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- Abdulla, Maysaa, et al.
(författare)
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Cell-of-origin determined by both gene expression profiling and immunohistochemistry is the strongest predictor of survival in patients with diffuse large B-cell lymphoma
- 2020
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Ingår i: American Journal of Hematology. - : Wiley. - 0361-8609 .- 1096-8652. ; 95:1, s. 57-67
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Tidskriftsartikel (refereegranskat)abstract
- The tumor cells in diffuse large B-cell lymphomas (DLBCL) are considered to originate from germinal center derived B-cells (GCB) or activated B-cells (ABC). Gene expression profiling (GEP) is preferably used to determine the cell of origin (COO). However, GEP is not widely applied in clinical practice and consequently, several algorithms based on immunohistochemistry (IHC) have been developed. Our aim was to evaluate the concordance of COO assignment between the Lymph2Cx GEP assay and the IHC-based Hans algorithm, to decide which model is the best survival predictor. Both GEP and IHC were performed in 359 homogenously treated Swedish and Danish DLBCL patients, in a retrospective multicenter cohort. The overall concordance between GEP and IHC algorithm was 72%; GEP classified 85% of cases assigned as GCB by IHC, as GCB, while 58% classified as non-GCB by IHC, were categorized as ABC by GEP. There were significant survival differences (overall survival and progression-free survival) if cases were classified by GEP, whereas if cases were categorized by IHC only progression-free survival differed significantly. Importantly, patients assigned as non-GCB/ABC both by IHC and GEP had the worst prognosis, which was also significant in multivariate analyses. Double expression of MYC and BCL2 was more common in ABC cases and was associated with a dismal outcome. In conclusion, to determine COO both by IHC and GEP is the strongest outcome predictor to identify DLBCL patients with the worst outcome.
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| 2. |
- Brauner, S., et al.
(författare)
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Reduced expression of TRIM21/Ro52 predicts poor prognosis in diffuse large B-cell lymphoma patients with and without rheumatic disease
- 2015
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Ingår i: Journal of Internal Medicine. - : Wiley. - 0954-6820 .- 1365-2796. ; 278:3, s. 323-332
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Tidskriftsartikel (refereegranskat)abstract
- ObjectiveTRIM21 (also known as Ro52) is an autoantigen in rheumatic disease and is predominantly expressed in leucocytes. Overexpression is associated with decreased proliferation, and the TRIM21 gene maps to a tumour suppressor locus. We therefore investigated the expression of TRIM21 in patients with diffuse large B-cell lymphoma (DLBCL) and its potential usefulness as a prognostic biomarker. Materials and methodsTRIM21 expression levels were assessed by immunohistochemistry in lymphoma biopsies from three cohorts of patients with DLBCL: 42 patients with rheumatic disease treated with a cyclophosphamide, vincristine, doxorubicin and prednisone (CHOP)-like regimen, 76 CHOP-treated and 196 rituximab-CHOP-treated nonrheumatic patients. Expression was correlated with clinical and biomedical parameters. TRIM21 expression was assessed in relation to lymphocyte proliferation by quantitative PCR and correlated with H-3-thymidine incorporation and propidium iodine staining. ResultsTRIM21 expression levels differed in the lymphomas compared to normal lymphoid tissue, with reduced expression correlating with shorter overall survival in all three cohorts. In the two larger cohorts, progression-free survival was assessed and was also found to correlate with TRIM21 expression. The association was independent of commonly used clinical prognostic scores, lymphoma subtype and several previously reported prognostic biomarkers. In agreement with this clinical observation, we noted an inverse correlation between TRIM21 expression and proliferation of leucocytes invitro. ConclusionsWe show that loss of TRIM21 expression is associated with more aggressive lymphoma and increased proliferation, whereas maintenance of TRIM21 expression is associated with better prognosis in patients with DLBCL. Based on our findings, we suggest that TRIM21 should be considered as a novel biomarker for lymphoma characterization and for predicting patient survival.
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