Array-based profiling of reference-independent methylation status (aPRIMES) identifies frequent promoter methylation and consecutive downregulation of ZIC2 in pediatric medulloblastoma

Existing microarray-based approaches for screening of DNA methylation are hampered by a number of shortcomings, such as the introduction of bias by DNA copy-number imbalances in the test genome and negligence of tissue-specific methylation patterns. We developed a method designated array-based profiling of reference-independent methylation status (aPRIMES) that allows the detection of direct methylation status rather than relative methylation. Array-PRIMES is based on the differential restriction and competitive hybridization of methylated and unmethylated DNA by methylation-specific and methylation-sensitive restriction enzymes, respectively. We demonstrate the accuracy of aPRIMES in detecting the methylation status of CpG islands for different states of methylation. Application of aPRIMES to the DNA from desmoplastic medulloblastomas of monozygotic twins showed strikingly similar methylation profiles. Additional analysis of 18 sporadic medulloblastomas revealed an overall correlation between highly methylated tumors and poor clinical outcome and identified ZIC2 as a frequently methylated gene in pediatric medulloblastoma

Medulloblastomas overexpress the p53-inactivating oncogene WIP1/PPM1D

Medulloblastoma is the most common malignant brain tumor of childhood. Despite numerous advances, clinical challenges range from recurrent and progressive disease to long-term toxicities in survivors. The lack of more effective, less toxic therapies results from our limited understanding of medulloblastoma growth. Although TP53 is the most commonly altered gene in cancers, it is rarely mutated in medulloblastoma. Accumulating evidence, however, indicates that TP53 pathways are disrupted in medulloblastoma. Wild-typep53-induced phosphatase 1 (WIP1 or PPM1D) encodes a negative regulator of p53. WIP1 amplification (17q22-q23) and its overexpression have been reported in diverse cancer types. We examined primary medulloblastoma specimens and cell lines, and detected WIP1 copy gain and amplification prevalent among but not exclusively in the tumors with 17q gain and isochromosome 17q (i17q), which are among the most common cytogenetic lesions in medulloblastoma. WIP1 RNA levels were significantly higher in the tumors with 17q gain or i17q. Immunoblots confirmed significant WIP1 protein in primary tumors, generally higher in those with 17q gain or i17q. Under basal growth conditions and in response to the chemotherapeutic agent, etoposide, WIP1 antagonized p53-mediated apoptosis in medulloblastoma cell lines. These results indicate that medulloblastoma express significant levels of WIP1 that modulate genotoxic responsiveness by negatively regulating p53

Application of aPRIMES in pediatric medulloblastoma identifying groups with low and high methylation

<p><b>Copyright information:</b></p><p>Taken from "Array-based profiling of reference-independent methylation status (aPRIMES) identifies frequent promoter methylation and consecutive downregulation of ZIC2 in pediatric medulloblastoma"</p><p></p><p>Nucleic Acids Research 2007;35(7):e51-e51.</p><p>Published online 7 Mar 2007</p><p>PMCID:PMC1874664.</p><p>© 2007 The Author(s)</p> () Scatter plots representing the correlation of methylation patterns of monozygotic twins (patients M1 and M10) with simultaneous desmoplastic medulloblastoma, a case of sporadic classic medulloblastoma (M5), and normal cerebellum. () twin one (patient M1) in comparison with normal cerebellum (pool of five unaffected donors), () twin 1 versus twin 2 (patient M10) and () twin one compared with a sporadic classic medulloblastoma (patient M5). Spearman-correlation coefficients () are given for each plot. Representative microarray sections of () patient M1 (low methylator group) and () patient M5 (high methylator group). Examples for differentially methylated clones are highlighted with white circles. () Kaplan–Meier plot of estimated survival time distribution with corresponding log-rank test. For survival analysis, patients were grouped into low and high methylator groups according to the percentage of highly methylated clones