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首页> 外文期刊>BMC Medical Genomics >Identification of transcriptional regulatory networks specific to pilocytic astrocytoma
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Identification of transcriptional regulatory networks specific to pilocytic astrocytoma

机译：鉴定特定于细胞性星形细胞瘤的转录调控网络

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Background Pilocytic Astrocytomas (PAs) are common low-grade central nervous system malignancies for which few recurrent and specific genetic alterations have been identified. In an effort to better understand the molecular biology underlying the pathogenesis of these pediatric brain tumors, we performed higher-order transcriptional network analysis of a large gene expression dataset to identify gene regulatory pathways that are specific to this tumor type, relative to other, more aggressive glial or histologically distinct brain tumours. Methods RNA derived from frozen human PA tumours was subjected to microarray-based gene expression profiling, using Affymetrix U133Plus2 GeneChip microarrays. This data set was compared to similar data sets previously generated from non-malignant human brain tissue and other brain tumour types, after appropriate normalization. Results In this study, we examined gene expression in 66 PA tumors compared to 15 non-malignant cortical brain tissues, and identified 792 genes that demonstrated consistent differential expression between independent sets of PA and non-malignant specimens. From this entire 792 gene set, we used the previously described PAP tool to assemble a core transcriptional regulatory network composed of 6 transcription factor genes (TFs) and 24 target genes, for a total of 55 interactions. A similar analysis of oligodendroglioma and glioblastoma multiforme (GBM) gene expression data sets identified distinct, but overlapping, networks. Most importantly, comparison of each of the brain tumor type-specific networks revealed a network unique to PA that included repressed expression of ONECUT2, a gene frequently methylated in other tumor types, and 13 other uniquely predicted TF-gene interactions. Conclusions These results suggest specific transcriptional pathways that may operate to create the unique molecular phenotype of PA and thus opportunities for corresponding targeted therapeutic intervention. Moreover, this study also demonstrates how integration of gene expression data with TF-gene and TF-TF interaction data is a powerful approach to generating testable hypotheses to better understand cell-type specific genetic programs relevant to cancer.
机译：背景上皮星形细胞瘤（PAs）是常见的低度中枢神经系统恶性肿瘤，对于这些恶性肿瘤，很少发现复发和特异性遗传改变。为了更好地了解这些小儿脑肿瘤发病机理的分子生物学，我们对大型基因表达数据集进行了高阶转录网络分析，以鉴定特定于该肿瘤类型的基因调控途径，相对于其他疾病，更多侵袭性神经胶质或组织学上不同的脑肿瘤。方法使用Affymetrix U133Plus2 GeneChip微阵列对来源于冰冻人PA肿瘤的RNA进行基于微阵列的基因表达谱分析。在适当归一化之后，将该数据集与先前从非恶性人脑组织和其他脑肿瘤类型生成的相似数据集进行比较。结果在这项研究中，我们检查了66种PA肿瘤中与15种非恶性皮层脑组织相比的基因表达，并鉴定了792个基因，这些基因在PA和非恶性标本的独立组之间表现出一致的差异表达。从整个792个基因集中，我们使用了先前描述的PAP工具组装了由6个转录因子基因（TF）和24个靶基因组成的核心转录调控网络，总共进行了55次相互作用。对少突胶质细胞瘤和多形胶质母细胞瘤（GBM）基因表达数据集的类似分析确定了不同但重叠的网络。最重要的是，对每种脑肿瘤类型特定网络的比较揭示了PA特有的网络，其中包括ONECUT2的表达受压，一种在其他肿瘤类型中经常甲基化的基因以及13种其他独特预测的TF基因相互作用。结论这些结果表明，特定的转录途径可能会产生PA的独特分子表型，从而为相应的靶向治疗提供了机会。此外，这项研究还证明了将基因表达数据与TF-基因和TF-TF相互作用数据进行整合是一种强大的方法，可用于生成可检验的假设，以更好地理解与癌症相关的细胞类型特异性遗传程序。

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