| Sumario: | Oral squamous cell carcinomas (OSCCs) often present as advanced tumours requiring aggressive local and regional therapy and result in significant functional impairment. The objective is to develop pre-symptomatic screening detection of OSCC by a brush biopsy method which is less invasive than the conventional biopsy for histology. Given the molecular heterogeneity of oral cancer, it is unlikely that even a panel of tumour markers would provide accurate diagnosis. Therefore, approaches such as the matrix-assisted-laser-desorption/ionisation-time-of-flight-mass -spectrometry (MALDI-TOF-MS) allow several biomarkers or peptide profile patterns to be simultaneously assessed. Brush biopsies from 27 patients with histology-proven OSCCs plus 40 biopsies from 10 healthy controls were collected. MALDI-TOF-MS profiling was performed and additional statistical analysis of the data was used to classify the disease status according to the biological behaviour of the lesion. For classification a support vector machine algorithm was trained using spectra of brush biopsy samples to distinguish healthy control patients from patients with histology-proven OSCC. MALDI-TOF-MS was able to distinguish between healthy patients and OSCC patients with a sensitivity of 100% and specificity of 93%. In summary, MALDI-TOF-MS in combination with sophisticated bioinformatic methods can distinguish OSCC patients from non-cancer controls with excellent sensitivity and specificity. Further improvement and validation of this approach is necessary to determine its feasibility to assist the pre-symptomatic detection of head and neck cancer screening in routine daily practice.
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