AI Article Synopsis

  • * A study analyzed whole-genome sequencing of 423 patients, identifying two genetically distinct subgroups of FL: DLBCL-like (dFL) and constrained FL (cFL), each with unique mutation patterns.
  • * The research developed a machine learning classification method to differentiate between cFL and dFL, finding that cFL is linked to a lower risk of histologic transformation, suggesting its potential for predicting patient outcomes based on genetic characteristics.

Article Abstract

Follicular lymphoma (FL) accounts for ∼20% of all new lymphoma cases. Increases in cytological grade are a feature of the clinical progression of this malignancy, and eventual histologic transformation (HT) to the aggressive diffuse large B-cell lymphoma (DLBCL) occurs in up to 15% of patients. Clinical or genetic features to predict the risk and timing of HT have not been described comprehensively. In this study, we analyzed whole-genome sequencing data from 423 patients to compare the protein coding and noncoding mutation landscapes of untransformed FL, transformed FL, and de novo DLBCL. This revealed 2 genetically distinct subgroups of FL, which we have named DLBCL-like (dFL) and constrained FL (cFL). Each subgroup has distinguishing mutational patterns, aberrant somatic hypermutation rates, and biological and clinical characteristics. We implemented a machine learning-derived classification approach to stratify patients with FL into cFL and dFL subgroups based on their genomic features. Using separate validation cohorts, we demonstrate that cFL status, whether assigned with this full classifier or a single-gene approximation, is associated with a reduced rate of HT. This implies distinct biological features of cFL that constrain its evolution, and we highlight the potential for this classification to predict HT from genetic features present at diagnosis.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10644066PMC
http://dx.doi.org/10.1182/blood.2022018719DOI Listing

Publication Analysis

Top Keywords

follicular lymphoma
8
coding noncoding
8
noncoding mutation
8
genetic features
8
genetic subdivisions
4
subdivisions follicular
4
lymphoma
4
lymphoma defined
4
defined distinct
4
distinct coding
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!