scholarly journals Prognostic Impact of Cell of Origin in Limited-Stage Diffuse Large B-Cell Lymphoma Treated With R-CHOP With or Without Radiation Therapy

Author(s):  
P. Youn ◽  
M.A. Cummings ◽  
S. Dhakal ◽  
W.R. Burack ◽  
C. Casulo ◽  
...  
Haematologica ◽  
2019 ◽  
Vol 105 (9) ◽  
pp. 2298-2307 ◽  
Author(s):  
Christopher R. Bolen ◽  
Magdalena Klanova ◽  
Marek Trneny ◽  
Laurie H. Sehn ◽  
Jie He ◽  
...  

Diffuse large B-cell lymphoma represents a biologically and clinically heterogeneous diagnostic category with well-defined cell-of-origin subtypes. Using data from the GOYA study (NCT01287741), we characterized the mutational profile of diffuse large B-cell lymphoma and evaluated the prognostic impact of somatic mutations in relation to cell-of-origin. Targeted DNA next-generation sequencing was performed in 499 formalin-fixed paraffin-embedded tissue biopsies from previously untreated patients. Prevalence of genetic alterations/mutations was examined. Multivariate Cox regression was used to evaluate the prognostic effect of individual genomic alterations. Of 465 genes analyzed, 59 were identified with mutations occurring in at least 10 of 499 patients (≥2% prevalence); 334 additional genes had mutations occurring in ≥1 patient. Single nucleotide variants were the most common mutation type. On multivariate analysis, BCL2 alterations were most strongly associated with shorter progression-free survival (multivariate hazard ratio: 2.6; 95% confidence interval: 1.6 to 4.2). BCL2 alterations were detected in 102 of 499 patients; 92 had BCL2 translocations, 90% of whom had germinal center B-cell-like diffuse large B-cell lymphoma. BCL2 alterations were also significantly correlated with BCL2 gene and protein expression levels. Validation of published mutational subsets revealed consistent patterns of co-occurrence, but no consistent prognostic differences between subsets. Our data confirm the molecular heterogeneity of diffuse large B-cell lymphoma, with potential treatment targets occurring in distinct cell-of-origin subtypes. clinicaltrials.gov identifier: NCT01287741.


Cancers ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 474 ◽  
Author(s):  
Sara Alonso-Álvarez ◽  
Miguel Alcoceba ◽  
María García-Álvarez ◽  
Oscar Blanco ◽  
Marta Rodríguez ◽  
...  

The biology and clinical impact of bone marrow (BM) infiltration in patients with diffuse large B-cell lymphoma (DLBCL) remains unclear in the rituximab era. We retrospectively analyzed 232 patients diagnosed with DLBCL at our center between 1999 and 2014. Concordant-presence of large cells similar to those of the lymph node biopsy- and discordant-infiltration by small cells forming lymphoid aggregates, lacking cytological atypia-BM infiltration was defined by histological criteria and further characterized by flow cytometry (FCM). Cell of origin (COO) was determined using Hans’ algorithm. For the clonal relationship between tumor and discordant BM, the VDJH rearrangement was analyzed. Survival analyses were restricted to 189 patients treated with rituximab and chemotherapy. Thirty-six (16%) had concordant, and 37 (16%) discordant BM infiltration. FCM described different indolent lymphomas among discordant cases, clonally related with DLBCL in 10/13 available samples. Median follow-up was 58 months. 5-year-progression-free survival (PFS) for non-infiltrated, discordant and concordant groups was 68%, 65% and 30%, respectively (p < 0.001). Combining COO and BM infiltration, patients with discordant BM and non-germinal center B-cell COO also had decreased 5-year-PFS (41.9%). In multivariate analysis, concordant BM had an independent effect on PFS (HR 2.5, p = 0.01). Five-year cumulative incidence of central nervous system (CNS) relapse was 21%, 4% and 1% in concordant, discordant and non-infiltrated groups, respectively (p < 0.001). In conclusion, concordant BM infiltration represents a subset with poor prognosis, whereas the prognostic impact of discordant BM infiltration could be limited to non-CGB cases.


2018 ◽  
Vol 182 (4) ◽  
pp. 534-541 ◽  
Author(s):  
Carlos Montalbán ◽  
Antonio Díaz-López ◽  
Alejandro Martín ◽  
Mónica Baile ◽  
José M. Sanchez ◽  
...  

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 2973-2973
Author(s):  
Karen Dybkær ◽  
Martin Bøgsted ◽  
Steffen Falgreen ◽  
Malene Krag Kjeldsen ◽  
Alexander Schmitz ◽  
...  

Abstract Background Recent findings have introduced biological classification of non-Hodgkin lymphomas as exemplified by the “activated B-cell-like” (ABC) and “germinal-center B-cell–like” (GCB) subgroups of diffuse large B-cell lymphoma (DLBCL). Aims The goal is to generate a refined cell of origin (COO) classification that includes B-cell subset associated gene signatures (BAGS) from the normal B-cell hierarchy. Methods We have combined fluorescence activated cell sorting and gene expression profiling by Gene Chip HG U133 Plus 2.0 to generate five BAGS for naïve, germinal centrocytes and centroblasts, post germinal memory B-cells, and plasmablasts of normal human tonsils. Clinical data sets are the Aalborg Project CHEPRETRO (N=89), the Lymphoma/Leukemia Molecular Profiling Project LLMPP (N=233), the International DLBCL Rituximab-CHOP Consortium MD Anderson Project IDRC (N=460), the Mayo Clinic, Brigham & Women Hospital, and Dana-Farber Cancer Institute Project MDFCI (N=88) available on the GEO website. All statistical analyses were done with R version 3.0.1 and full documentation is provided by a Sweave document. Results First, we verified the quality of the sampled B-cell subsets based on the expression patterns of differentiation molecules, transcription factors, and genes matching biological knowledge. Next, we constructed a BAGS-classifier provided by 77-115 gene probe sets, capable of assigning samples to each of the five COO subtypes. Second, we assigned individual lymphoma cases in 5 patient cohorts including a total of 1063 patient. BAGS identified COO subtypes with frequencies of 2-7 % naïve (N), 35-41 % centrocytes (CC), 18-21 % centroblasts (CB), 4-15 % memory (M), 12-18 % plasmablast (PB), and 15-16 % unclassified (UC) subtypes. The frequencies was not different between cohorts (p=0.41). Third, the BAGS subtypes was associated significantly with overall survival and time to progression for R-CHOP–treated patients in clinical cohorts from the LLMPPN (p=0.0441/0.0358) and the IDRC Program (p=0.002/8e-04). Fourth, we found a very high fraction of GCB samples to be of CC or CB subtypes. On the contrary, a major fraction of BAGS-unclassified subtypes were of the ABC class. In a multiple Cox proportional hazards model we identified the BAGS subtypes to be a prognostic variables independent of ABC/GCB subtypes but not of IPI and age. The most significant impact was observed within the GCB subclass, where the GCB-CC subtype had superior prognosis compared to the GCB-CB subtype, in accordance with individual assignments for drug specific sensitivity to hydroxydaunomycin and vincristine. Fifth, we performed genetic evaluation of the BAGS subtypes by mutation analysis within the CHEPRETRO cohort for EZH2, CD79B, and MYD88 identifying frequencies of 6.3%, 10.1% and 14.7%, respectively. The EZH2 mutation was only identified in the GCBN-CC and -CB subtypes. Mutations of CD79B and MYD88 were preferential in ABC, present in all subtypes. The CC subtype had high p53 mutation and indel frequencies, whereas the CB subtype had high Chr12q15 amplification frequencies and a complex genotype. Finally, the CC subtype expressed LMO2, NF-κB targets, CD58, Stroma1, and MHCII genes, known to have prognostic impact. Summary In summary, this study addresses an unmet medical need for a new diagnostic platform for individual DLBCL classification of “cell of origin” phenotyping attempting to design new strategies and more effective disease management. Disclosures No relevant conflicts of interest to declare.


2019 ◽  
Vol 46 (4) ◽  
pp. 4063-4076 ◽  
Author(s):  
Samir A. Shawky ◽  
Mohamed H. El-Borai ◽  
Hussein M. Khaled ◽  
Iman Guda ◽  
Marwa Mohanad ◽  
...  

2015 ◽  
Vol 171 (5) ◽  
pp. 776-783 ◽  
Author(s):  
Anita Kumar ◽  
Matthew A. Lunning ◽  
Zhigang Zhang ◽  
Jocelyn C. Migliacci ◽  
Craig H. Moskowitz ◽  
...  

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