Work

High-risk subgroup and associated genes identified by next generation sequencing in diffuse large B cell lymphoma

Year: 2026

Type: article

Abstract: PURPOSE: Diffuse large B cell lymphoma (DLBCL) displays genetic and clinical heterogeneity that limits the predictive value of cell-of-origin and LymphGen. We evaluated whether diagnostic targeted next generation sequencing (NGS) could predict outcomes and delineate high-risk subsets in routine practice. EXPERIMENTAL DESIGN: We retrospectively analyzed tumors from 106 patients. Variants with allele frequency(VAF) ≥ 10% from a lymphoma-focused panel were curated into a binary mutation matrix. Random Forest regression identified genes associated with overall survival (OS) and progression-free survival (PFS). Principal-component analysis with k-means clustering stratified tumors, and groups were compared for survival, clinical and pathologic features, and LymphGen composition. RESULTS: Thirty genes with strong prognostic signals were recovered, spanning canonical drivers and novel candidates. Clustering of these features yielded two molecular subgroups, one highly enriched for LymphGen-unclassified tumors. This subgroup showed significantly inferior PFS and a higher prevalence of adverse clinical factors like advanced IPI, stage, elevated LDH. CONCLUSIONS: Targeted NGS combined with machine learning and unsupervised clustering provides robust, clinical significant stratification in DLBCL, revealing a high-risk subgroup not captured by existing classification. These findings support incorporating panel-based sequencing into routine diagnostics to refine risk-adapted treatment and prioritize patients for intensified or novel therapies.

Source: BMC Cancer

DOI: 10.1186/s12885-026-15868-9