Michels Evi, Vandesompele Jo, De Preter Katleen, Hoebeeck Jasmien, Vermeulen Joëlle, Schramm Alexander, Molenaar Jan J, Menten Björn, Marques Barbara, Stallings Raymond L, Combaret Valérie, Devalck Christine, De Paepe Anne, Versteeg Rogier, Eggert Angelika, Laureys Geneviève, Van Roy Nadine, Speleman Frank
Center for Medical Genetics, Ghent University Hospital, Ghent, Belgium.
Genes Chromosomes Cancer. 2007 Dec;46(12):1098-108. doi: 10.1002/gcc.20496.
High-resolution array comparative genomic hybridization (arrayCGH) profiling was performed on 75 primary tumors and 29 cell lines to gain further insight into the genetic heterogeneity of neuroblastoma and to refine genomic subclassification. Using a novel data-mining strategy, three major and two minor genomic subclasses were delineated. Eighty-three percent of tumors could be assigned to the three major genomic subclasses, corresponding to the three known clinically and biologically relevant subsets in neuroblastoma. The remaining subclasses represented (1) tumors with no/few copy number alterations or an atypical pattern of aberrations and (2) tumors with 11q13 amplification. Inspection of individual arrayCGH profiles showed that recurrent genomic imbalances were not exclusively associated with a specific subclass. Of particular notice were tumors with numerical imbalances typically observed in subtype 1 neuroblastoma, in association with genomic features of subtype 2A or 2B. A search for prognostically relevant genomic alterations disclosed 1q gain as a predictive marker for therapy failure within the group of subtype 2A and 2B tumors. In cell lines, a high incidence of 6q loss was observed, with a 3.87-5.32 Mb region of common loss within 6q25.1-6q25.2. Our study clearly illustrates the importance of genomic profiling in relation to tumor behavior in neuroblastoma. We propose that genome-wide assessment of copy number alterations should ideally be included in the genetic workup of neuroblastoma. Further multicentric studies on large tumor series are warranted in order to improve therapeutic stratification in conjunction with other features such as age at diagnosis, tumor stage, and gene expression signatures.
对75例原发性肿瘤和29个细胞系进行了高分辨率阵列比较基因组杂交(arrayCGH)分析,以进一步深入了解神经母细胞瘤的基因异质性并完善基因组亚分类。采用一种新颖的数据挖掘策略,划定了三个主要和两个次要的基因组亚类。83%的肿瘤可归入这三个主要基因组亚类,它们分别对应于神经母细胞瘤中三个已知的临床和生物学相关亚组。其余亚类包括:(1)无/少量拷贝数改变或畸变模式不典型的肿瘤;(2)有11q13扩增的肿瘤。对单个arrayCGH图谱的检查显示,复发性基因组失衡并非仅与特定亚类相关。特别值得注意的是,具有通常在1型神经母细胞瘤中观察到的数字失衡的肿瘤,同时伴有2A或2B型的基因组特征。对预后相关基因组改变的搜索发现,1q增益是2A和2B型肿瘤组中治疗失败的预测标志物。在细胞系中,观察到6q缺失的发生率很高,在6q25.1 - 6q25.2区域内有一个3.87 - 5.32 Mb的共同缺失区域。我们的研究清楚地说明了基因组分析对于神经母细胞瘤肿瘤行为的重要性。我们建议,在神经母细胞瘤的基因检查中,理想情况下应包括全基因组拷贝数改变评估。有必要进一步开展针对大型肿瘤系列的多中心研究,以便结合其他特征(如诊断时的年龄、肿瘤分期和基因表达特征)来改善治疗分层。