Multiomic analysis identifies a high-risk signature that predicts early clinical failure in DLBCL.

ABSTRACT: Recent genetic and molecular classification of DLBCL has advanced our knowledge of disease biology, yet were not designed to predict early events and guide anticipatory selection of novel therapies. To address this unmet need, we used an integrative multiomic approach to identify a signature at diagnosis that will identify DLBCL at high risk of early clinical failure. Tumor biopsies from 444 newly diagnosed DLBCL were analyzed by WES and RNAseq. A combination of weighted gene correlation network analysis and differential gene expression analysis was used to identify a signature associated with high risk of early clinical failure independent of IPI and COO. Further analysis revealed the signature was associated with metabolic reprogramming and identified cases with a depleted immune microen

SUBMITTER: Wenzl K 

PROVIDER: S-EPMC11189905 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature