Research Project
8432665
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.
