ArticleJournal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology2013
A prototype tobacco-associated oral squamous cell carcinoma classifier using RNA from brush cytology.
Article in Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- A brief review of cytology in dentistry.British dental journal · 2024Review
- Heat shock factor 1 in cancer-associated fibroblasts is a potential prognostic factor and drives progression of oral squamous cell carcinoma.Cancer science · 2019Article
- microRNA from brush biopsy to characterize oral squamous cell carcinoma epithelium.Cancer medicine · 2017Article
- microRNA-21 and microRNA-375 from oral cytology as biomarkers for oral tongue cancer detection.Oral oncology · 2016Article
- Gene expression based evidence of innate immune response activation in the epithelium with oral lichen planus.Archives of oral biology · 2014Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
backgroundOral cancer in the form of squamous cell carcinoma (OSCC) is typically detected in advanced stages when treatment is complex and may not be curative. The need for surgical biopsy may contribute to delays in diagnosis and impede early detection. Multiple studies of RNA from surgically obtained tumor samples have revealed many genes differentially expressed with this disease. We sought to determine whether the identified mRNAs could be used as markers by a non-invasive detection system for OSCC using RNA from brush cytology.
methodsLevels of mRNAs from 21 genes known to be differentially expressed in head and neck squamous cell carcinoma surgical samples, compared with controls, were shown to be quantifiable in oral brush cytology samples. These mRNAs were quantified in a training set of 14 tumor and 20 non-malignant brush cytology samples from tobacco/betel nut users. With the measurement of two additional mRNAs and analysis using support vector machines algorithm for class prediction of these cancers was produced.
resultsThis OSCC classifier based on the levels of 5 mRNAs in RNA from brush cytology initially showed 0.93 sensitivity and 0.91 specificity in differentiating OSCC from benign oral mucosal lesions based on leave-one-out cross-validation. When used on a test set of 19 samples from 6 OSCCs and 13 non-malignant oral lesions, we found misclassification of only one OSCC and one benign lesion.
conclusionsThis shows the promise of using RNA from brush cytology for early OSCC detection and the potential for clinical usage of this non-invasive classifier.
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