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Sci Rep ; 11(1): 1886, 2021 01 21.
Article in English | MEDLINE | ID: mdl-33479306

ABSTRACT

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease whose prognosis is associated with clinical features, cell-of-origin and genetic aberrations. Recent integrative, multi-omic analyses had led to identifying overlapping genetic DLBCL subtypes. We used targeted massive sequencing to analyze 84 diagnostic samples from a multicenter cohort of patients with DLBCL treated with rituximab-containing therapies and a median follow-up of 6 years. The most frequently mutated genes were IGLL5 (43%), KMT2D (33.3%), CREBBP (28.6%), PIM1 (26.2%), and CARD11 (22.6%). Mutations in CD79B were associated with a higher risk of relapse after treatment, whereas patients with mutations in CD79B, ETS1, and CD58 had a significantly shorter survival. Based on the new genetic DLBCL classifications, we tested and validated a simplified method to classify samples in five genetic subtypes analyzing the mutational status of 26 genes and BCL2 and BCL6 translocations. We propose a two-step genetic DLBCL classifier (2-S), integrating the most significant features from previous algorithms, to classify the samples as N12-S, EZB2-S, MCD2-S, BN22-S, and ST22-S groups. We determined its sensitivity and specificity, compared with the other established algorithms, and evaluated its clinical impact. The results showed that ST22-S is the group with the best clinical outcome and N12-S, the more aggressive one. EZB2-S identified a subgroup with a worse prognosis among GCB-DLBLC cases.


Subject(s)
Algorithms , Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Lymphoma, Large B-Cell, Diffuse/drug therapy , Lymphoma, Large B-Cell, Diffuse/genetics , Mutation , Adult , Aged , CD79 Antigens/genetics , DNA-Binding Proteins/genetics , Female , Humans , In Situ Hybridization, Fluorescence , Lymphoma, Large B-Cell, Diffuse/classification , Male , Middle Aged , Neoplasm Proteins/genetics , Outcome Assessment, Health Care/methods , Outcome Assessment, Health Care/statistics & numerical data , Prognosis , Receptor, Notch1/genetics , Reproducibility of Results , Rituximab/administration & dosage
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