Journal
SCIENTIFIC REPORTS
Volume 11, Issue 1, Pages -Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41598-020-80376-0
Keywords
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Funding
- ISCIII
- Complejo Hospitalario de Toledo
- MD Anderson Cancer Center-Madrid
- Pathology Departments of the centers
- Spanish Ministry of Economy and Competence (MINECO) [SAF2013-47416-R]
- ISCIII-MINECO AES-FEDER (Plan Estatal de I+D+I 2008-2011) [PI14/00221, DTS17/00039, PI17/00272, PI16/01294, CIBERONC CB16/12/00291]
- ISCIII-MINECO AES-FEDER (Plan Estatal de I+D+I 2013-2016) [PI14/00221, DTS17/00039, PI17/00272, PI16/01294, CIBERONC CB16/12/00291]
- GILEAD [GL18/00019]
- Direccion General de Universidades e Investigacion Consejeria de Educacion e Investigacion de la Comunidad de Madrid [B2017/BMD-3778]
- iPFIS predoctoral fellowships [IFI18/0004, IFI14/0003]
- iPFIS predoctoral fellowships (ISCIII-MINECO AES-FEDER (Plan Estatal I+D+I 2017-2020))
- iPFIS predoctoral fellowships (ISCIII-MINECO AES-FEDER (Plan Estatal I+D+I 2013-2016))
- bioinformatician fellowship [CA18/00022]
- Asociacion Espanola Contra el Cancer
- Miguel Servet II [CPII16/00024]
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This study investigated the genetic subtypes of diffuse large B-cell lymphoma, identified mutated genes associated with treatment outcomes and survival, and proposed a two-step genetic DLBCL classifier. Different genetic subtypes have different impacts on patients' prognosis, with patients in the ST2(2-S) group having the best clinical outcome.
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 N1(2-S), EZB(2-S), MCD2-S, BN2(2-S), and ST2(2-S) groups. We determined its sensitivity and specificity, compared with the other established algorithms, and evaluated its clinical impact. The results showed that ST2(2-S) is the group with the best clinical outcome and N1(2-S), the more aggressive one. EZB(2-S) identified a subgroup with a worse prognosis among GCB-DLBLC cases.
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