Early discrimination of nasopharyngeal carcinoma based on tissue deoxyribose nucleic acid surface-enhanced Raman spectroscopy analysis

A New Detection Method of Oral and Oropharyngeal Squamous Cell Carcinoma Based on Multivariate Analysis of Surface Enhanced Raman Spectra of Salivary Exosomes

Raman spectroscopy recently proved a tremendous capacity to identify disease-specific markers in various (bio)samples being a non-invasive, rapid, and reliable method for cancer detection. In this study, we first aimed to record vibrational spectra of salivary exosomes isolated from oral and oropharyngeal squamous cell carcinoma patients and healthy controls using surface enhancement Raman spectroscopy (SERS). Then, we assessed this method's capacity to discriminate between malignant and non-malignant samples by means of principal component-linear discriminant analysis (PC-LDA) and we used area under the receiver operating characteristics with illustration as the area under the curve to measure the power of salivary exosomes SERS spectra analysis to identify cancer presence. The vibrational spectra were collected on a solid plasmonic substrate developed in our group, synthesized using tangential flow filtered and concentrated silver nanoparticles, capable of generating very reproducible spectra for a whole range of bioanalytes. SERS examination identified interesting variations in the vibrational bands assigned to thiocyanate, proteins, and nucleic acids between the saliva of cancer and control groups. Chemometric analysis indicated discrimination sensitivity between the two groups up to 79.3%. The sensitivity is influenced by the spectral interval used for the multivariate analysis, being lower (75.9%) when the full-range spectra were used.

High-Precision Detection of Cellular Drug Response Based on SERS Spectrum and Multivariate Statistical Analysis

The rapid development of personalized medicine places high demands on the control of drug dose and cellular drug response to provide patients with better curative effects and low side effects. To solve the problem of low detection accuracies of the cell-counting kit-8 (CCK8) method, a detection method based on surface-enhanced Raman spectroscopy (SERS) of cell-secreted proteins was adopted to evaluate the concentration of the anticancer drug cisplatin and the cellular drug response of nasopharyngeal carcinoma. CNE1 and NP69 cell lines were used to evaluate cisplatin response. The results showed that the combination of the SERS spectrum with principal component analysis-linear discriminant analysis could detect the difference in the response of cisplatin with a concentration difference of 1 μg/mL, which considerably exceeded that of CCK8. In addition, the SERS spectral peak intensity of the cell-secreted proteins strongly correlated with the cisplatin concentration. Furthermore, the mass spectrum of the secreted proteins of the nasopharyngeal carcinoma cells was analyzed to verify the results obtained using the SERS spectrum. The results demonstrated that SERS of secreted proteins has great potential for high-precision detection of chemotherapeutic drug response.

Surface-enhanced Raman spectroscopy for studying the interaction of N-propyl substituted imidazole compound with salmon sperm DNA

BACKGROUND

Surface Enhanced Raman Spectroscopy (SERS) is a very promising and fast technique for studying drugs and for detecting chemical nature of a molecule and DNA interaction. In the current study, SERS is employed to check the interaction of different concentrations of n-propyl imidazole derivative ligand with salmon sperm DNA using silver nanoparticles as SERS substrates.

OBJECTIVES

Multivariate data analysis technique like principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) are employed for the detailed analysis of the SERS spectral features associated with the mode of action of the imidazole derivative ligand with DNA.

METHODOLOGY

Silver nanoparticles were used as a SERS substrate in DNA-drug interaction. Five different concentrations of ligands were interacted with DNA and mix with Ag-NPs as substrate. The SERS spectra of were acquired for all seven samples and processed using MATLAB. Additionally, PCA and PLS-DA were used to assessed the ability SERS to differentiate interaction of DNA-drug.

RESULTS

Differentiating SERS features having changes in their peak position and intensities are observed including 629, 655, 791, 807, 859, 1337, 1377 and 1456 cm^-1. These SERS features reveal that binding of ligand with DNA is electrostatic in nature, and have specificity to major groove where it forms GC-CG interstrand cross-linking with the DNA double helix.

CONCLUSIONS

SERS give significant information regarding to Drug-DNA interaction mechanism, SERS spectra inferred the mode of action of anticancer compound that are imidazole in nature.

Diagnosis of nasopharyngeal carcinoma from serum samples using hyperspectral imaging combined with a chemometric method

Diagnosing nasopharyngeal carcinoma (NPC) is a significant challenge because of the highly complex process. We proposed an approach to diagnose NPC serum using a combination of hyperspectral imaging and weight-based principal component analysis. Samples were prepared by pressing boric acid into pellets for use as the sera substrate. The sera, collected from 100 healthy volunteers and 60 NPC patients, was dripped onto the surface of the substrate for hyperspectral imaging. The characteristic spectral bands were selected based on the variable weight obtained from a support vector machine (SVM) model, using principal component analysis (PCA) to reduce the dimension in the extracted bands. Obtained results show that the accuracy rate, sensitivity, and specificity between the NPC sera and the sera of the healthy controls reached extremely high levels of 99.15%, 98.79%, and 99.36%, respectively. For the model's consistency evaluation, we found that the Kappa and area under the curve (AUC) of the receiver operating characteristic (ROC) curve were 0.99 and 0.98, respectively. These results suggest that the developed approach could serve as a noninvasive diagnostic and screening tool for highly accurate and consistent detection of NPC. Hence, a combination of hyperspectral imaging (HSI) and a weighted principal component analysis (WPCA)-SVM model represents a powerful and promising tool for NPC diagnosis.