Literature DB >> 22157715

A pyrosequencing assay for the quantitative methylation analysis of the PCDHB gene cluster, the major factor in neuroblastoma methylator phenotype.

Barbara Banelli1, Claudio Brigati, Angela Di Vinci, Ida Casciano, Alessandra Forlani, Luana Borzì, Giorgio Allemanni, Massimo Romani.   

Abstract

Epigenetic alterations are hallmarks of cancer and powerful biomarkers, whose clinical utilization is made difficult by the absence of standardization and of common methods of data interpretation. The coordinate methylation of many loci in cancer is defined as 'CpG island methylator phenotype' (CIMP) and identifies clinically distinct groups of patients. In neuroblastoma (NB), CIMP is defined by a methylation signature, which includes different loci, but its predictive power on outcome is entirely recapitulated by the PCDHB cluster only. We have developed a robust and cost-effective pyrosequencing-based assay that could facilitate the clinical application of CIMP in NB. This assay permits the unbiased simultaneous amplification and sequencing of 17 out of 19 genes of the PCDHB cluster for quantitative methylation analysis, taking into account all the sequence variations. As some of these variations were at CpG doublets, we bypassed the data interpretation conducted by the methylation analysis software to assign the corrected methylation value at these sites. The final result of the assay is the mean methylation level of 17 gene fragments in the protocadherin B cluster (PCDHB) cluster. We have utilized this assay to compare the methylation levels of the PCDHB cluster between high-risk and very low-risk NB patients, confirming the predictive value of CIMP. Our results demonstrate that the pyrosequencing-based assay herein described is a powerful instrument for the analysis of this gene cluster that may simplify the data comparison between different laboratories and, in perspective, could facilitate its clinical application. Furthermore, our results demonstrate that, in principle, pyrosequencing can be efficiently utilized for the methylation analysis of gene clusters with high internal homologies.

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Year:  2011        PMID: 22157715     DOI: 10.1038/labinvest.2011.169

Source DB:  PubMed          Journal:  Lab Invest        ISSN: 0023-6837            Impact factor:   5.662


  13 in total

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9.  Performance of Different Analytical Software Packages in Quantification of DNA Methylation by Pyrosequencing.

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