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Reproducibility of Gene Expression Signatures in Diffuse Large B-Cell Lymphoma.

Authors :
Plaça JR
Diepstra A
Los T
Mendeville M
Seitz A
Lugtenburg PJ
Zijlstra J
Lam K
da Silva WA Jr
Ylstra B
de Jong D
van den Berg A
Nijland M
Source :
Cancers [Cancers (Basel)] 2022 Mar 05; Vol. 14 (5). Date of Electronic Publication: 2022 Mar 05.
Publication Year :
2022

Abstract

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). The host response (HR) signature of the consensus clustering was present in 55 (31%) patients, while the B-cell receptor signaling, and oxidative phosphorylation clusters could not be reproduced. The overlap of COO, consensus cluster and MYC activity score differentiated six gene expression clusters: GCB/MYC-high (12%), GCB/HR (16%), GCB/non-HR (27%), COO-Unclassified (13%), ABC/MYC-high (25%), and ABC/MYC-low (7%). In conclusion, the three validated signatures identify distinct subgroups based on different aspects of DLBCL biology, emphasizing that each classifier captures distinct molecular profiles.

Details

Language :
English
ISSN :
2072-6694
Volume :
14
Issue :
5
Database :
MEDLINE
Journal :
Cancers
Publication Type :
Academic Journal
Accession number :
35267654
Full Text :
https://doi.org/10.3390/cancers14051346