Publication Date:
2009-11-20
Description:
Abstract 707 Epigenetic deregulation of genes through aberrant DNA methylation has been widely reported in cancer. We hypothesized that in AML this aberrant DNA methylation does not occur randomly, but rather occurs in specific and distinct patterns. Therefore, large-scale genome-wide analysis of the DNA methylome could help explain and define the complexity underlying leukemia biology and reveal the existence of epigenetically defined variants of AML. Using the HELP microarray assay, which measures DNA methylation at 50,000 CpG sites annotated to ∼14,000 promoters, we obtained DNA methylation profiles for 344 AML patients seen at Erasmus University Medical Center. Median follow-up based on survivors was 18.2 months (7-215); median age: 48 years (15-77). Unsupervised analysis (hierarchical clustering, correlation distance with Ward's clustering method) demonstrated that based on their methylation profiles AML patients distributed into 16 cohorts. 11 of these groups were also defined by the presence of specific molecular lesions: inv(16) [cluster 1], t(8;21) [cluster 3], t(15;17) [cluster 6], CEBPA-mutant [clusters 4 and 9], CEBPA-silenced [cluster 10] NPM1-mutant [clusters 12, 13, 14 and 16] and 11q23 abnormalities [cluster 11]. Enrichment for cases harboring a specific molecular lesion within a given cluster was determined using Fisher's exact test (p70% cases and present in at least 10/16 cluster signatures). This common epigenetic signature included the tumor suppressor PDZD2, the nuclear import proteins IPO8 and TNPO3, PIAS2, a regulator of MAP kinase signaling, CDK8, and CSDA, a regulator of CSF2. Gene expression profiling of the same patients indicated that at least 50% of these genes were also aberrantly silenced compared to normal CD34+ cells. Finally, we randomly divided the 344-patient cohort into a training group of 200 patients, a test group (n=95) and an independent validation group (n=49), and using the Supervised Principal Components algorithm identified a 15-gene methylation classifier that was predictive of OS (p
Print ISSN:
0006-4971
Electronic ISSN:
1528-0020
Topics:
Biology
,
Medicine
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