Surface-enhanced Raman spectroscopy of blood serum based on gold nanoparticles for the diagnosis of the oral squamous cell carcinoma

Lipids in Health and Disease

Research

Yi Li¹  Xianyang Luo²  Bing Yan²  Lili Xue³  Ping Ji⁴  Yingyun Tan⁴ 

[1] Department of Head and Neck Oncology, the West China Hospital of Stomatology, Sichuan University, 610000, Chengdu, China;Department of Otolarygology Head and Neck Surgery, the First Affiliated Hospital of Xiamen University, 361000, Xiamen, China;Department of Stomatology, the First Affiliated Hospital of Xiamen University, 361000, Xiamen, China;Stomatological Hospital of Chongqing Medical University, 400000, Chongqing, China;Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, 400000, Chongqing, China;Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, 400000, Chongqing, China;

关键词: Oral squamous cell carcinoma (OSCC);    Surface-enhanced Raman spectroscopy (SERS);    Principal component analysis (PCA);    Linear discriminant analysis(LDA);    Diagnosis;   

DOI  :  10.1186/s12944-017-0465-y

 received in 2017-02-14, accepted in 2017-03-30,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundOral squamous cell carcinoma (OSCC) is becoming more common across the globe. The prognosis of OSCC is largely dependent on the early detection. But the routine oral cavity examination may delay the diagnosis because the early oral malignant lesions may be clinically indistinguishable from benign or inflammatory diseases. In this study, the new diagnostic method is developed by using the surface enhanced Raman spectroscopy (SERS) to detect the serum samples from the cancer patients.MethodThe blood serum samples were collected from the OSCC patients, MEC patients and the volunteers without OSCC or MEC. Gold nanoparticles(NPs) were then mixed in the serum samples to obtain the high quality SERS spectra. There were totally 135 spectra of OSCC, 90 spectra of mucoepidermoid carcinoma (MEC) and 145 spectra of normal control group, which were captured by SERS successfully. Compared with the normal control group, the Raman spectral differences exhibited in the spectra of OSCC and MEC groups, which were assigned to the nucleic acids, proteins and lipids. Based on these spectral differences and features, the algorithms of principal component analysis(PCA) and linear discriminant analysis (LDA) were employed to analyze and classify the Raman spectra of different groups.ResultsCompared with the normal groups, the major increased peaks in the OSCC and MEC groups were assigned to the molecular structures of the nucleic acids and proteins. And these different major peaks between the OSCC and MEC groups were assigned to the special molecular structures of the carotenoids and lipids. The PCA-LDA results demonstrated that OSCC could be discriminated successfully from the normal control groups with a sensitivity of 80.7% and a specificity of 84.1%. The process of the cross validation proved the results analyzed by PCA-LDA were reliable.ConclusionThe gold NPs were appropriate substances to capture the high-quality SERS spectra of the OSCC, MEC and normal serum samples. The results of this study confirm that SERS combined PCA-LDA had a giant capability to detect and diagnosis OSCC through the serum sample successfully.

【 授权许可】

CC BY   
© The Author(s). 2017