scholarly journals DNA methylation signatures define molecular subtypes of diffuse large B-cell lymphoma

Blood ◽  
2010 ◽  
Vol 116 (20) ◽  
pp. e81-e89 ◽  
Author(s):  
Rita Shaknovich ◽  
Huimin Geng ◽  
Nathalie A. Johnson ◽  
Lucas Tsikitas ◽  
Leandro Cerchietti ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
B Cell ◽  
Expression Profiling ◽  
B Cell Lymphoma ◽  
Genetic Alterations ◽  
Integrated Analysis ◽  
Germinal Center B Cell ◽  
Factor Α ◽  
Large B Cell

Abstract Expression profiling has shown 2 main and clinically distinct subtypes of diffuse large B-cell lymphomas (DLBCLs): germinal-center B cell–like (GCB) and activated B cell–like (ABC) DLBCLs. Further work has shown that these subtypes are partially characterized by distinct genetic alterations and different survival. Here, we show with the use of an assay that measures DNA methylation levels of 50 000 CpG motifs distributed among more than 14 000 promoters that these 2 DLBCL subtypes are also characterized by distinct epigenetic profiles. DNA methylation and gene expression profiling were performed on a cohort of 69 patients with DLBCL. After assigning ABC or GCB labels with a Bayesian expression classifier trained on an independent dataset, a supervised analysis identified 311 differentially methylated probe sets (263 unique genes) between ABC and GCB DLBCLs. Integrated analysis of methylation and gene expression showed a core tumor necrosis factor-α signaling pathway as the principal differentially perturbed gene network. Sixteen genes overlapped between the core ABC/GCB methylation and expression signatures and encoded important proteins such as IKZF1. This reduced gene set was an accurate predictor of ABC and GCB subtypes. Collectively, the data suggest that epigenetic patterning contributes to the ABC and GCB DLBCL phenotypes and could serve as useful biomarker.

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.

scholarly journals Differential efficacy of bortezomib plus chemotherapy within molecular subtypes of diffuse large B-cell lymphoma

Blood ◽  
2009 ◽  
Vol 113 (24) ◽  
pp. 6069-6076 ◽  
Author(s):  
Kieron Dunleavy ◽  
Stefania Pittaluga ◽  
Myron S. Czuczman ◽  
Sandeep S. Dave ◽  
George Wright ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Molecular Subtypes ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Large B Cell Lymphoma ◽  
Germinal Center B Cell ◽  
Large B Cell

Abstract Gene expression profiling of diffuse large B-cell lymphoma (DLBCL) has revealed distinct molecular subtypes that include germinal center B cell–like (GCB) and activated B cell–like (ABC) DLBCL. ABC DLBCL has a worse survival after upfront chemotherapy and is characterized by constitutive activation of the antiapoptotic nuclear factor–kappa B (NF-κB) pathway, which can inhibit chemotherapy. We hypothesized that inhibition of NF-κB might sensitize ABC but not GCB DLBCL to chemotherapy and improve outcome. As the proteasome inhibitor bortezomib can inhibit NF-κB through blocking IκBα degradation, we investigated bortezomib alone followed by bortezomib and doxorubicin-based chemotherapy in recurrent DLBCL. Tumor tissue was analyzed by gene expression profiling and/or immunohistochemistry to identify molecular DLBCL subtypes. As a control, we showed that relapsed/refractory ABC and GCB DLBCL have equally poor survivals after upfront chemotherapy. Bortezomib alone had no activity in DLBCL, but when combined with chemotherapy, it demonstrated a significantly higher response (83% vs 13%; P < .001) and median overall survival (10.8 vs 3.4 months; P = .003) in ABC compared with GCB DLBCL, respectively. These results suggest bortezomib enhances the activity of chemotherapy in ABC but not GCB DLBCL, and provide a rational therapeutic approach based on genetically distinct DLBCL subtypes. This trial is registered with http://www.ClinicalTrials.gov under identifier NCT00057902.

scholarly journals Gene expression profiling-based risk prediction and profiles of immune infiltration in diffuse large B-cell lymphoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Selin Merdan ◽  
Kritika Subramanian ◽  
Turgay Ayer ◽  
Johan Van Weyenbergh ◽  
Andres Chang ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
B Cell ◽  
Risk Prediction ◽  
Expression Profiling ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Gene Signatures ◽  
Large B Cell Lymphoma ◽  
Large B Cell

AbstractThe clinical risk stratification of diffuse large B-cell lymphoma (DLBCL) relies on the International Prognostic Index (IPI) for the identification of high-risk disease. Recent studies suggest that the immune microenvironment plays a role in treatment response prediction and survival in DLBCL. This study developed a risk prediction model and evaluated the model’s biological implications in association with the estimated profiles of immune infiltration. Gene-expression profiling of 718 patients with DLBCL was done, for which RNA sequencing data and clinical covariates were obtained from Reddy et al. (2017). Using unsupervised and supervised machine learning methods to identify survival-associated gene signatures, a multivariable model of survival was constructed. Tumor-infiltrating immune cell compositions were enumerated using CIBERSORT deconvolution analysis. A four gene-signature-based score was developed that separated patients into high- and low-risk groups. The combination of the gene-expression-based score with the IPI improved the discrimination on the validation and complete sets. The gene signatures were successfully validated with the deconvolution output. Correlating the deconvolution findings with the gene signatures and risk score, CD8+ T-cells and naïve CD4+ T-cells were associated with favorable prognosis. By analyzing the gene-expression data with a systematic approach, a risk prediction model that outperforms the existing risk assessment methods was developed and validated.

scholarly journals Genome-wide DNA methylation and RNA-seq analyses identify genes and pathways associated with doxorubicin resistance in a canine diffuse large B-cell lymphoma cell line

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0250013
Author(s):  
Chia-Hsin Hsu ◽  
Hirotaka Tomiyasu ◽  
Chi-Hsun Liao ◽  
Chen-Si Lin
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
B Cell ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Rna Seq ◽  
Doxorubicin Resistance ◽  
Large B Cell Lymphoma ◽  
Genome Wide ◽  
Large B Cell

Doxorubicin resistance is a major challenge in the successful treatment of canine diffuse large B-cell lymphoma (cDLBCL). In the present study, MethylCap-seq and RNA-seq were performed to characterize the genome-wide DNA methylation and differential gene expression patterns respectively in CLBL-1 8.0, a doxorubicin-resistant cDLBCL cell line, and in CLBL-1 as control, to investigate the underlying mechanisms of doxorubicin resistance in cDLBCL. A total of 20289 hypermethylated differentially methylated regions (DMRs) were detected. Among these, 1339 hypermethylated DMRs were in promoter regions, of which 24 genes showed an inverse correlation between methylation and gene expression. These 24 genes were involved in cell migration, according to gene ontology (GO) analysis. Also, 12855 hypermethylated DMRs were in gene-body regions. Among these, 353 genes showed a positive correlation between methylation and gene expression. Functional analysis of these 353 genes highlighted that TGF-β and lysosome-mediated signal pathways are significantly associated with the drug resistance of CLBL-1. The tumorigenic role of TGF-β signaling pathway in CLBL-1 8.0 was further validated by treating the cells with a TGF-β inhibitor(s) to show the increased chemo-sensitivity and intracellular doxorubicin accumulation, as well as decreased p-glycoprotein expression. In summary, the present study performed an integrative analysis of DNA methylation and gene expression in CLBL-1 8.0 and CLBL-1. The candidate genes and pathways identified in this study hold potential promise for overcoming doxorubicin resistance in cDLBCL.

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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