Gene Expression Profiling, Frozen and Paraffin Section Immunohistochemistry, and In Situ Hybridization for Determination of Monoclonality in Diffuse Large B-Cell Lymphoma.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 4553-4553
Author(s):  
Matthew W. Andres ◽  
Robin A. Roberts ◽  
Debbie J. Mustacich ◽  
Randy D. Gascoyne ◽  
Deborah A. Fuchs ◽  
...  

Abstract Background: Determining monotypia of surface immunoglobulin (SIg) is often an important step in the diagnosis of B-cell lymphomas. Many competing methods have been developed and are commonly used in clinical practice. The role of gene expression profiling (GEP) in determining light chain restriction is yet to be clarified. The goal of this study was to compare 4 methods by which light chain restriction can be determined: frozen section immunohistochemistry (FS-IHC), paraffin section IHC (PS-IHC), in-situ hybridization (ISH), and GEP. Design: 40 cases of DLBCL, part of a previous GEP study of DLBCL (Rosenwald et al, NEJM 2002), were made into a tissue microarray (TMA). FS-IHC slides, previously stained using by-hand streptavidin and diaminobenzidine, were re-examined for κ:λ restriction. PS-IHC was done on the TMA using the Benchmark system according to manufacturer’s protocols for κ/λ staining (Ventana Medical Systems VMSI, Tucson, AZ). ISH was performed on the TMA with a newly developed sensitive ISH procedure from VMSI which uses a purified streptavidin reagent to reduce background and increase sensitivity. The FS-IHC, PS-IHC, and ISH arrays were reviewed and scored as κ/λ monotypic, SIg-negative or indeterminate by 3 pathologists. The averaged gene expression ratios for microarray elements probing for κ and λ on each case were plotted on a log2 scale. Monoclonality was determined using 2 different GEP criteria: (1) κ-monoclonal if κ:λ expression was >2log2 or λ-monoclonal if expression was λ>κ or (2) κ and λ light chain relative expression on either side of the median. These data from all 4 techniques were used to determine a consensus clonality in which the majority of the results agreed. The results for each technique were then compared to the consensus for that case. Results: 7 Cases had a 4/4 consensus, 9 cases a 3/4, 11 cases a 3/3, 7 cases a 2/3, and 1 case a 2/2. 5 cases were excluded from the study because there was no majority consensus. 19 cases (47.5%) were κ monoclonal, 10 (25%) λ monoclonal, 6 (15%) SIg-negative, and 5 cases (12.5%) indeterminate. Compared to the consensus clonality FS-IHC was accurate in 21/26 (81%), PS-IHC in 28/32 (87%), sensitive ISH in 29/29 (100%) cases. GEP was accurate in 31/35 (89%) cases using either criteria (1) or (2); in 27/35 (77%) using criterion (1) alone, in 28/35 (80%) using criterion (2) alone, and 24/35 (69%) of cases when both criteria (1) and (2) were met. 6 SIg-negative cases failed all GEP criterion, but were considered correctly classified as neitherκ nor λ monoclonal. Discussion: The technique with the highest accuracy compared to consensus was the sensitive ISH assay, in part because samples were eliminated if the mRNA control (polyT probe) staining was suboptimal. GEP was also accurate using either of our criteria. The SIg-negative cases were not classified as either κ or λ monoclonal using any of our criteria. Given the increasing role GEP is likely to play in hematopathology, the application of GEP to B cell clonality may have diganostic utility.

2006 ◽  
Vol 130 (4) ◽  
pp. 483-520 ◽  
Author(s):  
Cherie H. Dunphy

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.


2019 ◽  
Vol 152 (Supplement_1) ◽  
pp. S109-S109
Author(s):  
Michael Franklin ◽  
Chelsey Deel ◽  
Mohammad Vasef

Abstract Objectives Evaluation of light chain restriction is critical to establish clonality in B-cell lymphoproliferative disorders (LPDs). Immunohistochemistry (IHC) and in situ hybridization (ISH) are commonly used to assess light chain restriction in formalin-fixed, paraffin-embedded (FFPE) tissues. However, except for cases with plasma cell differentiation, these techniques often fail to identify immunoglobulin light chains. An ultrasensitive technique, RNAscope, has been recently introduced that can identify light chains in cases of B-cell LPDs. We analyzed the utility of this ultrasensitive method in detection of clonality and correlated with flow cytometry results when available. Methods A tissue microarray was constructed using 1.6-mm diameter tissue punches of 31 FFPE tissue blocks from 27 cases that were previously characterized as marginal zone lymphoma (MZL) by a combination of morphology, IHC, and/or flow cytometry. Cases included 8 nodal and 19 extranodal MZLs. In two cases, additional blocks were included to assess reproducibility. For ultrasensitive ISH RNAscope assay, 4-µm thickness tissue sections were hybridized using kappa and lambda probes, incubated overnight, counterstained with hematoxylin, cover-slipped, and reviewed blindly without knowledge of prior flow cytometry results. Results Of 18 cases with evaluable staining, 15 were clonal and 3 were polytypic. Flow cytometry was available in 14 of these 18 cases with concordance in 13 of 14 (93%). The discordant case was polytypic by flow cytometry but kappa restricted by RNAscope. The false-negative flow results could be due to sampling issues. In six cases, staining failed and could not be evaluated. Conclusion Ultrasensitive RNAscope is a reliable assay in the detection of clonality in FFPE tissue, particularly where fresh tissue is not available for flow cytometry. In addition, our results confirm and further expand prior observations that RNAscope is a highly sensitive and specific assay with high concordance with flow cytometry.


Author(s):  
David W. Scott

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.


Blood ◽  
2011 ◽  
Vol 117 (18) ◽  
pp. 4836-4843 ◽  
Author(s):  
Gonzalo Gutiérrez-García ◽  
Teresa Cardesa-Salzmann ◽  
Fina Climent ◽  
Eva González-Barca ◽  
Santiago Mercadal ◽  
...  

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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