Nonlinear Models of mRNA Expression in Cancer by RT-PCR

RT-PCR 癌症中 mRNA 表达的非线性模型

• 批准号: 7500416
• 负责人: Terry HYSLOP
• 金额: $ 26.42万
• 依托单位: THOMAS JEFFERSON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-16 至 2010-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7500416
• 关键词: Accounting; Algorithms; Biological Assay; Biological Markers; Blood; Cancer Patient; Cause of Death; Characteristics; Clinical; Clinical Data; Clinical Trials; Code; Colorectal Cancer; Data; Dependence; Detection; Disease; Disease regression; Enrollment; Excision; Exhibits; Funding; Future; Goals; Guanylate Cyclase; Heterogeneity; Histopathology; Individual; Institution; Investigation; Kinetics; Laboratories; Malignant Neoplasms; Measurement; Measures; Messenger RNA; Methodology; Methods; Modeling; Molecular; Non-linear Models; Patients; Phase; Polymerase Chain Reaction; Positive Lymph Node; Procedures; Property; Range; Reaction; Recurrence; Recurrent disease; Reverse Transcriptase Polymerase Chain Reaction; Running; Sampling; Sensitivity and Specificity; Standards of Weights and Measures; Structure; Techniques; Technology; Testing; Time; Tissues; United States; Weight; base; cancer recurrence; design; improved; mRNA Expression; mortality; prognostic; prospective; quality assurance; research study; simulation

DESCRIPTION (provided by applicant): The overall goal of this project is to improve the data analytic procedures associated with quantitative real-time polymerase chain reaction (Q-RT-PCR), with particular focus on measuring mRNA expression of molecular biomarkers and their association with colorectal cancer. Colorectal cancer is the third most common malignancy in the United States, and the third most common cause of death among cancer-related mortalities. While resection therapy is the main course of treatment for these patients, over 50% of patients presumed cured will recur within three to five years. It is hypothesized that these recurrences are actually undetected micrometastases. We propose to adapt Q-RT-PCR technology by changing the methods to quantify the amount of mRNA expression based on nonlinear models of the kinetic reaction obtained from Q-RT-PCR experiments. The current approach to quantitation does not make use of most of the data from the kinetic RT-PCR reaction, and the assumptions of the current model do not match the reality of the experiments. Thus, we also propose extensions of the error structure of these models to account for serial dilution of samples, heterogeneity across concentrations, and dependence of replicate samples. It is our hypothesis that improved measurement of the quantity of molecular biomarkers will offer more accurate prognostic information for colorectal cancer patients. Data from two NCI funded multi-center trials of guanylyl-cyclase-C (GCC) are available for these studies to demonstrate the clinical utility of our proposed methods.

描述（由申请人提供）：本项目的总体目标是改进与定量实时聚合酶链反应（Q-RT-PCR）相关的数据分析程序，特别关注测量分子生物标志物的mRNA表达及其与结直肠癌的相关性。结直肠癌是美国第三常见的恶性肿瘤，也是癌症相关死亡中第三常见的死亡原因。虽然切除治疗是这些患者的主要治疗过程，但超过50%的假定治愈的患者将在三到五年内复发。据推测，这些复发实际上是未检测到的微转移。 我们建议根据Q-RT-PCR实验获得的动力学反应的非线性模型，通过改变量化mRNA表达量的方法来适应Q-RT-PCR技术。目前的定量方法没有利用来自动力学RT-PCR反应的大部分数据，并且当前模型的假设与实验的实际情况不匹配。因此，我们还提出了这些模型的误差结构的扩展，以考虑样品的连续稀释，浓度间的异质性和重复样品的依赖性。我们的假设是，改进的分子生物标志物的数量测量将为结直肠癌患者提供更准确的预后信息。来自NCI资助的鸟苷酸环化酶C（GCC）的两个多中心试验的数据可用于这些研究，以证明我们提出的方法的临床实用性。