Pair-end-ditag technologies for the complete annotation of fusion genes

描述(申请人提供)：我们开发了一种名为基因识别签名对-END-diTag(GIS-PET)的新技术，它可以精确捕获并连接文库中任何克隆插入的5‘和3’最大18个碱基对。由此产生的“双标记”是文库中任何cdna或基因组片段的边界的签名。当与先进的测序技术相结合时，地理信息系统-PET可以比当代克隆和测序快300-500倍并以更低的成本对整个转录组进行注释。我们已经捕获了MCF-7乳腺癌细胞系的转录组快照，并以前所未有的分辨率捕获了该乳腺癌细胞系的转录组状态。通过这种方法，我们发现我们可以再次精确地识别候选融合转录本，其中一个基因的开头与另一个基因的结尾融合在一起。这些融合转录本是癌症特异性的，可以作为生物标记物、治疗效果的监测和新疗法的靶点。因此，我们建议扩大和验证这项技术在原发性乳腺癌上的应用，并确认已经在MCF-7细胞系中发现的候选融合转录本的重要列表。我们将克隆和测序这些技术可以获得的所有融合转录本，并评估它们在原发性乳腺癌中的存在是否与癌症行为和临床结果有关。我们还建议优化基因组DNA的GIS-PET技术，以便绘制出癌细胞中基因组重排的精确位置。当结合在一起时，这项技术的综合力量可以揭示任何癌症基因组的完整重排图谱。因为我们已经使这项技术超越了概念化，所以我们将这一申请作为R33提交。 与公众健康相关：癌症是一种遗传性疾病，对癌症中遗传异常的了解已被证明在疾病管理中发现了新的生物标记物和新的治疗方法。我们已经开发了一项新技术，可以绘制出癌细胞中所有重要异常重排的后果图。我们建议完善这项技术，并将其应用于人类乳腺癌组织。

DESCRIPTION (provided by applicant): We have developed a new technology called Gene Identification Signature Pair-end-diTag (GIS-PET), which captures precisely and joins the 5' and 3' most 18 base pair of any clone insert in a library. The resultant "ditags" are signatures of the boundaries of any cDNA or genomic fragment within the library. When coupled with advanced sequencing technologies, GIS-PET can annotate an entire transcriptome 300-500 fold faster and less expensively than contemporary cloning and sequencing. We have captured the transcriptome snapshot of the MCF-7 breast cancer cell line to >500,000 full length cDNA equivalents and have captured the state of the transcriptome of this breast cancer cell line with unprecedented resolution. With this approach, we found that we can identify, again with precision, candidate fusion transcripts where the beginning of one gene is fused with the end of another. These fusion transcripts are cancer-specific and can function as biomarkers, as monitors of treatment effect, and as targets for new therapeutics. We therefore propose to expand and validate this technology on primary breast cancers and to confirm the significant list of candidate fusion transcripts already identified in the MCF-7 cell line. We will clone and sequence all the fusion transcripts accessible to these technologies and will assess if their presence in primary breast cancers is associated with cancer behavior and clinical outcome. We also propose to optimize the GIS-PET technology to genomic DNA so as to map the precise location of genomic rearrangements in cancer cells. When put together, the combined power of the technology can uncover the complete rearrangement map of any cancer genome. Because we have brought this technology beyond conceptualization, we are submitting this application as an R33. Relevance to public health: Cancer is a genetic disease and the understanding of the genetic abnormalities in cancer has been shown to uncover new biomarkers and new treatments in the management of the disease. We have developed a new technology that can map the consequences of all the important abnormal rearrangements in a cancer cell. We propose to perfect this technology and to apply it to human breast cancer tissues.