Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers
- Equal contributors
1 Center for Medical Genetics, Department of Pediatrics and Genetics, Ghent University, De Pintelaan 185, 9000 Ghent, Belgium
2 Faculty of Education, Health and Social Work, University College Ghent, 9000 Ghent, Belgium
3 Department of Mathematical Modelling, Statistics and Bio-informatics, Ghent University, Coupure Links 653, 9000 Ghent, Belgium
4 MDxHealth, Tour 5 GIGA, Avenue de l'Hôpital 11, 4000 Liège, Belgium
5 NXTGNT, Ghent University, De Pintelaan 185, 9000 Ghent, Belgium
6 Children's Cancer Research Institute, St Anna Kinderkrebsforschug, Zimmermannplatz 10, A-1090 Vienna, Austria
7 University Children's Hospital Essen, Hufelandstraße 55, 45122 Essen, Germany
8 Department of Pathology, Medical School, University of Valencia, Blasco Ibañez 17, 46010 Valencia, Spain
9 National Children's Research Centre, Our Lady's Children's Hospital, Crumlin, Dublin 12, Ireland
10 Department of Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, York House, York Street, Dublin 2, Ireland
11 Department of Pediatrics, Brussels University Hospital, Laarbeeklaan 101, 1090 Brussels, Belgium
12 Department of Pediatric Hematology and Oncology, Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium
13 Pédiatrie, Hôpital de Jolimont, Rue Ferrer 159, 7100 La Louvière (Haine-Saint-Paul), Belgium
14 Department of Clinical Chemistry, Microbiology and Immunology, Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium
Genome Biology 2012, 13:R95 doi:10.1186/gb-2012-13-10-r95Published: 3 October 2012
Accurate outcome prediction in neuroblastoma, which is necessary to enable the optimal choice of risk-related therapy, remains a challenge. To improve neuroblastoma patient stratification, this study aimed to identify prognostic tumor DNA methylation biomarkers.
To identify genes silenced by promoter methylation, we first applied two independent genome-wide methylation screening methodologies to eight neuroblastoma cell lines. Specifically, we used re-expression profiling upon 5-aza-2'-deoxycytidine (DAC) treatment and massively parallel sequencing after capturing with a methyl-CpG-binding domain (MBD-seq). Putative methylation markers were selected from DAC-upregulated genes through a literature search and an upfront methylation-specific PCR on 20 primary neuroblastoma tumors, as well as through MBD- seq in combination with publicly available neuroblastoma tumor gene expression data. This yielded 43 candidate biomarkers that were subsequently tested by high-throughput methylation-specific PCR on an independent cohort of 89 primary neuroblastoma tumors that had been selected for risk classification and survival. Based on this analysis, methylation of KRT19, FAS, PRPH, CNR1, QPCT, HIST1H3C, ACSS3 and GRB10 was found to be associated with at least one of the classical risk factors, namely age, stage or MYCN status. Importantly, HIST1H3C and GNAS methylation was associated with overall and/or event-free survival.
This study combines two genome-wide methylation discovery methodologies and is the most extensive validation study in neuroblastoma performed thus far. We identified several novel prognostic DNA methylation markers and provide a basis for the development of a DNA methylation-based prognostic classifier in neuroblastoma.