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中文摘要
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描述(由申请人提供):本申请的总体目标是招募最新可用的基因组技术,如细菌人工染色体(BAC)文库制备,人类基因组成品序列,以及454生命科学公司在抗癌方面开发的下一代测序技术。本应用程序旨在开发条形码标记池基因组索引(BT-PGI)方法,用于高度复用的基于bac的癌症染色体畸变定位。BT-PGI方法结合了两种多路复用——PGI方法对BAC克隆进行池化和新开发的454测序技术对短可映射序列标签进行并行测序,从而实现了吞吐量和分辨率。从成熟的MCF-7乳腺癌细胞系中获得的市售BAC文库将用于测试和验证这些方法。在MCF-7中检测到的特定重排将在其他乳腺癌细胞系和乳腺癌组织中进行测量。这些重排的生物学功能将通过永生化和转化乳腺上皮细胞的克隆和表达进行测试。生物分析将取决于重排或断点的兴趣,但将集中在增殖,生存,入侵和转化。对染色体重排的进一步了解将为绘制癌症进展、了解相关分子机制、确定知情治疗的生物标志物以及确定乳腺癌和其他肿瘤的治疗干预靶点提供新的机会。
英文摘要
DESCRIPTION (provided by applicant): The general aim of the present application is to recruit newly available genomic technologies such as Bacterial Artificial Chromosome (BAC) library preparations, finished sequence of the human genome, and next- generation sequencing technologies developed by the 454 Life Sciences Corporation in the fight against cancer. This application aims to develop the Barcoded Tag Pooled Genomic Indexing (BT-PGI) method for highly multiplexed BAC-based mapping of chromosomal aberrations in cancer. The BT-PGI method achieves throughput and resolution by combining two types of multiplexing -- the pooling of BAC clones by the PGI method and the parallel sequencing of short mappable sequence tags by the newly developed 454 sequencing technology. A commercially available BAC library obtained from the well-established MCF-7 breast cancer cell line will be used for'testing and validation of these methods. Specific rearrangements detected in MCF-7 will then be measured in other breast cancer cell lines, and in breast cancer tissue. The biological function of these rearrangements will be tested by cloning and expression in both immortalized and transformed breast epithelial cells. Biological assays will depend upon the rearrangement or breakpoints of interest, but will focus on proliferation, survival, invasion and transformation. The improved understanding of chromosomal rearrangements will open new opportunities for charting the progression of cancer, understanding relevant molecular mechanisms, identifying biomarkers for informed therapy, and identifying targets for therapeutic intervention in breast cancer and other tumors.
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Bioinformatics Section
  • 批准号:
    10471391
  • 项目类别:
  • 资助金额:
    $60.97万
  • 财政年份:
    2020
  • 负责人:
    Aleksandar Milosavljevic
  • 依托单位:
Bioinformatics Section
  • 批准号:
    10259807
  • 项目类别:
  • 资助金额:
    $60.97万
  • 财政年份:
    2020
  • 负责人:
    Aleksandar Milosavljevic
  • 依托单位:
Bioinformatics Section
  • 批准号:
    10670780
  • 项目类别:
  • 资助金额:
    $51.01万
  • 财政年份:
    2020
  • 负责人:
    Aleksandar Milosavljevic
  • 依托单位:
GENOMIC INDEXING OF COMMON FUND DATASETS
  • 批准号:
    10907970
  • 项目类别:
  • 资助金额:
    $115.25万
  • 财政年份:
    2020
  • 负责人:
    Aleksandar Milosavljevic
  • 依托单位:
海外基金