The cell of origin (COO) classification is an expression-based tumor algorithm identifying molecular subtypes of diffuse large B-cell lymphoma (DLBCL) with distinct prognostic characteristics. Traditional immunohistochemical methods for classifying COO subtypes have poor concordance and limited prognostic value in frontline DLBCL. In contrast, RNA-based metrics like the NanoString Lymphoma Subtyping Test (LST) define more robust subtypes with validated prognostic associations. This study introduces gneSeqCOO, an algorithm using bulk RNA Sequencing (RNASeq) profiles of individual tumor biopsies for COO classification based on a fixed reference. This method produced consistent per-sample results and was robust to variation in RNA quality and sequencing bias. Validation in >1000 DLBCL samples showed high concordance with the NanoString LST assay, even in cohorts containing only one COO subtype. gneSeqCOO presents a robust and versatile alternative to existing assays, potentially reducing the need for additional samples where RNASeq was already generated. The package is available at https://github.com/Genentech/gneSeqCOO.

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http://dx.doi.org/10.1080/10428194.2024.2446613DOI Listing

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