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Chip checks for oral cancer
Date:4/5/2010

The gentle touch of a lesion on the tongue or cheek with a brush can help detect oral cancer with success rates comparable to more invasive techniques, according to preliminary studies by researchers at Rice University, the University of Texas Health Science Centers at Houston and San Antonio and the University of Texas M.D. Anderson Cancer Center.

The test that uses Rice's diagnostic nano-bio-chip was found to be 97 percent "sensitive" and 93 percent specific in detecting which patients had malignant or premalignant lesions, results that compared well with traditional tests.

The study appeared online in the journal Cancer Prevention Research.

"One of the key discoveries in this paper is to show that the miniaturized, noninvasive approach produces about the same result as the pathologists do," said John McDevitt, the Brown-Wiess Professor of Chemistry and Bioengineering at Rice. His lab developed the novel nano-bio-chip technology at the university's BioScience Research Collaborative.

Oral cancer afflicts more than 300,000 people a year, including 35,000 in the United States alone. The five-year survival rate is 60 percent, but if cancer is detected early, that rate rises to 90 percent.

McDevitt and his team are working to create an inexpensive chip that can differentiate premalignancies from the 95 percent of lesions that will not become cancerous.

The minimally invasive technique would deliver results in 15 minutes instead of several days, as lab-based diagnostics do now; and instead of an invasive, painful biopsy, this new procedure requires just a light brush of the lesion on the cheek or tongue with an instrument that looks like a toothbrush.

"This area of diagnostics and testing has been terribly challenging for the scientific and clinical community," said McDevitt, who came to Rice from the University of Texas at Austin in 2009. "Part of the problem is that there are no good tools
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Contact: David Ruth
druth@rice.edu
713-348-6327
Rice University
Source:Eurekalert

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