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Nano-bio-chip sensor platform for examination of oral exfoliative cytology

Oral cancer is a deadly and disfiguring disease that could greatly benefit from new diagnostic approaches enabling early detection. In this pilot study, we describe a nano-bio-chip (NBC) sensor technique for analysis of oral cancer biomarkers in exfoliative cytology specimens, targeting both biochem...

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Published in:Cancer prevention research (Philadelphia, Pa.) Pa.), 2010-04, Vol.3 (4), p.518-528
Main Authors: Weigum, Shannon E, Floriano, Pierre N, Redding, Spencer W, Yeh, Chih-Ko, Westbrook, Stephen D, McGuff, H Stan, Lin, Alan, Miller, Frank R, Villarreal, Fred, Rowan, Stephanie D, Vigneswaran, Nadarajah, Williams, Michelle D, McDevitt, John T
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Language:English
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Summary:Oral cancer is a deadly and disfiguring disease that could greatly benefit from new diagnostic approaches enabling early detection. In this pilot study, we describe a nano-bio-chip (NBC) sensor technique for analysis of oral cancer biomarkers in exfoliative cytology specimens, targeting both biochemical and morphologic changes associated with early oral tumorigenesis. Here, oral lesions from 41 dental patients, along with normal epithelium from 11 healthy volunteers, were sampled using a noninvasive brush biopsy technique. Specimens were enriched, immunolabeled, and imaged in the NBC sensor according to previously established assays for the epidermal growth factor receptor (EGFR) biomarker and cytomorphometry. A total of 51 measurement parameters were extracted using custom image analysis macros, including EGFR labeling intensity, cell and nuclear size, and the nuclear-to-cytoplasmic ratio. Four key parameters were significantly elevated in both dysplastic and malignant lesions relative to healthy oral epithelium, including the nuclear area and diameter (P < 0.0001), the nuclear-to-cytoplasmic ratio (P < 0.0001), and EGFR biomarker expression (P < 0.03). Further examination using logistic regression and receiver operating characteristic curve analyses identified morphologic features as the best predictors of disease (area under the curve < or =0.93) individually, whereas a combination of all features further enhanced discrimination of oral cancer and precancerous conditions (area under the curve, 0.94) with high sensitivity and specificity. Further clinical trials are necessary to validate the regression model and evaluate other potential biomarkers, but this pilot study supports the NBC sensor technique as a promising new diagnostic tool for early detection of oral cancer, which could enhance patient care and survival.
ISSN:1940-6207
1940-6215
DOI:10.1158/1940-6207.capr-09-0139