Evaluation of gene expression assays to classify large B-cell lymphoma by molecular subtype using formalin-fixed paraffin-embedded tumor biopsies
Year: 2026
Type: article
Abstract: Gene expression profiling (GEP) can classify large B-cell lymphoma (LBCL) into activated B-cell (ABC), dark zone signature (DZsig), and germinal center B-cell (GCB) subtypes, which can inform prognosis and treatment strategies. We evaluated the concordance of Clinical Laboratory Improvement Amendments (CLIA) assays with the previously validated RNA-based DLBCL90 nanoString assay (DLBCL90) and an RNAseq-based approach (gneSeqCOO and gneSeqDZsig) for classification of DZsig status and cell-of-origin (COO) in 95 formalin-fixed paraffin-embedded tumor specimens. The correlation between DLBCL90 COO and gneSeqCOO linear predictor scores (LPS) was R 2 = 0.95 ( P < 0.0001), with an overall classification concordance of 87% (95% confidence interval [CI] 79–93), and 1.3% frank discordance (ABC to GCB or vice versa). The correlation between DLBCL90 DZsig and gneSeqDZsig LPS was R 2 = 0.92 ( P < 0.0001), with class concordance of 85% (95% CI 74–93) and 0% frank class discordance. These data demonstrate high concordance between DLBCL90 and an RNAseq classifier for COO and DZsig providing CLIA options for clinical gene expression classification of LBCLs.
Source: Blood Cancer Journal
Authors: Neha Akkad, Laura K. Hilton, Kumudha Balakrishnan, Dzifa Duose, Yasmine Yuen Man Lau, Aixiang Jiang, Subiksha Sankar, Okechukwu V. Nwogbo, Anindita Ghosh, Paul Young Erhumutemabor, Amy Ayers, Svetlana Paponova, Alexander Nesmelov, Pavel Zemskiy, Anastasiia Shvyrkova, Elizabeth Sheehan, Kelley Lauziere, Svetlana Podsvirova, Ekaterina Postovalova, Nikita Kotlov, Alexander Bagaev, Rajyalakshmi Luthra, L. Jeffrey Medeiros, Keyur P. Patel, Francisco Vega, Nathan Fowler, David W. Scott, Christopher R. Flowers
Language: English
Subfield: Pathology and Forensic Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $5,290
OpenAlex ID: W7222926375