Development and validation of a gene expression signature to predict early events in patients with follicular lymphoma.

ABSTRACT:

Abstract

Although follicular lymphoma (FL) typically follows an indolent course, patients with FL who experience early events, such as transformation or progression, have increased risk of death related to lymphoma. The FL24Cx is an algorithm based on a 45-target gene expression profiling (GEP) assay, which was developed and trained using 265 formalin-fixed, paraffin-embedded tissue samples on a reliable platform to predict, at the time of diagnosis, whether a patient will experience an event within 24 months. The modeling also confirmed and relied upon previously reported synergy between immune response (IR) gene expression signatures IR1 and IR2. Once locked, the 5-factor logistic regression FL24Cx model was independently validated in a retrospectively assessed cohort of 232 pati

SUBMITTER: Ramsower CA 

PROVIDER: S-EPMC12755980 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature