Raman spectroscopic analysis of the molecular composition of oral cavity squamous cell carcinoma and healthy tongue tissue

Abstract

A Raman tissue spectrum is a quantitative representation of the overall molecular composition of that tissue. Raman spectra are often used as tissue fingerprints without further interpretation of the specific information that they contain about the tissue's molecular composition. In this study, we analyzed the differences in molecular composition between oral cavity squamous cell carcinoma (OCSCC) and healthy tissue structures in tongue, based on their Raman spectra. A total of 1087 histopathologically annotated spectra (142 OCSCC, 202 surface squamous epithelium, 61 muscle, 65 adipose tissue, 581 connective tissue, 26 gland, and 10 nerve) were obtained from Raman maps of 44 tongue samples from 21 patients. A characteristic, average spectrum of each tissue structure was fitted with a set of 55 pure-compound reference spectra, to define the best library of fit-spectra. Reference spectra represented proteins, lipids, nucleic acids, carbohydrates, amino acids and other miscellaneous molecules. A non-negative least-squares algorithm was used for fitting. Individual spectra per histopathological annotation were then fitted with this selected library in order to determine the molecular composition per tissue structure. The spectral contribution per chemical class was calculated. The results show that all characteristic tissue-type spectra could be fitted with a low residual of <4.82%. The content of carbohydrates, proteins and amino acids was the strongest discriminator between OCSCC and healthy tissue. The combination of carbohydrates, proteins and amino acids was used for a classification model of 'tumor' versus 'healthy tissue'. Validation of this model on an independent dataset showed a specificity of 93% at a sensitivity of 100%.

Biophysical basis of skin cancer margin assessment using Raman spectroscopy

“…Raman spectroscopy is a nondestructive and label-free optical technique, and has demonstrated great clinical merits for tumor margin assessment in numerous types of cancer, including skin [6], brain [7,8], oral cavity [9,10], breast [11,12], and stomach [13]. Those studies either use fiber-optical Raman probe for single point sampling or Raman microscopy (also called Raman microspectroscopy) for optical imaging.…”

Raman Spectroscopy Analysis for Optical Diagnosis of Oral Cancer Detection

“…The accuracy (1-error rate) is the proportion of correct predictions, including correct positive and negative predications based on the selected samples [42]. The low specificity of the tongue indicates miss-classification between healthy tissue sublayers (surface squamous epithelium, muscle, and gland) and the OSCC structure, which has been discussed in an earlier study [43] and the section on validation methods.…”

“…Since the oral tissue is heterogeneous, it comprises of different structures and layers. Cals [43] reported that the sub-layers of a healthy tissue structure (surface squamous epithelium, muscle) have the same protein, lipids, and nucleic acid as OSCC or tumor tissues of the tongue. Therefore, the miss-classification between healthy tissues sublayers (surface squamous epithelium, muscle, and gland) and the OSCC structures was greater than other sub-sites.…”

Confocal Raman microscopy to identify bacteria in oral subgingival biofilm models

“…Previously, CRM has been successful in the spatial resolution of biomedical environments like tissue samples or bacterial cells [14][15][16][17][18]. However, the acquired signals from these biomedical components are highly complex [19][20][21].…”