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Journal of Computational Biology
Epigenetic Hypothesis Tests for Methylation and Acetylation in a Triple Microarray System
To cite this article:
Lang Li, Huidong Shi, Constantin Yiannoutsos, Tim Hui-Ming Huang, Kenneth P. Nephew.
Journal of Computational Biology.
April 2005,
12(3): 370-390.
doi:10.1089/cmb.2005.12.370.
Published in Volume: 12 Issue 3: April 21, 2005
Lang Li Division of Biostatistics, Department of Medicine, Indiana University, Indianapolis, IN 46022. Indiana University Cancer Center, Indianapolis, IN 46022. Huidong Shi Department of Pathology and Anatomical Sciences, Ellis Fischel Cancer Center, University of Missouri, School of Medicine, Columbia, Missouri 65203. Constantin Yiannoutsos Division of Biostatistics, Department of Medicine, Indiana University, Indianapolis, IN 46022. Indiana University Cancer Center, Indianapolis, IN 46022. Tim Hui-Ming Huang Division of Human Cancer Genetics, Department of Molecular Virology, Immunology, and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210. Kenneth P. Nephew Indiana University Cancer Center, Indianapolis, IN 46022. Medical Sciences, Indiana University, Bloomington, IN 47405. To fully elucidate the functional relationship between DNA methylation and histone hypoacetylation in gene silencing, we have developed an integrated "triple" microarray system that allows us to begin to decipher the influence of epigenetic hierarchies on the regulation of gene expression in cancer cells. Our hypothesis is that in the promoter region of a silenced gene, reversal of two epigenetic factors (i.e., DNA demethylation and/or histone hyperacetylation) is highly correlated with gene reexpression after treatment of the human epithelial ovarian cancer cell line CP70 with the drug combination 5-aza-2'-deoxycytidine (DAC), a demethylating agent, and trichostatin A (TSA), an inhibitor of histone deacetylases. To estimate the posterior probabilities for genes with altered expression, DNA methylation and histone acetylation status measured with a triple-microarray system, we have employed an established empirical Bayes model. Two methods have been proposed to test our hypothesis that DNA demethylation and histone hyperacetylation are highly correlated among those up-regulated genes. One method follows a weighted least squares regression, while the other is derived from a chi-square statistic. The data derived by these approaches, which have been further verified through bootstrap analyses, support the proposed epigenetic correlation (p-values are less than 0.001). Further simulations suggest that even if the constant variance and normality assumptions do not hold, the power of those two tests is robust. 
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