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

描述（由申请人提供）：我们已经开发了一种称为基因识别标记对末端双标签（GIS-PET）的新技术，其精确捕获并连接文库中任何克隆插入物的5'和3'端最多18个碱基对。所得的“双标签”是文库内任何cDNA或基因组片段的边界的标记。当与先进的测序技术相结合时，GIS-PET可以比当代克隆和测序快300-500倍且更便宜地注释整个转录组。我们已经捕获了MCF-7乳腺癌细胞系的转录组快照至> 500，000全长cDNA当量，并且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，其中一个基因的开始与另一个基因的结束融合。这些融合转录物是癌症特异性的，可以作为生物标志物，作为治疗效果的监测器，以及作为新疗法的靶点。因此，我们建议在原发性乳腺癌上扩展和验证该技术，并确认在MCF-7细胞系中已经鉴定的候选融合转录物的重要列表。我们将克隆和测序所有这些技术可以获得的融合转录本，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相关。我们还建议将GIS-PET技术优化到基因组DNA，以定位癌细胞中基因组重排的精确位置。 当放在一起时，该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，所以我们将此申请作为R33提交。 与公共卫生的相关性：癌症是一种遗传性疾病，对癌症遗传异常的了解已被证明可以发现新的生物标志物和疾病管理中的新治疗方法。我们已经开发出一种新技术，可以绘制出癌细胞中所有重要异常重排的后果。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.