Semiparametric Methods for Efficiency-Adjusted Relative qRT-PCR Quantification

描述(申请人提供)：定量RT-PCR被广泛用于癌症的分子诊断和预后评估。虽然生物标记物的检测(有无)正在成为常规临床实践的一部分，但对肿瘤负担的实际量化，例如，在淋巴结或血清中，仍处于发展阶段。为了使这种实际的定量方法在临床上有用，有必要建立数据分析方法，以提供跨用于qRT-PCR分析的各种设备平台和化学试剂的低丰度转录物的相对qRT-PCR定量的高准确度和精密度。该项目的总体目标是开发和验证新的、通用的效率调整的相对qRT-PCR定量方法，该方法将普遍适用于各种qRT-PCR设备、平台和化学物质。新的定量方法将基于新的qRT-PCR动力学数据的半参数模型，该模型使用平滑的样条线灵活地表示扩增历史，并通过适当的微分方程式定义的惩罚来结合qRT-PCR效率的动力学模型。所提出的研究将(1)探讨Michaelis-Menten模型及其扩展在描述qRT-PCR效率动力学方面的实用性；(2)利用功能数据分析中的轮廓惩罚估计法，为qRT-PCR动力学数据开发包含效率动态的半参数模型；(3)基于所提出的半参数模型，开发效率调整相对qRT-PCR定量的新的通用方法；(4)使用NCI赞助的两个大型结直肠癌患者新鲜组织和血液中GUYC2C的大型研究过程中公开获得的模拟和广泛的动力学qRT-PCR数据，比较新方法和已建立的方法的准确性和精密度。 公共卫生相关性：定量RT-PCR现在被广泛用于癌症的分子诊断和预后评估。虽然生物标记物的检测(有无)正在成为常规临床实践的一部分，但实际量化(拷贝数估计)肿瘤负担的方法仍然需要改进。该项目的总体目标是开发和验证新的和通用的低表达癌症生物标志物的实际相对qRT-PCR定量方法，这些方法将普遍适用于各种qRT-PCR设备、平台和化学设备。

DESCRIPTION (provided by applicant): 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. PUBLIC HEALTH RELEVANCE: Quantitative RT-PCR is now 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 methods for actual quantification (estimation of copy number) of tumor burden still need improvement. The overall goal of this project is to develop and validate new and universal methods of actual relative qRT-PCR quantification of low expression cancer biomarkers that would be universally applicable to various qRT-PCR equipment platforms and chemistries.