Standardized NanoArray PCR for Gene Expression Profiling of Lung Cancer

描述(由申请人提供)：癌症的分子特征，特别是通过基因转录图谱，在改善预后、治疗选择和临床结果方面具有巨大的潜力。然而，由于缺乏易于部署的检测试剂盒，缺乏常规临床使用所需的准确性、低RNA要求和位点间一致性，阻碍了将表达特征用于癌症预后和治疗选择的潜力。我们提出了一种创新的解决方案，基于两种经过充分验证的聚合酶链式反应技术，这两种技术的结合独特地解决了诊断分析的重复性问题。我们的计划是在Biotrove Inc.开发的新型纳米流体聚合酶链式反应平台中实施标准化RT(START)-聚合酶链式反应，这是托莱多大学开发的一种成熟的竞争性聚合酶链式反应方法，目的是简化流体工作流程，提高测量吞吐量，同时降低测试成本并保持低RNA投入。与现有的杂交或实时定量聚合酶链式反应方法相比，标准化纳米阵列聚合酶链式反应(SNAP)将提供与RT-PCR相同的动态范围和质量，但需要更少的RNA输入，并且更易于临床部署。这一发展将需要逐步整合经过验证的技术。首先，将建立16个肺癌预后基因的实时荧光定量聚合酶链式反应TaqMan分析。这些分析将通过创建竞争模板和竞争对手特定的染料标记探针而转换为Start-PCR。在START-PCR中增加一个预扩增步骤将减少RNA输入要求，从而使每个样本能够进行数千次测试。最后，将化验结果移入OpenArray Nano-PCR板将简化液体处理。使用从肺部临床肿瘤切除组织中提取的RNA，该集成平台将展示与实时qPCR相当的动态范围和精度。在初始开发阶段完成后，我们将在两个关键的基因表达谱实验中比较SNAP和实时qPCR。首先，我们将通过监测精密度的损失作为减少RNA样本投入的函数来比较每种方法所需的最小RNA量。其次，我们将通过测量三个实验室的七个肺肿瘤切除样本的基因表达谱，展示较低的位置间变异性，这是可部署性的关键因素。满足这些特定目标将导致寻求进一步的资金，用于多点预后验证研究，涉及具有广泛临床病史的福尔马林固定、石蜡包埋(FFPE)肺标本。

DESCRIPTION (provided by applicant): Molecular characterization of cancer, in particular by gene transcription profiling, has great potential to improve prognosis, therapeutic selection and clinical outcomes. However, the potential for using expression signatures for cancer prognosis and treatment selection is hampered by lack of readily deployable test kits with the accuracy, low RNA requirement and inter-site concordance required for routine clinical use. We propose an innovative solution based on two well-validated PCR technologies whose combination uniquely addresses the problem of diagnostic assay reproducibility. Our plan is to implement Standardized RT (StaRT)-PCR, a proven competitive PCR method developed at the University of Toledo, in a novel nanofluidic PCR platform developed by BioTrove Inc. in order to streamline the fluidic workflow, improve measurement throughput, and at the same time reduce test cost and maintain low RNA input. As compared to existing hybridization or real-time qPCR approaches, Standardized NanoArray PCR (SNAP) will provide the same dynamic range and quality as RT-PCR, yet require less RNA input and be more readily clinically deployable. The development will entail step-wise integration of proven technologies. First, real-time qPCR TaqMan assays will be developed for 16 lung tumor prognostic genes. These assays will be converted to StaRT-PCR by creation of competitive template and a competitor specific dye-labeled probe. Adding a pre-amplification step to StaRT-PCR will reduce the RNA input requirements to enable thousands of tests per sample. Finally, moving the assays into the OpenArray nano-PCR plate will streamline fluid handling. Using RNA isolated from lung clinical tumor resections, dynamic range and precision equivalent to real-time qPCR will be demonstrated for the integrated platform. After the initial development phase is complete, we will compare SNAP and real time qPCR in two critical gene expression profiling experiments. First we will compare the minimum amount of RNA required for each method by monitoring loss of precision as a function of decreasing RNA sample input. Second we will demonstrate lower inter-site variability, a critical factor for deploy-ability, by measuring gene expression profiles of seven lung tumor resection samples in three laboratories. Meeting these Specific Aims will lead to seeking further funding for multi-site prognostic validation studies involving formalin-fixed, paraffin-embedded (FFPE) lung specimens with extensive clinical history.