Outcome prediction and risk assessment by quantitative pyrosequencing methylation analysis of the SFN gene in advanced stage, high‐risk, neuroblastic tumor patients

• Published in: International journal of cancer 2010-02, Vol.126 (3), p.656-668
• Main Authors: Banelli, Barbara, Bonassi, Stefano, Casciano, Ida, Mazzocco, Katia, Di Vinci, Angela, Scaruffi, Paola, Brigati, Claudio, Allemanni, Giorgio, Borzì, Luana, Tonini, Gian Paolo, Romani, Massimo
• Format: Article
• Language: English
• Subjects: 14-3-3 Proteins; Azacitidine - pharmacology; Biomarkers, Tumor - biosynthesis; Biomarkers, Tumor - genetics; Cell Line, Tumor - drug effects; Cell Line, Tumor - metabolism; Child; Child, Preschool; Cohort Studies; CpG Islands; DNA methylation; DNA Methylation - drug effects; DNA, Neoplasm - chemistry; DNA, Neoplasm - genetics; epigenetics; Exonucleases - biosynthesis; Exonucleases - genetics; Exoribonucleases; Female; Ganglioneuroblastoma - genetics; Ganglioneuroblastoma - mortality; Ganglioneuroblastoma - pathology; Ganglioneuroma - genetics; Ganglioneuroma - mortality; Ganglioneuroma - pathology; Humans; Infant; Kaplan-Meier Estimate; Male; Neoplasm Proteins - biosynthesis; Neoplasm Proteins - genetics; neuroblastoma; Neuroblastoma - genetics; Neuroblastoma - mortality; Neuroblastoma - pathology; predictive oncology; Prognosis; Proportional Hazards Models; pyrosequencing; Risk; Risk Assessment; Sequence Analysis, DNA; Soft Tissue Neoplasms - genetics; Soft Tissue Neoplasms - mortality; Soft Tissue Neoplasms - pathology; Survivors - statistics & numerical data
• ISSN: 0020-7136; 1097-0215
• DOI: 10.1002/ijc.24768

The aim of our study was to identify threshold levels of DNA methylation predictive of the outcome to better define the risk group of stage 4 neuroblastic tumor patients. Quantitative pyrosequencing analysis was applied to a training set of 50 stage 4, high risk patients and to a validation cohort of 72 consecutive patients. Stage 4 patients at lower risk and ganglioneuroma patients were included as control groups. Predictive thresholds of methylation were identified by ROC curve analysis. The prognostic end points of the study were the overall and progression‐free survival at 60 months. Data were analyzed with the Cox proportional hazard model. In a multivariate model the methylation threshold identified for the SFN gene (14.3.3σ) distinguished the patients presenting favorable outcome from those with progressing disease, independently from all known predictors (Training set: Overall Survival HR 8.53, p = 0.001; Validation set: HR 4.07, p = 0.008). The level of methylation in the tumors of high‐risk patients surviving more than 60 months was comparable to that of tumors derived from lower risk patients and to that of benign ganglioneuroma. Methylation above the threshold level was associated with reduced SFN expression in comparison with samples below the threshold. Quantitative methylation is a promising tool to predict survival in neuroblastic tumor patients. Our results lead to the hypothesis that a subset of patients considered at high risk—but displaying low levels of methylation—could be assigned at a lower risk group.