The value of gene expression profiling by DNA microarray analysis in prognostication of diffuse large B-cell lymphomas reaffirmed in a large study

2002 ◽  
Vol 9 (6) ◽  
pp. 371
Author(s):  
John K.C. Chan
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Microarray Analysis ◽  
Dna Microarray ◽  
Expression Profiling ◽  
Large Study ◽  
B Cell Lymphomas ◽  
Dna Microarray Analysis ◽  
Large B Cell

Gene expression profiling of diffuse large B-Cell lymphomas supervised by CD5 expression

2015 ◽  
Vol 102 (2) ◽  
pp. 188-194 ◽  
Author(s):  
Kana Miyazaki ◽  
Motoko Yamaguchi ◽  
Hiroshi Imai ◽  
Kyoko Kobayashi ◽  
Satoshi Tamaru ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
B Cell Lymphomas ◽  
Large B Cell

scholarly journals Gene expression profiling using DNA microarray analysis of the cerebellum of mice treated with methylmercury

2011 ◽  
Vol 36 (3) ◽  
pp. 389-391 ◽  
Author(s):  
Gi-Wook Hwang ◽  
Jin-Yong Lee ◽  
Katsunori Ryoke ◽  
Fujio Matsuyama ◽  
Jong-Mu Kim ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Microarray Analysis ◽  
Dna Microarray ◽  
Expression Profiling ◽  
Dna Microarray Analysis

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.

Gene-expression profiling and not immunophenotypic algorithms predicts prognosis in patients with diffuse large B-cell lymphoma treated with immunochemotherapy

Blood ◽  
2011 ◽  
Vol 117 (18) ◽  
pp. 4836-4843 ◽  
Author(s):  
Gonzalo Gutiérrez-García ◽  
Teresa Cardesa-Salzmann ◽  
Fina Climent ◽  
Eva González-Barca ◽  
Santiago Mercadal ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Progression Free Survival ◽  
B Cell Lymphoma ◽  
Tissue Microarrays ◽  
Prognostic Impact ◽  
Germinal Center B Cell ◽  
Large B Cell

Abstract Diffuse large B-cell lymphomas (DLBCLs) can be divided into germinal-center B cell–like (GCB) and activated-B cell–like (ABC) subtypes by gene-expression profiling (GEP), with the latter showing a poorer outcome. Although this classification can be mimicked by different immunostaining algorithms, their reliability is the object of controversy. We constructed tissue microarrays with samples of 157 DLBCL patients homogeneously treated with immunochemotherapy to apply the following algorithms: Colomo (MUM1/IRF4, CD10, and BCL6 antigens), Hans (CD10, BCL6, and MUM1/IRF4), Muris (CD10 and MUM1/IRF4 plus BCL2), Choi (GCET1, MUM1/IRF4, CD10, FOXP1, and BCL6), and Tally (CD10, GCET1, MUM1/IRF4, FOXP1, and LMO2). GEP information was available in 62 cases. The proportion of misclassified cases by immunohistochemistry compared with GEP was higher when defining the GCB subset: 41%, 48%, 30%, 60%, and 40% for Colomo, Hans, Muris, Choi, and Tally, respectively. Whereas the GEP groups showed significantly different 5-year progression-free survival (76% vs 31% for GCB and activated DLBCL) and overall survival (80% vs 45%), none of the immunostaining algorithms was able to retain the prognostic impact of the groups (GCB vs non-GCB). In conclusion, stratification based on immunostaining algorithms should be used with caution in guiding therapy, even in clinical trials.

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