1%and specificity of95.6%.4. A novel three-dimensional Ag nanofilm formed by dry MgSO4-aggregated silver nanoparticles as the SERS-active substrate was presented to effectively enhance the serum RNA samples:one group from gastric cancer patients (n=31) and the other group from healthy volunteers (n=34). PCA-LDA analysis generated features can differentiate the gastric cancer from normal with sensitivity of100%and specificity of94.1%.