Semiparametric Methods for Efficiency-Adjusted Relative qRT-PCR Quantification

用于效率调整的相对 qRT-PCR 定量的半参数方法

基本信息

批准号：
8288712
负责人：
Inna Chervoneva
金额：
$ 16.86万
依托单位：
THOMAS JEFFERSON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-06-23 至 2014-05-31
项目状态：
已结题

项目摘要

Project Summary/Abstract Quantitative RT-PCR is widely used for molecular diagnostics and evaluating prognosis in cancer. While detection of biomarkers (presence vs. absent) is becoming a part of routing clinical practice, the actual quantification of tumor burden, for example, in lymph nodes or serum is still in developmental phase. In order for such actual quantification to become clinically useful, it is necessary to have in place data analysis methods that would provide high accuracy and precision of relative qRT-PCR quantification of low abundance transcripts across various equipment platforms and chemistries used for qRT-PCR assay. The overall goal of this project is to develop and validate new and universal methods of efficiency-adjusted relative qRT-PCR quantification that would be universally applicable to various qRT-PCR equipment platforms and chemistries. New quantification methods will be based on novel semiparametric models for qRT-PCR kinetic data that flexibly represent amplification history using smoothing splines and incorporate the model for dynamics of qRT-PCR efficiency through the penalty defined by suitable differential equation. The proposed studies will (1) investigate the utility of Michaelis-Menten model and its extensions for describing dynamics of qRT-PCR efficiency; (2) develop semi- parametric models for qRT-PCR kinetic data incorporating the dynamics of PCR efficiency using the profiled penalty estimation approach in functional data analysis; (3) develop new universal methods for efficiency-adjusted relative qRT-PCR quantification based on the proposed semi-parametric models; (4) compare accuracy and precision of the new and established methods using simulations and wide range of kinetic qRT-PCR data publicly available and collected during the course of two large NCI sponsored studies of GUYC2C in fresh tissue and blood from colorectal cancer patients.

项目摘要/摘要定量RT-PCR广泛用于分子诊断和评估预后在癌症中。虽然发现生物标志物（存在与不存在）正在成为路由临床实践，例如淋巴的实际定量肿瘤负担节点或血清仍处于发育阶段。为了进行实际量化在临床上有用，有必要使用数据分析方法将提供低精度和相对QRT-PCR的低精度跨各种设备平台和化学的丰度成绩单 QRT-PCR分析。该项目的总体目标是开发和验证新的和通用效率调整的相对QRT-PCR定量的方法将是普遍的适用于各种QRT-PCR设备平台和化学。新的量化方法将基于用于QRT-PCR动力学数据的新型半参数模型使用平滑花纹灵活地表示放大历史记录，并结合 QRT-PCR效率动态的模型通过适当定义的惩罚模型微分方程。拟议的研究将（1）研究Michaelis-Menten模型的实用性及其扩展用于描述QRT-PCR效率的动力学；（2）发展半 QRT-PCR动力学数据的参数模型包含PCR的动力学在功能数据分析中使用概述的惩罚估计方法的效率；（3）开发新的通用方法，用于效率调整的相对QRT-PCR定量基于提议的半参数模型；（4）比较准确性和精度使用模拟和各种动力学QRT-PCR的新方法和已建立的方法在两个大型NCI赞助的过程中，公开可用并收集了数据对结直肠癌患者的新鲜组织和血液中Guyc2c的研究。