PURPOSE: Oral fluid (saliva) meets the demand for noninvasive, accessible, and highly efficient diagnostic medium. Recent discovery that a large panel of human RNA can be reliably detected in saliva gives rise to a novel clinical approach, salivary transcriptome diagnostics. The purpose of this study is to evaluate the diagnostic value of this new approach by using oral squamous cell carcinoma (OSCC) as the proof-of-principle disease. EXPERIMENTAL DESIGN: Unstimulated saliva was collected from patients (n = 32) with primary T1/T2 OSCC and normal subjects (n = 32) with matched age, gender, and smoking history. RNA isolation was done from the saliva supernatant, followed by two-round linear amplification with T7 RNA polymerase. Human Genome U133A microarrays were applied for profiling human salivary transcriptome. The different gene expression patterns were analyzed by combining a t test comparison and a fold-change analysis on 10 matched cancer patients and controls. Quantitative polymerase chain reaction (qPCR) was used to validate the selected genes that showed significant difference (P < 0.01) by microarray. The predictive power of these salivary mRNA biomarkers was analyzed by receiver operating characteristic curve and classification models. RESULTS: Microarray analysis showed there are 1,679 genes exhibited significantly different expression level in saliva between cancer patients and controls (P < 0.05). Seven cancer-related mRNA biomarkers that exhibited at least a 3.5-fold elevation in OSCC saliva (P < 0.01) were consistently validated by qPCR on saliva samples from OSCC patients (n = 32) and controls (n = 32). These potential salivary RNA biomarkers are transcripts of IL8, IL1B, DUSP1, HA3, OAZ1, S100P, and SAT. The combinations of these biomarkers yielded sensitivity (91%) and specificity (91%) in distinguishing OSCC from the controls. CONCLUSIONS: The utility of salivary transcriptome diagnostics is successfully demonstrated in this study for oral cancer detection. This novel clinical approach could be exploited to a robust, high-throughput, and reproducible tool for early cancer detection. Salivary transcriptome profiling can be applied to evaluate its usefulness for other major disease applications as well as for normal health surveillance.
PURPOSE: Oral fluid (saliva) meets the demand for noninvasive, accessible, and highly efficient diagnostic medium. Recent discovery that a large panel of human RNA can be reliably detected in saliva gives rise to a novel clinical approach, salivary transcriptome diagnostics. The purpose of this study is to evaluate the diagnostic value of this new approach by using oral squamous cell carcinoma (OSCC) as the proof-of-principle disease. EXPERIMENTAL DESIGN: Unstimulated saliva was collected from patients (n = 32) with primary T1/T2 OSCC and normal subjects (n = 32) with matched age, gender, and smoking history. RNA isolation was done from the saliva supernatant, followed by two-round linear amplification with T7 RNA polymerase. Human Genome U133A microarrays were applied for profiling human salivary transcriptome. The different gene expression patterns were analyzed by combining a t test comparison and a fold-change analysis on 10 matched cancerpatients and controls. Quantitative polymerase chain reaction (qPCR) was used to validate the selected genes that showed significant difference (P < 0.01) by microarray. The predictive power of these salivary mRNA biomarkers was analyzed by receiver operating characteristic curve and classification models. RESULTS: Microarray analysis showed there are 1,679 genes exhibited significantly different expression level in saliva between cancerpatients and controls (P < 0.05). Seven cancer-related mRNA biomarkers that exhibited at least a 3.5-fold elevation in OSCC saliva (P < 0.01) were consistently validated by qPCR on saliva samples from OSCC patients (n = 32) and controls (n = 32). These potential salivary RNA biomarkers are transcripts of IL8, IL1B, DUSP1, HA3, OAZ1, S100P, and SAT. The combinations of these biomarkers yielded sensitivity (91%) and specificity (91%) in distinguishing OSCC from the controls. CONCLUSIONS: The utility of salivary transcriptome diagnostics is successfully demonstrated in this study for oral cancer detection. This novel clinical approach could be exploited to a robust, high-throughput, and reproducible tool for early cancer detection. Salivary transcriptome profiling can be applied to evaluate its usefulness for other major disease applications as well as for normal health surveillance.
Authors: Lei Zhang; Hua Xiao; Hui Zhou; Silverio Santiago; Jay M Lee; Edward B Garon; Jieping Yang; Ole Brinkmann; Xinmin Yan; David Akin; David Chia; David Elashoff; No-Hee Park; David T W Wong Journal: Cell Mol Life Sci Date: 2012-06-12 Impact factor: 9.261
Authors: David Elashoff; Hui Zhou; Jean Reiss; Jianghua Wang; Hua Xiao; Bradley Henson; Shen Hu; Martha Arellano; Uttam Sinha; Anh Le; Diana Messadi; Marilene Wang; Vishad Nabili; Mark Lingen; Darly Morris; Timothy Randolph; Ziding Feng; David Akin; Dragana A Kastratovic; David Chia; Elliot Abemayor; David T W Wong Journal: Cancer Epidemiol Biomarkers Prev Date: 2012-02-01 Impact factor: 4.254
Authors: Alexandra Lucs; Benjamin Saltman; Christine H Chung; Bettie M Steinberg; David L Schwartz Journal: Head Neck Date: 2012-01-27 Impact factor: 3.147
Authors: Noh Jin Park; Xiaofeng Zhou; Tianwei Yu; Brigitta M N Brinkman; Bernhard G Zimmermann; Visswanathan Palanisamy; David T Wong Journal: Arch Oral Biol Date: 2006-10-18 Impact factor: 2.633