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Typing the Transcriptome in Cancer Using Splicing Array

Typing the Transcriptome in Cancer Using Splicing Array
使用剪接阵列对癌症转录组进行分型
批准号:
7067622
负责人:
XIANG-DONG FU
金额:
$48.48万
依托单位国家:
美国
项目类别:
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-06-01 至 2008-05-31

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DESCRIPTION (provided by applicant): Alternative splicing is a permanent feature in higher eukaryotic cells and understanding of how alternative splicing alters the composition and function of the proteome represents a major challenge in the post-genome era. For cancer research, unique mRNA isoforms may provide a robust set of biomarkers for diagnosis and prognosis, and cancer-specific mRNA isoforms may serve as discriminating targets for effective therapeutic interventions. Furthermore, understanding of how splice choice is made and regulated in development and disease is a fundamental issue in cancer cell biology. An mRNA isoform-sensitive microarray technology would be ideally and timely suited for addressing a wide range of clinical and mechanistic questions regarding alternative splicing. In the past IMAT funding period, we have developed a unique and novel technology platform to attack the splicing problem. After a systematic and substantial effort in database construction and experimental development, the technology is now matured, and its superiority in reproducible measurement of mRNA isoforms under a variety of conditions has been demonstrated. Unique to the splicing array is the need to progressively enlarge the database for accurately annotated mRNA isoforms and preparation of corresponding oligo sets for measurement. We are therefore seeking IMAT support to put the technology in practical use and let the research community to take advantage of the technology development. We have three specific goals for the next phase in applying the emerging technology for molecular analysis of cancer. (1) We plan to use the technology to identify unique mRNA isoforms associated with prostate cancer. We will survey existing prostate cancer cell lines untreated or treated with androgen and estrogen as well as cancer tissues at different malignant stages to identify tumor-specific and hormonal regulated alternative splicing. (2) We propose to apply the technology to address mechanisms of splicing regulation by identifying direct targets for a large number of splicing regulators in knockdown and knockout cells. (3) Along with the proposed technology applications, we will progressively enlarge the high quantity databases coupled with the technology development and continue to improve and enlarge the database by adding new features and functions and develop linked software for splicing array data analysis.
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