Guannan Chen

Nasopharyngeal cancer detection based on blood plasma surface-enhanced Raman spectroscopy and multivariate analysis

A surface-enhanced Raman spectroscopy (SERS) method was developed for blood plasma biochemical analysis for the first time with the aim to develop a simple blood test for non-invasive nasopharyngeal cancer detection. Silver nanoparticles (Ag NP) as the SERS-active nanostructures were directly mixed with blood plasma to enhance the Raman scattering signals of various biomolecular constituents such as proteins, lipids, and nucleic acids. High quality SERS spectrum from blood plasma-Ag NP mixture can be obtained within 10s using a Renishaw micro-Raman system. SERS measurements were performed on two groups of blood plasma samples: one group from patients (n=43) with pathologically confirmed nasopharyngeal carcinomas (WHO type I, II, and III) and the other group from healthy volunteers (control subjects, n=33). Tentative assignments of the Raman bands in the measured SERS spectra suggest interesting cancer specific biomolecular differences, including an increase in the relative amounts of nucleic acid, collagen, phospholipids and phenylalanine and a decrease in the percentage of amino acids and saccharide contents in the blood plasma of nasopharyngeal cancer patients as compared to that of healthy subjects. Principal component analysis (PCA) of the measured SERS spectra separated the spectral features of the two groups into two distinct clusters with little overlaps. Linear discriminate analysis (LDA) based on the PCA generated features differentiated the nasopharyngeal cancer SERS spectra from normal SERS spectra with high sensitivity (90.7%) and specificity (100%). The results from this exploratory study demonstrated great potentials for developing SERS blood plasma analysis into a novel clinical tool for non-invasive detection of nasopharyngeal cancers.

Colorectal cancer detection by gold nanoparticle based surface-enhanced Raman spectroscopy of blood serum and statistical analysis

The capabilities of using gold nanoparticle based surface-enhanced Raman spectroscopy (SERS) to obtain blood serum biochemical information for non-invasive colorectal cancer detection were presented in this paper. SERS measurements were performed on two groups of blood serum samples: one group from patients (n = 38) with pathologically confirmed colorectal cancer and the other group from healthy volunteers (control subjects, n = 45). Tentative assignments of the Raman bands in the measured SERS spectra suggested interesting cancer specific biomolecular changes, including an increase in the relative amounts of nucleic acid, a decrease in the percentage of saccharide and proteins contents in the blood serum of colorectal cancer patients as compared to that of healthy subjects. Both empirical approach and multivariate statistical techniques, including principal components analysis (PCA) and linear discriminant analysis (LDA) were employed to develop effective diagnostic algorithms for classification of SERS spectra between normal and colorectal cancer serum. The empirical diagnostic algorithm based on the ratio of the SERS peak intensity at 725 cm(-1) for adenine to the peak intensity at 638 cm(-1) for tyrosine achieved a diagnostic sensitivity of 68.4% and specificity of 95.6%, whereas the diagnostic algorithms based on PCA-LDA yielded a diagnostic sensitivity of 97.4% and specificity of 100% for separating cancerous samples from normal samples. Receiver operating characteristic (ROC) curves further confirmed the effectiveness of the diagnostic algorithm based on PCA-LDA technique. The results from this exploratory study demonstrated that gold nanoparticle based SERS serum analysis combined with PCA-LDA has tremendous potential for the non-invasive detection of colorectal cancers.

A novel blood plasma analysis technique combining membrane electrophoresis with silver nanoparticle-based SERS spectroscopy for potential applications in noninvasive cancer detection

Combining membrane electrophoresis with silver nanoparticle-based surface-enhanced Raman spectroscopy (SERS), we have developed a novel method for blood plasma analysis for cancer detection applications. In this method, total serum proteins are isolated from blood plasma by membrane electrophoresis and mixed with silver nanoparticles to perform SERS spectral analysis. The obtained SERS spectra present information-rich, fingerprint-type signatures of the biochemical constituents of whole proteins. We evaluated the utility of this method by analyzing blood plasma samples from patients with gastric cancer (n=31) and healthy volunteers (n=33). Principal components analysis of the spectra revealed that the data points for the two groups form distinct, completely separated clusters with no overlap. The gastric cancer group can be unambiguously distinguished from the normal group in this initial test-that is, with both diagnostic sensitivity and specificity of 100%. These results are very promising for developing a label-free, noninvasive clinical tool for cancer detection and screening.

Gold nanoparticle based surface-enhanced Raman scattering spectroscopy of cancerous and normal nasopharyngeal tissues under near-infrared laser excitation.

The capabilities of using gold nanoparticle based near-infrared surface-enhanced Raman scattering (SERS) to obtain biochemical information with high spatial resolution from human nasopharyngeal tissue were presented in this paper. The gold nanoparticles used have a mean diameter of 43 nm with a standard deviation of 6 nm. The SERS bands of nasopharyngeal tissue were assigned to known molecular vibrations of nucleic acids, amino acids, proteins, and metabolites. We also observed the blinking phenomenon at the tissue level when measuring the nasopharyngeal tissue SERS spectra, most frequently in signal intensity but also occasionally in peak positions. This phenomenon is excitation light intensity dependent. This work demonstrated great potential for using SERS imaging for distinguishing cancerous and normal nasopharyngeal tissues on frozen sections without using any dye labeling or other chemical species as functionalized binding sites.

Label-free blood plasma test based on surface-enhanced Raman scattering for tumor stages detection in nasopharyngeal cancer

This study aims to evaluate the feasibility of a label-free nanobiosensor based on blood plasma surface-enhanced Raman spectroscopy (SERS) method for exploring variability of different tumor (T) stages in nasopharyngeal cancer (NPC). Au nanoparticles as the SERS-active nanostructures were directly mixed with human blood plasma to enhance the Raman scattering signals. High quality SERS spectra can be acquired from blood plasma samples belong to 60 healthy volunteers, 25 NPC patients with T1 stage and 75 NPC patients with T2–T4 stage. A diagnostic accuracy of 83.5% and 93.3%, respectively, can be achieved for classification between early T (T1) stage cancer and normal; and advanced T (T2–T4) stage cancer and normal blood groups. This exploratory study demonstrates that the nanobiosensor based on SERS technique in conjunction with PCA-LDA has great potential as a clinical complement for different T stages detection in nasopharyngeal cancer.

Esophageal cancer detection based on tissue surface-enhanced Raman spectroscopy and multivariate analysis

The capability of using silver nanoparticle based near-infrared surface enhanced Raman scattering (SERS) spectroscopy combined with principal component analysis (PCA) and linear discriminate analysis (LDA) to differentiate esophageal cancer tissue from normal tissue was presented. Significant differences in Raman intensities of prominent SERS bands were observed between normal and cancer tissues. PCA-LDA multivariate analysis of the measured tissue SERS spectra achieved diagnostic sensitivity of 90.9% and specificity of 97.8%. This exploratory study demonstrated great potential for developing label-free tissue SERS analysis into a clinical tool for esophageal cancer detection.

Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors

The capability of saliva protein analysis, based on membrane protein purification and surface-enhanced Raman spectroscopy (SERS), for detecting benign and malignant breast tumors is presented in this paper. A total of 97 SERS spectra from purified saliva proteins were acquired from samples obtained from three groups: 33 healthy subjects; 33 patients with benign breast tumors; and 31 patients with malignant breast tumors. Subtle but discernible changes in the mean SERS spectra of the three groups were observed. Tentative assignments of the saliva protein SERS spectra demonstrated that benign and malignant breast tumors led to several specific biomolecular changes of the saliva proteins. Multiclass partial least squares–discriminant analysis was utilized to analyze and classify the saliva protein SERS spectra from healthy subjects, benign breast tumor patients, and malignant breast tumor patients, yielding diagnostic sensitivities of 75.75%, 72.73%, and 74.19%, as well as specificities of 93.75%, 81.25%, and 86.36%, respectively. The results from this exploratory work demonstrate that saliva protein SERS analysis combined with partial least squares–discriminant analysis diagnostic algorithms has great potential for the noninvasive and label-free detection of breast cancer.

Micro-Raman spectroscopy study of cancerous and normal nasopharyngeal tissues

Abstract. The capabilities of micro-Raman spectroscopy for differentiating normal and malignant nasopharyngeal tissues were evaluated. Raman scattering signals were acquired from 22 normal and 52 malignant nasopharyngeal tissue samples. Distinctive spectral differences in Raman spectra between normal and malignant nasopharyngeal tissues were found, particularly in the spectral ranges of 853, 937, 1094, 1209, 1268, 1290 to 1340, 1579, and 1660  cm−1, which primarily contain signals related to proteins, DNA, and lipids. Compared to normal tissues, the band intensity located at 853, and 937  cm−1 were significantly lower for cancerous tissues (p<0.05), while the band intensity located at 1094, 1209, 1268, and 1579  cm−1 were significantly higher (p<0.05). The band intensity located at 1290 to 1340, and 1660  cm−1 were also higher for cancerous tissues; but the differences were not statistically significant (p>0.05). Principal component analysis (PCA) and linear discriminate analysis (LDA) were employed to generate diagnostic algorithms for classification of Raman spectra of the two nasopharyngeal tissue types. The PCA-LDA algorithms together with leave-one-out, cross-validation technique yielded diagnostic sensitivity of 92% and specificity of 82%. This work demonstrated that the Raman spectroscopy technique associated with PCA-LDA diagnostic algorithms has potential for improving the diagnosis of nasopharyngeal cancers.

Surface-enhanced Raman spectroscopy for differentiation between benign and malignant thyroid tissues

The aim of this study was to evaluate the potential of applying silver nano-particle based surface-enhanced Raman scattering (SERS) to discriminate different types of human thyroid tissues. SERS measurements were performed on three groups of tissue samples including thyroid cancers (n = 32), nodular goiters (n = 20) and normal thyroid tissues (n = 25). Tentative assignments of the measured tissue SERS spectra suggest interesting cancer specific biomolecular differences. The principal component analysis (PCA) and linear discriminate analysis (LDA) together with the leave-one-out, cross-validated technique yielded diagnostic sensitivities of 92%, 75% and 87.5%; and specificities of 82.6%, 89.4% and 84.4%, respectively, for differentiation among normal, nodular and malignant thyroid tissue samples. This work demonstrates that tissue SERS spectroscopy associated with multivariate analysis diagnostic algorithms has great potential for detection of thyroid cancer at the molecular level.

Saliva analysis combining membrane protein purification with surface-enhanced Raman spectroscopy for nasopharyngeal cancer detection

A method for saliva analysis combining membrane protein purification with silver nanoparticle-based surface-enhanced Raman spectroscopy (SERS) for non-invasive nasopharyngeal cancer detection was present in this paper. In this method, cellulose acetate membrane was used to obtain purified whole proteins from human saliva while removing other native saliva constituents and exogenous substances. The purified proteins were mixed with silver nanoparticle for SERS analysis. A diagnostic accuracy of 90.2% can be achieved by principal components analysis combined with linear discriminate analysis, for saliva samples obtained from patients with nasopharyngeal cancer (n = 62) and healthy volunteers (n = 30). This exploratory study demonstrated the potential for developing non-invasive, rapid saliva SERS analysis for nasopharyngeal cancer detection.