BACKGROUND: Currently, the classification of oral squamous cell carcinoma (OSCC) depends heavily on the clinical and pathologic examination of tissue. This system can lead to the classification of potentially heterogeneous tumors into single groups when they may have different degrees of aggressiveness. No system to date has incorporated genetic changes as a factor by which to classify OSCC tumors. METHODS: To test the hypothesis that OSCC has a genome-wide genetic expression profile that differs from normal oral tissue and that transcriptional expression profiling can be used to characterize the heterogeneity among tumors, the authors examined the genetic expression profiles of 26 invasive squamous cell carcinomas of the oral cavity and oropharynx, 2 premalignant lesions, and 18 normal oral tissue samples using oligonucleotide arrays that contained probes representing approximately 7000 full-length human genes. RESULTS: Using hierarchical clustering analysis, the data show that oral carcinomas are distinguishable from normal oral tissue based on genome-wide transcriptional expression patterns. However, there is genetic expression profile heterogeneity among tumors of a particular histopathologic grade and stage. In addition, using a statistical approach that integrated normalization and regression analysis, the authors found 314 genes that were expressed differentially in the OSCC samples with statistical significance (P <or= 0.05). Of these, 239 genes were overexpressed in the OSCC samples, whereas 75 genes were down-regulated. CONCLUSIONS: No statistically significant differences in gene expression were found between early-stage disease and late-stage disease or between metastatic tumors and nonmetastatic tumors. The implications of these findings for the prediction of clinical outcome and for the discovery of new OSCC tumor markers are discussed. Copyright 2002 American Cancer Society.DOI 10.1002/cncr.10875
BACKGROUND: Currently, the classification of oral squamous cell carcinoma (OSCC) depends heavily on the clinical and pathologic examination of tissue. This system can lead to the classification of potentially heterogeneous tumors into single groups when they may have different degrees of aggressiveness. No system to date has incorporated genetic changes as a factor by which to classify OSCC tumors. METHODS: To test the hypothesis that OSCC has a genome-wide genetic expression profile that differs from normal oral tissue and that transcriptional expression profiling can be used to characterize the heterogeneity among tumors, the authors examined the genetic expression profiles of 26 invasive squamous cell carcinomas of the oral cavity and oropharynx, 2 premalignant lesions, and 18 normal oral tissue samples using oligonucleotide arrays that contained probes representing approximately 7000 full-length human genes. RESULTS: Using hierarchical clustering analysis, the data show that oral carcinomas are distinguishable from normal oral tissue based on genome-wide transcriptional expression patterns. However, there is genetic expression profile heterogeneity among tumors of a particular histopathologic grade and stage. In addition, using a statistical approach that integrated normalization and regression analysis, the authors found 314 genes that were expressed differentially in the OSCC samples with statistical significance (P <or= 0.05). Of these, 239 genes were overexpressed in the OSCC samples, whereas 75 genes were down-regulated. CONCLUSIONS: No statistically significant differences in gene expression were found between early-stage disease and late-stage disease or between metastatic tumors and nonmetastatic tumors. The implications of these findings for the prediction of clinical outcome and for the discovery of new OSCC tumor markers are discussed. Copyright 2002 American Cancer Society.DOI 10.1002/cncr.10875
Authors: Winston Patrick Kuo; Eduardo Mendez; Chu Chen; Mark E Whipple; Greg Farell; Nicholas Agoff; Peter J Park Journal: AMIA Annu Symp Proc Date: 2003
Authors: Eduardo Méndez; John R Houck; David R Doody; Wenhong Fan; Pawadee Lohavanichbutr; Tessa C Rue; Bevan Yueh; Neal D Futran; Melissa P Upton; D Gregory Farwell; Patrick J Heagerty; Lue Ping Zhao; Stephen M Schwartz; Chu Chen Journal: Clin Cancer Res Date: 2009-02-15 Impact factor: 12.531