Application Of Surface-enhanced Raman Spectroscopy In The Diagnosis Of Liver And Lung Tumors

Surface enhanced Raman scattering?SERS?is an analytical method with the advantages of high specificity,high detection sensitivity,rapid detection and trace analysis.At the same time,the method also has fingerprint recognition characteristics,and can provide abundant information of molecular vibration.Gold,silver,copper and other precious metals have superior physical and chemical properties,and can generate localized surface plasmon resonance?also known as"hot spots"?on the surface of rough nano-metal structure,so as to achieve single-molecule level detection.Due to its high detection sensitivity,SERS has broad application prospects in tumor analysis.Silver nanoparticles?Ag-NPs?have good physical or chemical properties and favorable biocompatibility,and have been widely used in SERS research of tumors.This paper will study the application of SERS technology in liver cancer and lung cancer.The main research work is as follows:?1?Traditional detection methods can be used to make early diagnosis for the liver cancer patients,but these methods cannot to expound the tissue carcinogenesis at the molecular level.With SERS,the normal?n=46?and cancerous?n=56?liver tissue slices from 56 patients were analyzed in the fingerprint region(500-1800 cm^-1).The relative intensities of the characteristic vibration peaks at 838,1448,and 1585 cm^-1 are significantly changed in the cancerous tissues.In the preliminary analysis,there are differences in the content of specific biomolecules?such as DNA and glycogen?of cancerous tissues and normal ones.Principal component analysis?PCA?and linear discriminate analysis?LDA?were combined to classify cancerous and normal liver tissue slices.The receiver operating characteristic?ROC?curve can give the sensitivity and specificity of the classification method,and their values were 100%and 100%,respectively.This study demonstrates that the fingerprint SERS of tissue slices have great potential in the clinical detection of liver cancer.?2?Although Raman spectroscopy can diagnose lung cancer through tissue slices,its weak cross sections are problematic.In this study,Ag-NPs were added to the surface of lung tissue slices to enhance the Raman scattering signals of biomolecules.The electromagnetic field distribution of Ag-NPs prepared was simulated using the COMSOL software.SERS obtained from the slices reflected the difference in biochemical molecules between normal?n=23?and cancerous?n=23?lung tissues.PCA-LDA was utilized to classify lung cancer and healthy lung tissues.The ROC curve gave the sensitivity?95.7%?and specificity?95.7%?of the PCA-LDA method.This study sheds new light on the general applicability of SERS analysis of tissue slices in clinical trials.?3?SERS has a broad application prospect in the field of tumor detection owing to its ultrahigh detective sensitivity.However,SERS analysis of serum remain a challenge in terms of repeatability and stability due to the maldistribution of the Ag-NPs-serum.With the aim to make up for this shortcoming,we report a new method for obtaining stable serum Raman signals utilizing the ordered arrays of pyramidal silicon?PSi?and Ag-NPs.We prove the practicability of this method by detecting the samples of serum from 50 lung cancer patients and 50 normal healthy people.PCA of the serum SERS spectra shows that the spectral data of the two sample groups can form obvious and completely separated clusters.The ROC curve provides the sensitivity?100%?and specificity?90%?from the PCA-LDA method.This research indicates that a stable and label-free analysis technique of serum SERS based on Ag-NPs/PSi and PCA-LDA is promising for noninvasive lung cancer diagnoses.