Metabolic characteristics revealing cell differentiation of nasopharyngeal carcinoma by combining NMR spectroscopy with Raman spectroscopy

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.

Differentiation and prognostic stratification of acute myeloid leukemia by serum-based spectroscopy coupling with metabolic fingerprints

Acute myeloid leukemia (AML) is a heterogeneous disease characterized by complex molecular and cytogenetic abnormalities. New approaches to predict the prognosis of AML have increasingly attracted attention. There were 98 non-M3 AML cases and 48 healthy controls were enrolled in the current work. Clinically routine assays for cytogenetic and molecular genetic analyses were performed on the bone marrow samples of patients with AML. Meanwhile, metabolic profiling of these AML subjects was also performed on the serum samples by combining Ag nanoparticle-based surface-enhanced Raman spectroscopy (SERS) with proton nuclear magnetic resonance (NMR) spectroscopy. Although most of the routine biochemical test showed no significant differences between the M0-M2 and M5 groups, the metabolic profiles were significantly different either between AML subtypes or between prognostic risk subgroups. Specific SERS bands were screened to serve as potential markers for AML subtypes. The results demonstrated that the classification models for M0-M2 and M5 shared two bands (i.e., 1328 and 741 cm^-1 ), all came from nucleic acid signals. Furthermore, Metabolic profiles provided various differential metabolites responsible for different AML subtypes, and we found altered pathways mainly included energy metabolism like glycolysis, pyruvate metabolism, and metabolisms of nucleic acid bases as well as specific amino acid metabolisms. It is concluded that integration of SERS and NMR provides the rational and could be reliable to reveal AML differentiation, and meanwhile lay the basis for experimental and clinical practice to monitor disease progression and prognostic evaluation.

Raman profile alterations of irradiated human nasopharyngeal cancer cells detected with laser tweezer Raman spectroscopy

Radiotherapy has been widely used for nasopharyngeal carcinoma (NPC) treatment, which causes DNA damage and alterations of macromolecules of cancer cells. However, the Raman profile alterations of irradiated NPC cells remain unclear. In the present study, we used laser tweezers Raman spectroscopy (LTRS) to monitor internal structural changes and chemical modifications in NPC cells after exposure at a clinical dose (2.3 Gy) to X-ray irradiation (IR) at a single-cell level. Two types of NPC cell lines, CNE2 (EBV-negative cell line) and C666-1 (EBV-positive cell line), were used. The Raman spectra of cells before and after radiation treatment were recorded by LTRS. The analysis of spectral differences indicated that the IR caused Raman profile alterations of intracellular proteins, DNA base and lipids. Moreover, by using the multivariate statistical analysis including principal component analysis (PCA) and linear discriminant analysis (LDA) algorithm, an accuracy of 90.0% for classification between CNE2 cells before and after IR could be achieved, which was 10% better than that of C666-1 cells. The results demonstrated that CNE2 cells were more sensitive to IR in comparison to C666-1 cells, providing useful information for creating a treatment strategy in clinical practice. This exploratory study suggested that LTRS combined with multivariate statistical analysis would be a novel and effective tool for evaluating the radiotherapeutic effect on tumor cells, and for detection of the corresponding alterations at the molecular level.

Laser tweezer Raman spectroscopy combined with multivariate statistical analysis was used for evaluating the radiotherapeutic effect on a single tumor cell.