期刊
ORAL ONCOLOGY
卷 47, 期 4, 页码 278-281出版社
ELSEVIER
DOI: 10.1016/j.oraloncology.2011.02.005
关键词
HNSCC; OSCC; Brush biopsy; MALDI-TOF mass spectrometry; Peptide profiling; Support vector machine classification
资金
- German Federal Ministry of Education and Research [NBL-3, formel.1-27, 01 ZZ 0106]
- Fund for Regional Development
- Medical Faculty of the University of Leipzig, Germany
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. (C) 2011 Elsevier Ltd. All rights reserved.
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