Nonlinear Models of mRNA Expression in Cancer by RT-PCR

描述（由申请人提供）：该项目的总体目标是改进定量实时聚合酶链反应（Q-RT-PCR）相关的数据分析程序，特别关注分子生物标志物mRNA表达的测量及其与结直肠癌的关系。结直肠癌是美国第三大最常见的恶性肿瘤，也是癌症相关死亡的第三大常见原因。虽然切除治疗是这些患者的主要治疗方案，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被发现的微转移。我们建议采用Q-RT-PCR技术，改变基于非线性动力学模型的定量mRNA表达量的方法。目前的定量方法并没有利用动力学RT-PCR反应的大部分数据，而且目前模型的假设与实验的现实不匹配。因此，我们还建议扩展这些模型的误差结构，以考虑样品的连续稀释、浓度的异质性和重复样本的依赖性。我们的假设是，改进分子生物标志物数量的测量将为结直肠癌患者提供更准确的预后信息。来自NCI资助的两项多中心胍基环化酶-c （GCC）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。

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.