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

用于融合基因完整注释的双末端双标签技术

• 批准号: 7496388
• 负责人: Edison Tak-Bun Liu
• 金额: $ 38.51万
• 依托单位: GENOME INSTITUTE OF SINGAPORE
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-13 至 2010-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7496388
• 关键词: Bacterial Artificial Chromosomes; Base Pairing; Behavior; Biological Markers; Breast Cancer Cell; Cancer Etiology; Cancer cell line; Cell Line; Clinical; Cloning; Complementary DNA; Coupled; DNA; DNA Sequence Rearrangement; Diagnostic; Disease Management; Epithelial; Frequencies; Gene Expression Profile; Generations; Genes; Genomics; Goals; Guilt; Hereditary Disease; Human; Individual; Lead; Length; Libraries; Location; MCF7 cell; Malignant Neoplasms; Maps; Methods; Molecular Abnormality; Monitor; Oncogene Proteins; Outcome; Polymerase Chain Reaction; Principal Investigator; Public Health; Purpose; Range; Recurrence; Resolution; Reverse Transcriptase Polymerase Chain Reaction; Sampling; Source; Technology; Testing; Therapeutic; Tissues; Transcript; Validation; cDNA Library; cancer cell; cancer genome; clinically relevant; cost effective; disease phenotype; fusion gene; gene discovery; malignant breast neoplasm; new technology; novel; novel therapeutics; programs; treatment effect

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.

描述（由申请人提供）：我们开发了一种称为基因识别签名对末端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片段的5'和3'最18个碱基对。所得的“双标签”是文库内任何 cDNA 或基因组片段边界的标记。与先进的测序技术相结合，GIS-PET 注释整个转录组的速度比当代克隆和测序快 300-500 倍，而且成本更低。我们已经捕获了 MCF-7 乳腺癌细胞系的转录组快照，其全长 cDNA 当量超过 500,000 个，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。这些融合转录本具有癌症特异性，可以作为生物标志物、治疗效果的监测器以及新疗法的靶标。因此，我们建议在原发性乳腺癌上扩展和验证这项技术，并确认 MCF-7 细胞系中已鉴定的候选融合转录本的重要列表。我们将克隆和测序所有可利用这些技术的融合转录本，并将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。我们还建议优化基因组DNA的GIS-PET技术，以绘制癌细胞中基因组重排的精确位置。 当整合在一起时，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。因为我们已经使这项技术超越了概念化，所以我们将此应用程序作为 R33 提交。 与公共卫生的相关性：癌症是一种遗传疾病，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治疗该疾病的新疗法。我们开发了一种新技术，可以绘制癌细胞中所有重要的异常重排的后果。我们建议完善这项技术并将其应用于人类乳腺癌组织。