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Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers

机译:神经母细胞瘤的全基因组启动子甲基化分析可鉴定预后甲基化生物标志物

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摘要

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.
机译:准确预测神经母细胞瘤的预后仍然是一项挑战,这对于实现风险相关疗法的最佳选择是必要的。为了改善神经母细胞瘤患者的分层,本研究旨在确定预后肿瘤DNA甲基化生物标志物。结果:为了鉴定启动子甲基化沉默的基因,我们首先对八种神经母细胞瘤细胞系应用了两种独立的全基因组甲基化筛选方法。具体而言,我们使用甲基CpG结合域(MBD-seq)捕获后,对5-氮杂2'-脱氧胞苷(DAC)处理和大规模并行测序进行了重新表达谱分析。通过文献检索和针对20种原发性神经母细胞瘤肿瘤的前期甲基化特异性PCR,以及通过MBD-seq结合公开的神经母细胞瘤肿瘤基因表达数据,从DAC上调的基因中选择推定的甲基化标记。这产生了43种候选生物标志物,随后通过高通量甲基化特异性PCR在89个原发性神经母细胞瘤肿瘤的独立队列中进行了测试,这些肿瘤已被选择用于风险分类和生存。基于该分析,发现KRT19,FAS,PRPH,CNR1,QPCT,HIST1H3C,ACSS3和GRB10的甲基化与至少一种经典危险因素有关,即年龄,阶段或MYCN状态。重要的是,HIST1H3C和GNAS甲基化与总体生存和/或无事件生存有关。结论:本研究结合了两种全基因组甲基化发现方法,是迄今为止对神经母细胞瘤进行的最广泛的验证研究。我们确定了几种新型的预后DNA甲基化标志物,并为神经母细胞瘤中基于DNA甲基化的预后分类器的发展提供了基础。

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