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Quantitative RT-PCR: Prediction Lymphoma Transformation

Quantitative RT-PCR: Prediction Lymphoma Transformation
定量 RT-PCR:预测淋巴瘤转化
批准号:
6884253
负责人:
KOJO S. J. ELENITOBA-JOHNSON
金额:
$10.0万
依托单位:
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:
2005-03-01 至 2006-09-01

项目摘要

项目成果

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中文摘要
翻译
描述(由申请人提供):人类基因组的完成和表达谱的出现使得对不同疾病状态的转录特征的全面表征成为可能。基于荧光定量实时聚合酶链反应的方法已成为分子诊断的有力工具,因为它们结合了非凡的定量动态范围和优越的特异性。尽管实时荧光定量技术取得了显著进展,但该技术尚未广泛应用于固定石蜡包埋组织的基因表达分析,这是活检材料存档的最常见方式。在这个快速通道申请的R41阶段,我们将建立一种简单的方法来定量RT-PCR对来自福尔马林固定石蜡包埋组织的RNA的性能。该技术的优势在于它简单,与短扩增子的PCR设计兼容,而不影响目标特异性。在本项目的R41阶段结束时,我们将建立定量实时RT-PCR方法对来自福尔马林固定石蜡包埋组织材料的RNA的可行性,可重复性和稳健性。这些研究将作为基因表达谱研究的基础,评估先前确定的一组约30个基因的预测能力,以预测滤泡性淋巴瘤向侵袭性大b细胞淋巴瘤的转变。
英文摘要
DESCRIPTION (provided by applicant): Completion of the human genome and the advent of expression profiling have permitted comprehensive characterization of the transcriptional signatures of different disease states. Quantitative fluorescent real-time polymerase chain reaction-based methods have emerged as a powerful tool in molecular diagnostics as they combine extraordinary dynamic range of quantification and superior specificity. Despite the remarkable advances in real-time fluorescence quantification techniques, this technique has yet to gain widespread application in the analysis of gene expression fixed paraffin-embedded tissues, which is the most common way in which biopsy material is archived. In the R41 phase of this fast-track application, we will establish the utility of a simple approach to the performance of quantitative RT-PCR on RNA derived from formalin-fixed paraffinembedded tissue. The technique is advantageous in that it is simple and compatible with the design of PCR for short amplicons, without compromising target specificity. By the end of the R41 phase of this project, we would have established the feasibility, reproducibility and robustness of our quantitative real-time RT-PCR approach on RNA derived from formalin-fixed paraffin embedded tissue material. These studies will serve as the foundation for the gene expression profiling studies evaluating the predictive power of a previously identified set of ~30 genes to predict the transformation of follicular lymphoma to an aggressive large B-cell lymphoma in phase II.
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