Literature DB >> 17363581

Large-scale CpG methylation analysis identifies novel candidate genes and reveals methylation hotspots in acute lymphoblastic leukemia.

Kristen H Taylor1, Keila E Pena-Hernandez, J Wade Davis, Gerald L Arthur, Deiter J Duff, Huidong Shi, Farah B Rahmatpanah, Ozy Sjahputera, Charles W Caldwell.   

Abstract

This study examined DNA methylation associated with acute lymphoblastic leukemia (ALL) and showed that selected molecular targets can be pharmacologically modulated to reverse gene silencing. A CpG island (CGI) microarray containing more than 3,400 unique clones that span all human chromosomes was used for large-scale discovery experiments and led to 262 unique CGI loci being statistically identified as methylated in ALL lymphoblasts. The methylation status of 10 clones encompassing 11 genes (DCC, DLC-1, DDX51, KCNK2, LRP1B, NKX6-1, NOPE, PCDHGA12, RPIB9, ABCB1, and SLC2A14) identified as differentially methylated between ALL patients and controls was independently verified. Consequently, the methylation status of DDX51 was found to differentiate patients with B- and T-ALL subtypes (P = 0.011, Fisher's exact test). Next, the relationship between methylation and expression of these genes was examined in ALL cell lines (NALM-6 and Jurkat) before and after treatments with 5-aza-2-deoxycytidine and trichostatin A. More than a 10-fold increase in mRNA expression was observed for two previously identified tumor suppressor genes (DLC-1 and DCC) and also for RPIB9 and PCDHGA12. Although the mechanisms that lead to the CGI methylation of these genes are unknown, bisulfite sequencing of the promoter of RPIB9 suggests that expression is inhibited by methylation within SP1 and AP2 transcription factor binding motifs. Finally, specific chromosomal methylation hotspots were found to be associated with ALL. This study sets the stage for acquiring a better biological understanding of ALL and for the identification of epigenetic biomarkers useful for differential diagnosis, therapeutic monitoring, and the detection of leukemic relapse.

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Year:  2007        PMID: 17363581     DOI: 10.1158/0008-5472.CAN-06-3993

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  61 in total

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