Integrated analysis of epigenomic and genomic changes by DNA methylation dependent mechanisms provides potential novel biomarkers for prostate cancer
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Nicole M. A. White-Al Habeeb1,2, Linh T. Ho1,2, Ekaterina Olkhov-Mitsel1,2, Ken Kron3, Vaijayanti Pethe1, Melanie Lehman4, Lidija Jovanovic4, Neil Fleshner3, Theodorus van der Kwast2,5, Colleen C. Nelson4 and Bharati Bapat1,2,5
1 Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital
2 Department of Laboratory Medicine and Pathobiology, University of Toronto
3 Ontario Cancer Institute, Princess Margaret Cancer Center, University Health Network, Toronto, Canada
4 Australian Prostate Cancer Research Center, Queensland University of Technology, Brisbane, Australia
5 Department of Pathology, University Health Network, Toronto, Canada
Bharati Bapat, email:
Keywords: Prostate cancer, tumor markers, biomarkers, epigenetics, DNA methylation, expression array, DAC treatment, demethylating agent treatment
Received: April 25, 2014 Accepted: August 05, 2014 Published: August 06, 2014
Epigenetic silencing mediated by CpG methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with tumor progression may identify potential prognostic markers for prostate cancer (PCa). We treated two PCa cell lines, 22Rv1 and DU-145 with the demethylating agent 5-Aza 2’–deoxycitidine (DAC) and global methylation status was analyzed by performing methylation-sensitive restriction enzyme based differential methylation hybridization strategy followed by genome-wide CpG methylation array profiling. In addition, we examined gene expression changes using a custom microarray. Gene Set Enrichment Analysis (GSEA) identified the most significantly dysregulated pathways. In addition, we assessed methylation status of candidate genes that showed reduced CpG methylation and increased gene expression after DAC treatment, in Gleason score (GS) 8 vs. GS6 patients using three independent cohorts of patients; the publically available The Cancer Genome Atlas (TCGA) dataset, and two separate patient cohorts. Our analysis, by integrating methylation and gene expression in PCa cell lines, combined with patient tumor data, identified novel potential biomarkers for PCa patients. These markers may help elucidate the pathogenesis of PCa and represent potential prognostic markers for PCa patients.
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