Integrated genome, transcriptome and translatome profiling of neuroblastoma cells

Microarray-based genome-wide measurements of copy number alterations and of transcriptome variations are proposed for neuroblastoma prognosis and possible treatment choice. Nonetheless, they lack to provide clues on a neglected layer of systems-level changes, the translatome, whose variations are defined by the activity of the translational regulatory machinery. Our study extends the conventional genome-wide approaches to translatome profiling in neuroblastoma, by means of polysomal sucrose gradient separation followed by microarray analysis. The panel of fourteen parental (not subcloned) neuroblastoma cell lines used in the study includes: CHP-134, SIMA, NB-69, LAN-1, KELLY, CHP-126, CHP-212, SK-N-BE(2), IMR-32, SK-N-AS, SK-N-SH, STA-NB-7, STA-NB-1, STA-NB-10 cells. Each cell line has been profiled with high resolution array CGH analysis for copy number changes, and for transcriptome and translatome variations. The integration of these three types of data sets obtained from the same cells can provide information on the impact in neuroblastoma of a defined pattern of genomic lesions on both transcriptional and translational alterations of gene expression. We analyzed the following human neuroblastoma cell lines: STA-NB-1, SK-N-AS, NB-69, KELLY, LAN-1, CHP-134, SK-N-SH, SK-N-BE(2), STA-NB-7, CHP-126, CHP-212, IMR-32, SIMA, STA-NB-10.

基于微阵列（microarray）的全基因组拷贝数变异与转录组变化检测，曾被应用于神经母细胞瘤的预后评估与潜在治疗方案筛选。然而此类检测手段无法揭示被忽视的系统层面调控维度——翻译组（translatome），其变化特征由翻译调控机器的活性所决定。
本研究通过多聚核糖体蔗糖梯度分离结合微阵列分析的技术路径，将传统全基因组检测方法拓展至神经母细胞瘤的翻译组谱分析领域。
本研究使用的14株亲本（未经过亚克隆）神经母细胞瘤细胞系涵盖：CHP-134、SIMA、NB-69、LAN-1、KELLY、CHP-126、CHP-212、SK-N-BE(2)、IMR-32、SK-N-AS、SK-N-SH、STA-NB-7、STA-NB-1、STA-NB-10细胞。所有细胞系均通过高分辨率阵列比较基因组杂交（array CGH）分析，完成了拷贝数变异、转录组及翻译组变化的谱学检测。
整合自同一细胞株的这三类数据集，可用于解析特定基因组损伤模式对基因表达的转录与翻译调控改变在神经母细胞瘤发生发展中的影响。
本研究分析的人源神经母细胞瘤细胞系如下：STA-NB-1、SK-N-AS、NB-69、KELLY、LAN-1、CHP-134、SK-N-SH、SK-N-BE(2)、STA-NB-7、CHP-126、CHP-212、IMR-32、SIMA、STA-NB-10。