The Annals of otology, rhinology, and laryngology · 2006
Differential gene expression profiling of vocal fold polyps and Reinke's edema by complementary DNA microarray.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Duflo Suzy M, Thibeault Susan L, Li Wenhua, Smith Marshall E, Schade Goetz, Hess Markus M
Аннотация
OBJECTIVES: Our purpose was to determine whether complementary DNA (cDNA) microarray analysis (MA) can establish distinct gene expression profiles for 2 phenotypically similar vocal fold lesions: Reinke's edema (RE) and polyps. Established transcript profiles can provide insight into the molecular and cellular processes involved in these diseases.
METHODS: Eleven RE specimens and 17 polyps were analyzed with MA for 8,745 genes. Further MA profiling was attempted within each lesion group to identify molecular markers for reflux exposure and smoking. Prediction analysis was used to predict lesion classification for 2 unclassified samples. A real-time polymerase chain reaction was performed to corroborate MA transcript levels for selected significant genes.
RESULTS: Sixty-five genes were found to differentiate RE and polyps (p = .0088). For RE, 19 genes were differentiated for reflux exposure (p = .016). No genes were found to differentiate smokers from nonsmokers. For polyps, no genes were found to differentiate for reflux (p = .16) and smoking (p = .565). Categorization of unclassified lesions was possible with a minimum of 13 genes.
CONCLUSIONS: We demonstrate the feasibility of benign lesion classification based on MA. Microarray analysis is useful not only for improving diagnosis and classification of such lesions, but also for potentially generating prognostic indicators and targets for therapy.
METHODS: Eleven RE specimens and 17 polyps were analyzed with MA for 8,745 genes. Further MA profiling was attempted within each lesion group to identify molecular markers for reflux exposure and smoking. Prediction analysis was used to predict lesion classification for 2 unclassified samples. A real-time polymerase chain reaction was performed to corroborate MA transcript levels for selected significant genes.
RESULTS: Sixty-five genes were found to differentiate RE and polyps (p = .0088). For RE, 19 genes were differentiated for reflux exposure (p = .016). No genes were found to differentiate smokers from nonsmokers. For polyps, no genes were found to differentiate for reflux (p = .16) and smoking (p = .565). Categorization of unclassified lesions was possible with a minimum of 13 genes.
CONCLUSIONS: We demonstrate the feasibility of benign lesion classification based on MA. Microarray analysis is useful not only for improving diagnosis and classification of such lesions, but also for potentially generating prognostic indicators and targets for therapy.