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Proteomic Profiling Identifies Predictive Signatures for Progression Risk in Patients with Advanced-Stage Follicular Lymphoma.

Authors :
Hemmingsen, Jonas Klejs
Enemark, Marie Hairing
Sørensen, Emma Frasez
Lauridsen, Kristina Lystlund
Hamilton-Dutoit, Stephen Jacques
Kridel, Robert
Honoré, Bent
Ludvigsen, Maja
Source :
Cancers; Oct2024, Vol. 16 Issue 19, p3278, 15p
Publication Year :
2024

Abstract

Simple Summary: This research aims to identify new protein markers that can help predict the risk of disease progression in patients with follicular lymphoma (FL) at the time of diagnosis. By analyzing a large number of proteins in FL samples, the study found significant differences in protein composition among patients, which may help distinguish those at higher risk of disease progression. These findings could improve our understanding of FL biology and lead to the discovery of new biomarkers or treatment targets, potentially allowing for more personalized and effective treatment strategies for FL patients, improving their outcomes. Background: Follicular lymphoma (FL) is characterized by an indolent nature and generally favorable prognosis, yet poses a particular clinical challenge, since disease progression is observed in a notable subset of patients. Currently, it is not possible to anticipate which patients will be at risk of progression, highlighting the need for reliable predictive biomarkers that can be detected early in the disease. Methods: We applied tandem-mass-tag labelled nano-liquid chromatography tandem mass spectrometry (nLC-MS/MS) on 48 diagnostic formalin-fixed, paraffin-embedded tumor samples from patients with advanced-stage FL. Of these, 17 experienced subsequent progression (subsequently-progressing, sp-FL) while 31 did not (non-progressing, np-FL). Results: We identified 99 proteins that were significantly differentially expressed between sp-FL samples and np-FL samples (p < 0.05; log<subscript>2</subscript>-fold changes between 0.2 and −1.3). Based on this subset of proteins, we classified patients into high-risk and low-risk subgroups using unsupervised machine learning techniques. Pathway analyses of the identified proteins revealed aberrancies within the immune system and cellular energy metabolism. In addition, two proteins were selected for immunohistochemical evaluation, namely stimulator of interferon genes 1 (STING1) and isocitrate dehydrogenase 2 (IDH2). Notably, IDH2 retained significantly lower expression levels in sp-FL samples compared with np-FL samples (p = 0.034). Low IDH2 expression correlated with shorter progression-free survival (PFS, p = 0.020). Conclusions: This study provides evidence for some of the biological mechanisms likely to be involved in FL progression and, importantly, identifies potential predictive biomarkers for improvement of risk stratification up-front at time of FL diagnosis. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20726694
Volume :
16
Issue :
19
Database :
Complementary Index
Journal :
Cancers
Publication Type :
Academic Journal
Accession number :
180274175
Full Text :
https://doi.org/10.3390/cancers16193278