Epigenetic studies in rhabdomyosarcoma

横纹肌肉瘤的表观遗传学研究

• 批准号: 8553174
• 负责人: Frederic Barr
• 金额: $ 51.06万
• 依托单位: DIVISION OF BASIC SCIENCES - NCI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8553174
• 关键词: Age; Algorithms; Bioinformatics; Biological Assay; Biotin; Bone Marrow; Categories; Cell Line; Cells; Chromatin; Computer software; CpG dinucleotide; Cytosine; DNA; DNA Sequence; Data; Development; Epigenetic Process; Faculty; Family; Future; Genes; Genomics; Glycerol; Goals; Human; Human Genome; Human Resources; Hypermethylation; In Vitro; Individual; Label; Laboratories; Laboratory Research; Malignant Neoplasms; Measurement; Measures; Methodology; Methods; Methylation; Normal tissue morphology; Nucleic Acid Regulatory Sequences; PAX3 gene; PAX7 gene; Pennsylvania; Pilot Projects; Preparation; Procedures; Reaction; Recruitment Activity; Relative (related person); Research Personnel; Rhabdomyosarcoma; Sampling; Scientist; Series; Site; Skeletal Muscle; Specificity; Specimen; Subgroup; Temperature; Testing; Tumor Cell Line; Universities; Uracil; Work; base; bisulfite; cohort; design; interest; research study; tumor

The Senior Investigator moved to the NCI during FY2011 and hired personnel to set up a research laboratory during the first half of FY2012. A Staff Scientist was recruited in November 2011, and this individual initially helped to set up the laboratory; this scientist then began working on this RMS methylation project in March 2012. The staff scientist applied bioinformatic strategies to the methylation data from the first set of RMS tumors to identify genes that are differentially methylated between fusion-positive ARMS and fusion-negative ERMS tumors. Supervised analysis algorithms were used to compare mean methylation levels for each gene in the fusion-negative and fusion-positive tumors, and then to determine those genes whose mean methylation levels were significantly different between the two groups of tumors. As there were greater than 27,000 comparisons, corrections were made for multiple comparisons. Genes were found for which there was both evidence of hypermethylation in ARMS and hypomethylation in ERMS, and other genes were found for which there was evidence of hypomethylation in ARMS and hypermethylation in ERMS. As each methylation measurement applies to a single CpG site, confidence and interest increased when the relationship was found for more than one CpG in the same gene. Our next goal was to validate the differential methylation of selected genes by determining the methylation status of the larger CpG-containing regulatory region in fusion-negative and positive RMS tumors. Based on some trial experiments, it was clear that we needed to optimize methodology in our laboratory to accurately measure gene-specific methylation levels in tumor samples. We initially used RMS tumor cell lines to work out this methodology and then we will subsequently use DNA from RMS specimens in our later analyses. Our goal was to treat genomic DNA with bisulfite, amplify selected CpG containing regions, and then characterize the methylation status of this region by pyrosequencing. We determined that one of several commercially available kits for controlled bisulfite treatment of genomic DNA efficiently converts all cytosines to uracil. In previous studies, using in vitro methylated genomic DNA controls, we also confirmed that the bisulfite treatment from these kits does not modify methylated cytosines. Therefore, we can confidently use this bisulfite procedure to modify the sequence of DNA in a methylation-specific fashion. To amplify the selected regions, there were several considerations in our design of PCR primers and the subsequent PCR reaction. First, the sequence of the region was not the native sequence but the modified sequence after bisulfite treatment. The sequences of interest were the CpG-rich regulatory regions including the CpG's of interest identified in the Illumina array. However, it should be emphasized that we select flanking primers that do not contain CpG dinucleotides and thus do not have a variable sequence dependent on methylation status. Of the available algorithms for selecting primers, we determined that Methyl Primer Express software (Applied Biosystems) was useful in selecting robust primer pairs. In addition to the gene specific sequences in the primer, we also determined the utility of adding tags on the 5' ends of the forward and reverse primers (such as M13 forward and reverse primer sequences). These tags permit a second nested step if the first PCR results in a low yield of product. In addition, a single common biotin-labeled M13 forward primer can be used to isolate the single stranded product from the double stranded PCR products in preparation for the pyrosequencing studies. Once the PCR primers were selected, we looked for optimal reaction conditions, particularly for these high-CpG-containing regions. In particular, we found that addition of BSA and glycerol to the reaction conditions permitted increased specificity by allowing use of higher annealing temperatures during cycling. Based on these various parameters, we have amplified CpG-containing regions for several differentially methylated genes from a series of fusion-negative and positive RMS cells lines, and are now commencing pyrosequencing analysis to determine the C:T ration at cytosines within CpG dinucleotides and thereby determining the methylation status of these sites within the larger CpG-containing region.

高级研究员于2011财政年度转往NCI，并于2012财政年度上半年聘请人员设立研究实验室。2011年11月招募了一名科学家，这名科学家最初帮助建立了实验室;这名科学家随后于2012年3月开始从事RMS甲基化项目。研究人员将生物信息学策略应用于第一组RMS肿瘤的甲基化数据，以识别融合阳性ARMS和融合阴性ERMS肿瘤之间差异甲基化的基因。使用监督分析算法比较融合阴性和融合阳性肿瘤中每个基因的平均甲基化水平，然后确定两组肿瘤之间平均甲基化水平显著不同的基因。由于比较次数超过27，000次，因此对多重比较进行了校正。发现了在ARMS中存在高甲基化证据和在ERMS中存在低甲基化证据的基因，并且发现了在ARMS中存在低甲基化证据和在ERMS中存在高甲基化证据的其他基因。由于每个甲基化测量适用于单个CpG位点，因此当在同一基因中发现多于一个CpG的关系时，置信度和兴趣增加。我们的下一个目标是通过确定融合阴性和阳性RMS肿瘤中较大的含CpG调控区的甲基化状态来验证所选基因的差异甲基化。基于一些试验实验，很明显，我们需要优化我们实验室的方法，以准确测量肿瘤样本中的基因特异性甲基化水平。我们最初使用RMS肿瘤细胞系来制定这种方法，然后我们将随后使用RMS标本的DNA进行后续分析。我们的目标是用亚硫酸氢盐处理基因组DNA，扩增选定的含CpG的区域，然后通过焦磷酸测序来表征该区域的甲基化状态。我们确定了用于基因组DNA的受控亚硫酸氢盐处理的几种市售试剂盒中的一种有效地将所有胞嘧啶转化为尿嘧啶。在先前的研究中，使用体外甲基化基因组DNA对照，我们还证实了来自这些试剂盒的亚硫酸氢盐处理不会修饰甲基化胞嘧啶。因此，我们可以自信地使用这种亚硫酸氢盐程序以甲基化特异性方式修饰DNA序列。为了扩增选定的区域，在我们设计PCR引物和随后的PCR反应中有几个考虑因素。首先，该区域的序列不是天然序列，而是亚硫酸氢盐处理后的修饰序列。感兴趣的序列是富含CpG的调控区，包括在Illumina阵列中鉴定的感兴趣的CpG。然而，应该强调的是，我们选择的侧翼引物不含CpG二核苷酸，因此不具有依赖于甲基化状态的可变序列。在用于选择引物的可用算法中，我们确定甲基引物表达软件（Applied Biosystems）可用于选择稳健的引物对。除了引物中的基因特异性序列之外，我们还确定了在正向和反向引物（例如M13正向和反向引物序列）的5'端添加标签的效用。如果第一次PCR导致产物产量低，则这些标签允许第二次嵌套步骤。此外，在焦磷酸测序研究的准备中，可以使用单个普通生物素标记的M13正向引物从双链PCR产物中分离单链产物。一旦选择了PCR引物，我们就寻找最佳反应条件，特别是对于这些高CpG含量的区域。特别是，我们发现，添加BSA和甘油的反应条件允许增加的特异性，允许使用更高的退火温度在循环过程中。基于这些不同的参数，我们已经扩增了几个差异甲基化基因的CpG含有区域从一系列融合阴性和阳性RMS细胞系，现在开始焦磷酸测序分析，以确定C：T比率在胞嘧啶内的CpG二核苷酸，从而确定这些网站内的更大的CpG含有区域的甲基化状态。