Micro RNA Profiling in Pediatric Cancers

1. 确定作为儿科癌症良好生物标志物的microRNA谱。2. 鉴定作为预测预后的生物标志物的microRNA。3. 确定microRNA表达的基因组背景，以及它们如何与mRNA表达相关4。鉴定神经母细胞瘤中控制关键基因的基因组改变区域的mirna。5. 所选miRNAs的功能验证microrna是最近在植物和动物基因组中发现的小的、非编码的RNA分子。这些高度保守的21-mer rna通过结合特定mRNA的3'-非翻译区（3'-UTR）来调节基因的表达，导致翻译抑制或mRNA降解。由于许多mrna可能共享这个短序列，microrna能够同时影响大量基因的表达。据估计，每个microRNA可以靶向数百个基因，多个microRNA可以靶向单个基因。到目前为止，已经报道了710种microrna（版本11.0）在人类细胞中表达（http://microrna.sanger.ac.uk/）。由于其在基因表达中的调控作用，越来越多的证据表明，microrna不仅直接参与正常的胚胎发生、代谢、细胞生长、分化和凋亡，而且还参与人类癌症的发病。由于大多数儿童恶性肿瘤是发展性肿瘤，即它们是由异常分化产生的，我们假设儿童肿瘤将表现出可能与发展和成瘤过程相关的癌症和组织特异性microRNA表达谱，可用于诊断和预后。在这项研究中，我们研究了一组儿童细胞系和肿瘤异种移植物的microRNAs表达谱，这些mrna表达谱目前被用作儿童药物筛选的临床前模型。利用这组代表10种不同类型儿科肿瘤的样本，我们通过对内部microRNA阵列进行microRNA分析，探索儿科肿瘤是否根据其诊断差异表达microRNA。我们使用机器学习算法和统计学来识别可能用作这些癌症类型生物标志物的microrna。我们将在独立的NB和RMS肿瘤样本中验证这些发现。此外，我们还探讨了microrna与其所在宿主基因的共调控程度。我们也在研究与RMS具有生物学相关性并可作为预后标志物的关键microrna。

1. Identify microRNA profiles that are good biomarkers of pediatric cancers. 2. Identify microRNA that are biomarkers for predicting prognosis. 3. Identify genomic context of microRNA expression, and how they correlate with mRNA expression 4. Identify miRNAs in genomically altered regions that control critical genes in neuroblastoma. 5. Functional validation of selected miRNAs 6. Mutational screening of microRNAs MicroRNAs are recently discovered small, non-coding RNA molecules encoded in the genomes of plants and animals. These highly conserved, 21-mer RNAs regulate the expression of genes by binding to their 3'-untranslated regions (3'-UTR) of specific mRNAs, causing translational inhibition or mRNA degradation. As many mRNAs may share this short sequence, microRNAs are capable of simultaneously influence the expression of a large set of genes. It is estimated that each microRNA can target hundreds of genes, and multiple microRNAs can target a single gene. So far 710 microRNAs (version 11.0) have been reported to be expressed in human cells (http://microrna.sanger.ac.uk/). Due to their regulatory roles in gene expression, there is increasing evidence that microRNAs are directly involved not only in normal embryogenesis, metabolism, cell growth, differentiation, and apoptosis, but also in pathogenesis of human cancers. Because most pediatric malignancies are developmental tumors, i.e., they arise from aberrant differentiation, we hypothesized that pediatric tumors will exhibit cancer and tissue specific microRNA expression profiles that may be associated with development and the tumorigenic process, which can be used in diagnosis and prognosis. In this study we investigate the expression profiles of microRNAs for a panel of pediatric cell lines and tumor xenografts for which mRNAs profiles were, and which are currently used as pediatric pre-clinical models for drug screening. Using this panel of samples representing 10 different types of pediatric tumors we explore if pediatric tumors differentially express microRNAs according to their diagnosis by performing microRNA profiling on in-house microRNA arrays. We use machine learning algorithm and statistical to identify microRNAs that can potentially be used as biomarkers for these cancer types. We will validate these findings on independent NB and RMS tumor samples. In addition, we explore the degree of co-regulation of the microRNAs with the host gene within which they are located. We are also investigate key microRNAs that are biologically relevant and can be used as prognostic markers in RMS.