A Highly Multiplexed PCR Platform for Gene Expression Profiling from FFPE Tissue

描述（由申请人提供）：本申请的总体目标是提供一种高度多重、定量和自动化的系统，用于使用福尔马林固定石蜡包埋（FFPE）材料作为样本来源快速鉴定弥漫性大B细胞淋巴瘤（DLBCL）亚组;这是一种尚未用于研究和临床社区的技术。DLBCL占所有非霍奇金淋巴瘤的约30%，因此是美国这种癌症最常见的亚型。虽然许多患者对治疗反应良好，但仍有相当大的一部分患者难以治疗或复发。基因表达谱分析表明，这种反应差异反映在肿瘤的生物学中，基于肿瘤细胞的起源定义了两个亚组。一组17个基因内的分子特征可以区分这些亚组。检测基因表达模式的技术目前主要集中在两种现有的形式：微阵列和实时PCR。前者虽然能够检测数百至数千个基因，但缺乏灵敏度和定量能力，而PCR虽然定量且非常灵敏，但具有极其有限的多重能力。因此，迫切需要将多路复用的联合收割机属性与灵敏的定量分析相结合的技术，以促进对肿瘤生物学的理解，从而转化为临床诊断实用性。档案 FFPE肿瘤代表了转化癌症基因组研究的宝贵资源。然而，利用FFPE组织是具有挑战性的，因为它通常来源于含有在固定和储存期间片段化的RNA的小活检，因此使其不太适合微阵列分析。因此，缺乏能够利用FFPE作为用于遗传分析的组织来源的定量、多重、灵敏和robus测定。 为了克服上述障碍，我们提出开发一种新的、快速的、自动化的检测方法来检测、定量和分类DLBCL的两种主要亚型，从而促进肿瘤类型的及时诊断，以便为临床治疗方案提供信息。这样一种技术，可以检测到 并使用FFPE样本作为源材料在单管反应中定量多个基因靶的方法目前还不存在。 本提案的目标将通过完成三个具体目标来实现。这些包括：（i）通过采用PrimeraDx的新兴星星技术和ICEclase仪器系统开发技术，称为“ICEclase多重FFPE测定”;（ii）验证所得测定的分析性能特征;以及（iii）通过进行一致性研究，将新开发的检测方法的结果与参考微阵列技术进行比较，验证检测方法的性能目前用于DLBCL子分型。 公共卫生相关性：在过去的十年中，随着肿瘤基因表达谱分析的兴起，癌症诊断发生了重大转变，这导致了癌症检测，诊断和治疗的改进。然而，为了实现这一方法的全部潜力，需要克服技术障碍，包括在一次检测中可以检测到的基因数量以及使用可能降解的储存组织样本。PrimeraDx将通过为储存的肿瘤组织材料的单反应、多样本分析提供自动化解决方案来解决这些问题，以便对类型进行分类 的一个共同的人类淋巴瘤，从而促进快速诊断，治疗方案的决定，并分析对治疗的反应。

DESCRIPTION (provided by applicant): The overall goal of this application is to deliver a highly multiplexed, quantitative, and automated system for the rapid identification of diffuse large B-cell lymphoma (DLBCL) subgroups using formalin-fixed paraffin-embedded (FFPE) material as the sample source; a technology that is not yet available to the research and clinical communities. DLBCL accounts for ~30% of all non-Hodgkin lymphomas and thus is the most common subtype of this cancer in the United States. While many patients respond well to treatment, there is a sizable subset that remains refractory or suffers relapse. Gene expression profiling has revealed that this difference in response is reflected in the biology of the tumor an two subgroups have been defined based on the origin of the tumor cell. Molecular signatures within a panel of 17 genes can differentiate these subgroups. Technologies to detect gene expression patterns currently center around two existing formats: microarrays and real-time PCR. The former, although able to detect hundreds to thousands of genes, suffer from their lack of sensitivity and quantitative capacity, while PCR, although quantitative and exceedingly sensitive, has extremely limited multiplexing capability. Therefore, technologies that combine attributes of multiplexing with sensitive, quantitative analysis are critically needed to advance the understanding of tumor biology toward translation into clinical diagnostic utility. Archives of FFPE tumors represent a valuable resource for translational cancer genomic research. However, utilizing FFPE tissue is challenging since it is often derived from small biopsies containing RNA that is fragmented during fixation and storage, thus rendering it less suitable for microarray analysis. As a result there is a lack of quantitative, multiplexed, sensitive, and robus assays that are able to utilize FFPE as a source of tissue for genetic analysis. In order to overcome these above obstacles we propose to develop a novel, rapid, and automated assay to detect, quantify, and classify the two main subtypes of DLBCL, thus facilitating timely diagnosis of the tumor type in order to inform clinical treatment options. Such a technology, that can detect and quantify multiple gene targets in a single-tube reaction using FFPE specimens as the source material, does not currently exist. The objective of this proposal will be met by completing three Specific Aims. These consist of (i) developing the technology, to be termed the 'ICEPlex Multiplex FFPE Assay', by adapting PrimeraDx's emerging STAR technology and ICEPlex instrument system for this purpose; (ii) validating the analytical performance characteristics of the resultant assay; and (iii) verifying performance of the assay by conducting a concordance study comparing results from the newly developed assay with a reference microarray technology currently used for DLBCL subtyping. PUBLIC HEALTH RELEVANCE: The past decade has seen a major shift in cancer diagnostics with the ascendance of gene expression profile analysis of tumors, which is leading to improvements in cancer detection, diagnosis, and treatment. However, to achieve the full potential of this approach, technology impediments involving the number of genes that can be detected in a single assay and the use of stored tissue samples that may be degraded need to be overcome. PrimeraDx will address these problems by providing an automated solution for a single-reaction, multi-sample analysis from stored tumor tissue material in order to classify types of a common human lymphoma, thereby facilitating rapid diagnosis, determination of treatment options, and analysis of response to therapy.