Spectroscopy & Cancer - Bio-Chemical Detection & Surveillance

Objectives: 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.

Methods: Tissue-engineered models of normal, dysplastic and HNC squamous cell carcinoma (HNSCC) were constructed and their biochemical content determined by interpretation of spectral characteristics. Principal component analysis, cluster analysis and linear discriminant analysis (LDA) were successful in identifying subtypes of dysplasia and cancer. Finally, tissue-engineered models were irradiated and the post-irradiation effects were assessed.
Results: Spectral features of normal models were mainly attributed to lipids, whereas, malignant models were observed to be protein dominant. Principal component analysis, cluster analysis and linear discriminant analysis (LDA) were successful in identifying subtypes of dysplasia and cancer.
Chemometric analysis has helped us understand radiosensitivity of the cells. Cancer cells have shown more heterogeneity after day 4 post radiation whereas peak height analysis of phenylalanine and DNA macromolecules suggest that
normal tissue has recovered better than cancer.


Conclusions: Vibrational spectroscopic techniques may offer non-invasive tissue assessments in clinical settings during radiotherapy procedures to minimise the associated side effects. Moreover they may be very useful in understanding tissue response to radiation on in vitro models which may aid in a better understanding of cancer treatment and eventually improve prognosis.