scholarly journals Subtyping Diffuse Large B-Cell Lymphoma with Cell-of-Origin Using 32-Gene Expression Assay in Formalin-Fixed Paraffin-Embedded Tissue

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 5337-5337
Author(s):  
Xiangnan Jiang ◽  
Wanhui Yan ◽  
Yifeng Sun ◽  
Qinghua Xu ◽  
Xiaoyan Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Gold Standard ◽  
B Cell Lymphoma ◽  
Global Gene Expression ◽  
Rna Seq ◽  
Gene Assay ◽  
Global Gene Expression Profiling

Introduction Diffuse large B-cell lymphoma (DLBCL) is a group of heterogeneous disease with distinct molecular subtypes. The most established subtyping algorithm, the Cell-of-Origin (COO) model, categorizes DLBCL into activated B-cell (ABC) and germinal center B-cell (GCB)-like subgroups through gene expression profiling. COO subtyping is mandatory for every newly diagnosed DLBCL patients, as it is critical for determining the therapeutic and surveillance strategies. We evaluated a newly developed assay using 32-gene expression profiling to determine the COO of DLBCL with formalin-fixed paraffin-embedded (FFPE) tissue. Methods The DLBCL-COO Test is a qPCR-based 32-gene expression assay for COO determination in FFPE samples. Biopsy of DLBCL patients with paired FFPE and fresh tissue were identified to assign COO, based on the immunohistochemistry (IHC) algorithm (Han's algorithm), DLBCL-COO qPCR assay and global gene expression profiling with RNA-seq, respectively. The global gene expression profiling with RNA-seq was taken as the "gold standard" for reference. Clinical information including the survival data were collected. Results 160 cases of DLBCL with evaluable COO assignments with IHC, DLBCL-COO 32-gene assay and global gene expression profiling with RNA-seq were identified. Comparing with the 77.5% concordance between IHC algorithm and gold standard, there is 91.9% concordance between DLBCL-COO 32-gene assay and gold standard (P =0.005). 72 patients assigned as ABC subtype and 14 patients assigned as Type-3 subtype demonstrated a significantly inferior overall survival than 42 patients assigned as GCB subtype using DLBCL-COO assay (P =0.023). However, COO based the IHC algorithm failed to provide the predictive value regarding overall survival (P =0.09). Conclusions DLBCL-COO assay provides flexibility and accuracy in DLBCL subtype characterization. These subtype distinctions should help guide disease prognosis and treatment options within DLBCL clinical practice. Disclosures Sun: Canhelp Genomics: Employment. Xu:Canhelp Genomics: Employment.

Global gene expression profiling of porcine endometria on Days 12 and 16 of the estrous cycle and pregnancy

2014 ◽  
Vol 82 (6) ◽  
pp. 897-909 ◽  
Author(s):  
Jolanta Kiewisz ◽  
Kamil Krawczynski ◽  
Pawel Lisowski ◽  
Agnieszka Blitek ◽  
Lech Zwierzchowski ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Estrous Cycle ◽  
Expression Profiling ◽  
Global Gene Expression ◽  
Global Gene Expression Profiling

Gene Expression Profiling Data in Lymphoma and Leukemia: Review of the Literature and Extrapolation of Pertinent Clinical Applications

2006 ◽  
Vol 130 (4) ◽  
pp. 483-520 ◽  
Author(s):  
Cherie H. Dunphy
Keyword(s):  
Gene Expression ◽  
Acute Lymphoblastic Leukemia ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Hodgkin Lymphoma ◽  
Expression Profiling ◽  
Myeloid Leukemia ◽  
Lymphoblastic Leukemia ◽  
B Cell Lymphoma ◽  
Clinical Applications

Abstract Context.—Gene expression (GE) analyses using microarrays have become an important part of biomedical and clinical research in hematolymphoid malignancies. However, the methods are time-consuming and costly for routine clinical practice. Objectives.—To review the literature regarding GE data that may provide important information regarding pathogenesis and that may be extrapolated for use in diagnosing and prognosticating lymphomas and leukemias; to present GE findings in Hodgkin and non-Hodgkin lymphomas, acute leukemias, and chronic myeloid leukemia in detail; and to summarize the practical clinical applications in tables that are referenced throughout the text. Data Source.—PubMed was searched for pertinent literature from 1993 to 2005. Conclusions.—Gene expression profiling of lymphomas and leukemias aids in the diagnosis and prognostication of these diseases. The extrapolation of these findings to more timely, efficient, and cost-effective methods, such as flow cytometry and immunohistochemistry, results in better diagnostic tools to manage the diseases. Flow cytometric and immunohistochemical applications of the information gained from GE profiling assist in the management of chronic lymphocytic leukemia, other low-grade B-cell non-Hodgkin lymphomas and leukemias, diffuse large B-cell lymphoma, nodular lymphocyte–predominant Hodgkin lymphoma, and classic Hodgkin lymphoma. For practical clinical use, GE profiling of precursor B acute lymphoblastic leukemia, precursor T acute lymphoblastic leukemia, and acute myeloid leukemia has supported most of the information that has been obtained by cytogenetic and molecular studies (except for the identification of FLT3 mutations for molecular analysis), but extrapolation of the analyses leaves much to be gained based on the GE profiling data.

Cell-of-Origin in Diffuse Large B-Cell Lymphoma: Are the Assays Ready for the Clinic?

2015 ◽  
pp. e458-e466 ◽  
Author(s):  
David W. Scott
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Practical Implementation ◽  
Cell Of Origin ◽  
Large B Cell Lymphoma ◽  
Large B Cell

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma worldwide and consists of a heterogeneous group of cancers classified together on the basis of shared morphology, immunophenotype, and aggressive clinical behavior. It is now recognized that this malignancy comprises at least two distinct molecular subtypes identified by gene expression profiling: the activated B-cell-like (ABC) and the germinal center B-cell-like (GCB) groups—the cell-of-origin (COO) classification. These two groups have different genetic mutation landscapes, pathobiology, and outcomes following treatment. Evidence is accumulating that novel agents have selective activity in one or the other COO group, making COO a predictive biomarker. Thus, there is now a pressing need for accurate and robust methods to assign COO, to support clinical trials, and ultimately guide treatment decisions for patients. The “gold standard” methods for COO are based on gene expression profiling (GEP) of RNA from fresh frozen tissue using microarray technology, which is an impractical solution when formalin-fixed paraffin-embedded tissue (FFPET) biopsies are the standard diagnostic material. This review outlines the history of the COO classification before examining the practical implementation of COO assays applicable to FFPET biopsies. The immunohistochemistry (IHC)-based algorithms and gene expression–based assays suitable for the highly degraded RNA from FFPET are discussed. Finally, the technical and practical challenges that still need to be addressed are outlined before robust gene expression–based assays are used in the routine management of patients with DLBCL.

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