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1.  Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers 
Genome Biology  2012;13(10):R95.
Background
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.
Results
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.
Conclusions
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.
doi:10.1186/gb-2012-13-10-r95
PMCID: PMC3491423  PMID: 23034519
2.  Clinical and Biologic Features Predictive of Survival After Relapse of Neuroblastoma: A Report From the International Neuroblastoma Risk Group Project 
Journal of Clinical Oncology  2011;29(24):3286-3292.
Purpose
Survival after neuroblastoma relapse is poor. Understanding the relationship between clinical and biologic features and outcome after relapse may help in selection of optimal therapy. Our aim was to determine which factors were significantly predictive of postrelapse overall survival (OS) in patients with recurrent neuroblastoma—particularly whether time from diagnosis to first relapse (TTFR) was a significant predictor of OS.
Patients and Methods
Patients with first relapse/progression were identified in the International Neuroblastoma Risk Group (INRG) database. Time from study enrollment until first event and OS time starting from first event were calculated. Cox regression models were used to calculate the hazard ratio of increased death risk and perform survival tree regression. TTFR was tested in a multivariable Cox model with other factors.
Results
In the INRG database (N = 8,800), 2,266 patients experienced first progression/relapse. Median time to relapse was 13.2 months (range, 1 day to 11.4 years). Five-year OS from time of first event was 20% (SE, ± 1%). TTFR was statistically significantly associated with OS time in a nonlinear relationship; patients with TTFR of 36 months or longer had the lowest risk of death, followed by patients who relapsed in the period of 0 to less than 6 months or 18 to 36 months. Patients who relapsed between 6 and 18 months after diagnosis had the highest risk of death. TTFR, age, International Neuroblastoma Staging System stage, and MYCN copy number status were independently predictive of postrelapse OS in multivariable analysis.
Conclusion
Age, stage, MYCN status, and TTFR are significant prognostic factors for postrelapse survival and may help in the design of clinical trials evaluating novel agents.
doi:10.1200/JCO.2010.34.3392
PMCID: PMC3158599  PMID: 21768459
3.  The First European Interdisciplinary Ewing Sarcoma Research Summit 
The European Network for Cancer Research in Children and Adolescents (ENCCA) provides an interaction platform for stakeholders in research and care of children with cancer. Among ENCCA objectives is the establishment of biology-based prioritization mechanisms for the selection of innovative targets, drugs, and prognostic markers for validation in clinical trials. Specifically for sarcomas, there is a burning need for novel treatment options, since current chemotherapeutic treatment protocols have met their limits. This is most obvious for metastatic Ewing sarcoma (ES), where long term survival rates are still below 20%. Despite significant progress in our understanding of ES biology, clinical translation of promising laboratory results has not yet taken place due to fragmentation of research and lack of an institutionalized discussion forum. To fill this gap, ENCCA assembled 30 European expert scientists and five North American opinion leaders in December 2011 to exchange thoughts and discuss the state of the art in ES research and latest results from the bench, and to propose biological studies and novel promising therapeutics for the upcoming European EWING2008 and EWING2012 clinical trials.
doi:10.3389/fonc.2012.00054
PMCID: PMC3361960  PMID: 22662320
Ewing sarcoma; animal models; sarcomagenesis; genomics; epigenetics; biomarkers; drug screen; prognosis
4.  Outcome Prediction of Children with Neuroblastoma using a Multigene Expression Signature, a Retrospective SIOPEN/COG/GPOH Study 
The lancet oncology  2009;10(7):663-671.
BACKGROUND
More accurate prognostic assessment of patients with neuroblastoma is required to improve the choice of risk-related therapy. The aim of this study is to develop and validate a gene expression signature for improved outcome prediction.
METHODS
Fifty-nine genes were carefully selected based on an innovative data-mining strategy and profiled in the largest neuroblastoma patient series (n=579) to date using RT-qPCR starting from only 20 ng of RNA. A multigene expression signature was built using 30 training samples, tested on 313 test samples and subsequently validated in a blind study on an independent set of 236 additional tumours.
FINDINGS
The signature accurately classifies patients with respect to overall and progression-free survival (p<0·0001). The signature has a performance, sensitivity, and specificity of 85·4% (95%CI: 77·7–93·2), 84·4% (95%CI: 66·5–94·1), and 86·5% (95%CI: 81·1–90·6), respectively to predict patient outcome. Multivariate analysis indicates that the signature is a significant independent predictor after controlling for currently used riskfactors. Patients with high molecular risk have a higher risk to die from disease and for relapse/progression than patients with low molecular risk (odds ratio of 19·32 (95%CI: 6·50–57·43) and 3·96 (95%CI: 1·97–7·97) for OS and PFS, respectively). Patients with increased risk for adverse outcome can also be identified within the current treatment groups demonstrating the potential of this signature for improved clinical management. These results were confirmed in the validation study in which the signature was also independently statistically significant in a model adjusted for MYCN status, age, INSS stage, ploidy, INPC grade of differentiation, and MKI. The high patient/gene ratio (579/59) underlies the observed statistical power and robustness.
INTERPRETATION
A 59-gene expression signature predicts outcome of neuroblastoma patients with high accuracy. The signature is an independent risk predictor, identifying patients with increased risk in the current clinical risk groups. The applied method and signature is suitable for routine lab testing and ready for evaluation in prospective studies.
FUNDING
The Belgian Foundation Against Cancer, found of public interest (project SCIE2006-25), the Children Cancer Fund Ghent, the Belgian Society of Paediatric Haematology and Oncology, the Belgian Kid’s Fund and the Fondation Nuovo-Soldati (JV), the Fund for Scientific Research Flanders (KDP, JH), the Fund for Scientific Research Flanders (grant number: G•0198•08), the Institute for the Promotion of Innovation by Science and Technology in Flanders, Strategisch basisonderzoek (IWT-SBO 60848), the Fondation Fournier Majoie pour l’Innovation, the Instituto Carlos III,RD 06/0020/0102 Spain, the Italian Neuroblastoma Foundation, the European Community under the FP6 (project: STREP: EET-pipeline, number: 037260), and the Belgian program of Interuniversity Poles of Attraction, initiated by the Belgian State, Prime Minister's Office, Science Policy Programming.
doi:10.1016/S1470-2045(09)70154-8
PMCID: PMC3045079  PMID: 19515614

Results 1-4 (4)