Application Of Surface Enhanced Raman Spectroscopy In Rapid Screening Of Lung Adenocarcinoma

Due to air pollution,occupational exposure,smoking and many other reasons,lung cancer has become one of the most malignant tumors with the fastest growth in morbidity and mortality and the greatest threat to human health and life.At present,the screening methods for lung cancer in the clinic are not only expensive,but also harmful to the human body.It urgently requires a simple and non-invasive method for early diagnosis of lung cancer to improve the survival rate of patients.Raman spectroscopy is a detection technique based on samples'inelastic scattered light,which has the advantages of fast,simple,non-invasive and high sensitivity.Since the invention of the laser in the 1960s,Raman spectroscopy has developed rapidly and has been widely used in biomedicine,food safety,environmental testing,materials research,archaeological relics,gem identification,and forensic science in recent years.In this paper,surface-enhanced Raman spectroscopy?SERS?technology was used to detect both human serum and pleural effusion,and it was used for classification and staging of lung adenocarcinoma?LAC?.This topic mainly carries out the following three aspects of research work:?1?Three nano-silver substrates were prepared,including titanium dioxide-silver nanoparticles prepared by chemical methods,and two silver nanorods prepared by physical methods?naked silver nanorods and nanorods coated with a dense alumina film?.The performances of these three Raman-active substrates were compared.The silver nanorod coated with alumina film was chosen for subsequent detection of human body fluid samples,with 28.5 nm surface root mean square roughness,8.40%surface morphology,good signal reproducibility and stability,and 10^-8 M detection sensitivity to p-mercaptobenzoic acid.?2?In order to eliminate the interference and redundant information in the collected Raman spectra of the body fluid samples,some spectral preprocessing methods were used,such as de-"ghost line",smoothing,de-baseline correction,and average spectral correction,in order to improve the signal-to-noise ratio of the spectra.Principal component analysis?PCA?,orthogonal partial least squares?OPLS?and linear discriminant analysis?LDA?were combined to establish PCA-LDA and OPLS-LDA identification models.On this basis,the original spectra,the first derivative spectra and the second derivative spectra were taken as the input of the analysis model respectively,and the identification results were compared to determine the optimal input spectra type and analysis model.?3?The 108 serum from patients with LAC,82 serum from healthy people,51malignant pleural effusions and 32 benign pleural effusions were experimental subjects.The Raman spectra of serum and pleural effusion were analyzed and classified based on the established screening model.The results showed that in the screening problem of LAC serum and healthy human serum,the combination of 2ⁿdd derivative spectra and OPLS-LDA model can achieve the best results,with overall accuracy of 99.5%;in the staging problem of LAC serum,the combination of 1^stt derivative spectra and OPLS-LDA model can achieve the best results,with overall accuracy of 84.3%,93.3%and 86.5%,respectively;in the classification problem of benign/malignant pleural effusion,the combination of 2^nd derivative spectra and OPLS-LDA model can achieve the best results,with overall accuracy of 92.8%.These results demonstrated the feasibility of the classification of Raman spectra of human body fluids based on OPLS-LDA model.Based on the above researches,this paper not only realized the SERS detection of human serum and pleural effusion,but also staged the serum of patients with LAC,and classified the serum of LAC patients and healthy people,and benign and malignant pleural effusions.These results have made it possible to achieve non-invasive,high accuracy and early screening for lung cancer.