Raman spectroscopic analysis of normal, abnormal and irradiated oral mucosa: A tissue engineered and ex vivo approach

Head and neck cancer (HNC) is the sixth most common malignancy worldwide. Squamous cell carcinoma (SCC), the primary cause of HNC, evolves from normal epithelium through dysplasia before invading the connective tissue to form a carcinoma. However, less than 18% of dysplastic lesions progress to cancer with diagnosis currently relying on histopathological evaluation, which is invasive and time-consuming. A non-invasive, real-time, point-of-care method could overcome these problems and facilitate regular screening. The aim of this study was to use Raman spectroscopy to identify specific chemical moieties which can be identified to determine cancer progression and thereby investigate its use as a diagnostic tool.
Tissue-engineered models of normal, dysplastic and HNC squamous cell carcinoma (HNSCC) were constructed and their biochemical content determined by interpretation of spectral characteristics. Spectral features of normal models were mainly attributed to lipids, whereas, malignant models were observed to be protein dominant. Visible differences between the spectra of normal, dysplastic and cancerous models, specifically in the bands of amide I and III were observed. Principal component analysis, cluster analysis and linear discriminant analysis (LDA) were successful in identifying subtypes of dysplasia and cancer.
Patient biopsy samples were also analysed using Raman spectroscopy. Spectral data revealed biochemical variations associated with lipids, proteins and nucleic acids. LDA was utilised for tissue classification and achieved 99% specificity to normal and 97% sensitivity to cancer whereas between dysplasia and cancer a sensitivity of 80 and 92% was achieved respectively.
Finally, tissue-engineered models were irradiated and the post-irradiation effects were assessed. Chemometric data analysis revealed that nucleic acids and proteins were mainly targeted whilst increased incubation periods demonstrated cell repair and recovery mechanisms.
In summary, vibrational spectroscopy offers great potential in diagnosing, staging and designing treatments for HNSCC. This study has generated a wealth of spectral data, describing chemical structural changes associated with oral cancer progression and thereby building up a single comprehensive and standardised database for future studies.