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Head and neck cancer is the sixth most common malignancy worldwide. Survival rates for patients with this disease have changed little in the past 30 years despite significant medical and surgical advances.

Non-invasive Raman spectroscopy can detect cancer at early stages leading to an improved prognosis. Raman spectroscopy is a powerful analytical tool to reproducibly, definitively, and objectively identify biochemical changes related to carcinogenesis and recognize biomolecules associated with cancer. 3D tissue engineered models of normal oral mucosa and Squamous cell carcinoma were constructed and their chemical structure properties predicted by interpreting their spectral characteristics. Visible differences between the spectra of normal and cancerous models were found. Additionally, the data were analyzed with Principal Component Analysis (PCA), which further differentiated between the normal and cancer models, hence supporting the capabilities of Raman Spectroscopy as a tool for early detection of cancer.

Duration: 25 minutes

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