Reliable subtype classification of diffuse large B-Cell lymphoma samples from GELA LNH2003 trials using the Lymph2Cx gene expression assay (original) (raw)
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Leukemia, 2012
Gene expression profiling (GEP) has stratified diffuse large B-cell lymphoma (DLBCL) into molecular subgroups that correspond to different stages of lymphocyte development-namely germinal center B-cell-like and activated B-cell-like. This classification has prognostic significance, but GEP is expensive and not readily applicable into daily practice, which has lead to immunohistochemical algorithms proposed as a surrogate for GEP analysis. We assembled tissue microarrays from 475 de novo DLBCL patients who were treated with rituximab-CHOP chemotherapy. All cases were successfully profiled by GEP on formalin-fixed, paraffin-embedded tissue samples. Sections were stained with antibodies reactive with CD10, GCET1, FOXP1, MUM1, and BCL6 and cases were classified following a rationale of sequential steps of differentiation of B-cells. Cutoffs for each marker were obtained using receiver operating characteristic curves, obviating the need for any arbitrary method. An algorithm based on the expression of CD10, FOXP1, and BCL6 was developed that had a simpler structure than other recently proposed algorithms and 92.6% concordance with GEP. In multivariate analysis, both the International Prognostic Index and our proposed algorithm were significant independent predictors of progression-free and overall survival. In conclusion, this algorithm effectively predicts prognosis of DLBCL patients matching GEP subgroups in the era of rituximab therapy.
Journal of Clinical Oncology, 2007
The results of immunohistochemical class prediction and prognostic stratification of diffuse large B-cell lymphoma (DLBCL) have been remarkably various thus far. Apart from biologic variations, this may be caused by differences in laboratory techniques, scoring definitions, and inter- and intraobserver variations. In this study, an international collaboration of clinical lymphoma research groups from Europe, United States, and Canada concentrated on validation and standardization of immunohistochemistry of the currently potentially interesting prognostic markers in DLBCL. Sections of a tissue microarray from 36 patients with DLBCL were stained in eight laboratories with antibodies to CD20, CD5, bcl-2, bcl-6, CD10, HLA-DR, MUM1, and MIB-1 according to local methods. The study was performed in two rounds firstly focused on the evaluation of laboratory staining variation and secondly on the scoring variation. Different laboratory staining techniques resulted in unexpectedly highly variable results and very poor reproducibility in scoring for almost all markers. No single laboratory stood out as uniformly poor or excellent. With elimination of variation due to staining, high agreement was found for CD20, HLA-DR, and CD10. Poor agreement was found for bcl-6 and Ki-67. Optimization of techniques and uniformly agreed on scoring criteria improved reproducibility. This study shows that semiquantitative immunohistochemistry for subclassification of DLBCL is feasible and reproducible, but exhibits varying rates of concordance for different markers. These findings may explain the wide variation of biomarker prognostic impact reported in the literature. Harmonization of techniques and centralized consensus review appears mandatory when using immunohistochemical biomarkers for treatment stratification.
Oncotarget, 2016
Diffuse large B cell lymphoma (DLBCL) is a heterogeneous group of aggressive lymphomas that can be classified into three molecular subtypes by gene expression profiling (GEP): GCB, ABC and unclassified. Immunohistochemistry-based cell of origin (COO) classification, as a surrogate for GEP, using three available immunohistochemical algorithms was evaluated in TMA-arranged tissue samples from 297 patients with de novo DLBCL treated by chemoimmunotherapy (R-CHOP and R-CHOP-like regimens). Additionally, the prognostic impacts of MYC, BCL2, IRF4 and BCL6 abnormalities detected by FISH, the relationship between the immunohistochemical COO classification and the immunohistochemical expression of MYC, BCL2 and pSTAT3 proteins and clinical data were evaluated.In our series, non-GCB DLBCL patients had significantly worse progression-free survival (PFS) and overall survival (OS), as calculated using the Choi, Visco-Young and Hans algorithms, indicating that any of these algorithms would be app...
Translational Medicine Communications, 2020
Background Diffuse large B-cell lymphoma (DLBCL) is a heterogenous blood cancer, but can be broadly classified into two main subtypes, germinal center B-cell-like (GCB) and activated B-cell-like (ABC). GCB and ABC subtypes have very different clinical courses, with ABC having a much worse survival prognosis. It has been observed that patients with different subtypes also respond differently to therapeutic intervention, in fact, some have argued that ABC and GCB can be thought of as separate diseases altogether. Due to this variability in response to therapy, having an assay to determine DLBCL subtypes has important implications in guiding the clinical approach to the use of existing therapies, as well as in the development of new drugs. The current gold standard assay for subtyping DLBCL uses gene expression profiling on formalin fixed, paraffin embedded (FFPE) tissue to determine the “cell of origin” and thus disease subtype. However, this approach has some significant clinical lim...
PROTEOMICS – Clinical Applications, 2019
Purpose: Diffuse large B-cell lymphoma (DLBCL), the most common non-Hodgkin lymphoma, is a heterogeneous lymphoma with different clinical manifestations and molecular alterations, and several markers are currently being measured routinely for its diagnosis, subtyping, or prognostication by immunohistochemistry (IHC). Here, the utility of a reverse-phase-protein-array (RPPA) as a novel supportive tool to measure multiple biomarkers for DLBCL diagnosis is validated. Experimental design: The expression of seven markers (CD5, CD10, BCL2, BCL6, MUM1, Ki-67, and C-MYC) is analyzed by RPPA and IHC using 37 DLBCL tissues, and the correlation between the two methods is determined. To normalize tumor content ratio in the tissues, the raw RPPA values of each marker are adjusted by that of CD20 or PAX-5. Results: The CD20-adjusted data for CD5, MUM1, BCL2, Ki-67, and C-MYC has better correlation with IHC results than PAX-5-adjusted data. Receiver operating characteristic (ROC) analysis reveals that CD5, MUM1, BCL2, and C-MYC exhibit a better sensitivity and specificity >0.750. Furthermore, the CD20-adjusted C-MYC value strongly correlates with that of IHC, and has a particularly high specificity (0.882). Conclusions and clinical relevance: Although further investigation using a large number of DLBCL specimens needs to be conducted, these results suggest that RPPA could be applicable as a supportive tool for determining lymphoma prognosis.
Blood, 2004
Diffuse large B-cell lymphoma (DLBCL) can be divided into prognostically important subgroups with germinal center Bcell-like (GCB), activated B-cell-like (ABC), and type 3 gene expression profiles using a cDNA microarray. Tissue microarray (TMA) blocks were created from 152 cases of DLBCL, 142 of which had been successfully evaluated by cDNA microarray (75 GCB, 41 ABC, and 26 type 3). Sections were stained with antibodies to CD10, bcl-6, MUM1, FOXP1, cyclin D2, and bcl-2. Expression of bcl-6 (P < .001) or CD10 (P ؍ .019) was associated with better overall survival (OS), whereas expression of MUM1 (P ؍ .009) or cyclin D2 (P < .001) was associated with worse OS. Cases were subclassified using CD10, bcl-6, and MUM1 expression, and 64 cases (42%) were considered GCB and 88 cases (58%) non-GCB. The 5-year OS for the GCB group was 76% compared with only 34% for the non-GCB group (P < .001), which is similar to that reported using the cDNA microarray. Bcl-2 and cyclin D2 were adverse predictors in the non-GCB group. In multivariate analysis, a high International Prognostic Index score (3-5) and the non-GCB phenotype were independent adverse predictors (P < .0001). In summary, immunostains can be used to determine the GCB and non-GCB subtypes of DLBCL and predict survival similar to the cDNA microarray. (Blood. 2004;103:275-282)
Reproducibility of Gene Expression Signatures in Diffuse Large B-Cell Lymphoma
Cancers, 2022
Multiple gene expression profiles have been identified in diffuse large B-cell lymphoma (DLBCL). Besides the cell of origin (COO) classifier, no signatures have been reproduced in independent studies or evaluated for capturing distinct aspects of DLBCL biology. We reproduced 4 signatures in 175 samples of the HOVON-84 trial on a panel of 117 genes using the NanoString platform. The four gene signatures capture the COO, MYC activity, B-cell receptor signaling, oxidative phosphorylation, and immune response. Performance of our classification algorithms were confirmed in the original datasets. We were able to validate three of the four GEP signatures. The COO algorithm resulted in 94 (54%) germinal center B-cell (GCB) type, 58 (33%) activated B-cell (ABC) type, and 23 (13%) unclassified cases. The MYC-classifier revealed 77 cases with a high MYC-activity score (44%) and this MYC-high signature was observed more frequently in ABC as compared to GCB DLBCL (68% vs. 32%, p < 0.00001). T...
British Journal of Haematology
We assessed the concordance between immunohistochemistry (IHC) and gene expression profiling (GEP) for determining diffuse large B-cell lymphoma (DLBCL) cell of origin (COO) in the phase III PHOENIX trial of rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) with or without ibrutinib. Among 910/1114 screened patients with nongerminal centre B-cell-like (non-GCB) DLBCL by IHC, the concordance with GEP for non-GCB calls was 82•7%, with 691 (75•9%) identified as activated B-cell-like (ABC), and 62 (6•8%) as unclassified. Among 746/837 enrolled patients with verified non-GCB DLBCL by This trial was funded by Janssen Research and Development. The authors would like to thank Dr Anas Younes' contributions towards the PHOENIX study and all patients included in this analysis. Writing assistance was provided by