Abstract
BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) has variable prognosis, with only 50 to 60% of patients cured by standard first line treatment. Identifying patients unlikely to benefit from standard first line therapy is therefore crucial. Schmitz's study identified four molecular subtypes of DLBCL with differing prognoses: MCD, BN2, N1, and EZB, with BN2 and EZB showing more favorable outcomes. This study aimed to evaluate the effectiveness of the Archer FusionPlex Lymphoma Assay in identifying the newly defined genetic subtypes of DLBCL, while also exploring the association between immunohistochemical (IHC) and next-generation sequencing (NGS) methods for classifying the cell of origin (COO) and assessing their predictive value for patient survival. MATERIALS AND METHODS: We classified 131 DLBCL patients using Hans algorithm into GCB (germinal center B-cell-like) and ABC (activated B-cell-like) subtypes, and with NGS applying Archer FusionPlex lymphoma assay into ABC, GCB, unclassified, and into Schmitz's novel genetic subtypes. A mutational analysis of just 7 genes (MYD88 (L265P), CD79B, EZH2, NOTCH1, NOTCH2, BCL2, and BCL6) was used for genetic classification. Various statistical models were applied to assess survival differences between subtypes. Finally, STRATOS analysis was conducted to validate our preliminary statistical findings. RESULTS: 35.9% of patients were successfully classified into new genetic subtypes, with acceptable consistency between IHC and NGS method for COO determination. However, the new genetic subtype classification by NGS did not correlate with overall survival, nor did the COO classifications by IHC or NGS. The inclusion of these classifications also did not improve the predictive value of models compared to the basic model based on the International Prognostic Index (IPI) only. CONCLUSIONS: The Archer FusionPlex Lymphoma assay showed a somewhat lower detection rate of novel genetic subtypes compared to reports based on exome sequencing, yet identified novel genetic subtypes in over one-third of patients. However, an in-depth STRATOS statistical analysis did not confirm its predictive value for DLBCL prognosis, likely due to factors like patient selection and sample size limitations.