Litcius/Paper detail

Expression and prognostic value of the transcription factors EGR1 and EGR3 in gliomas

Arnon Møldrup Knudsen, Ida Eilertsen, Susanne Kielland, M W Pedersen, Mia Dahl Sørensen, Rikke Hedegaard Dahlrot, Henning B. Boldt, Sune Munthe, Frantz Rom Poulsen, Bjarne Winther Kristensen

2020Scientific Reports26 citationsDOIOpen Access PDF

Abstract

Most glioblastoma patients have a dismal prognosis, although some survive several years. However, only few biomarkers are available to predict the disease course. EGR1 and EGR3 have been linked to glioblastoma stemness and tumour progression, and this study aimed to investigate their spatial expression and prognostic value in gliomas. Overall 207 gliomas including 190 glioblastomas were EGR1/EGR3 immunostained and quantified. A cohort of 21 glioblastomas with high P53 expression and available tissue from core and periphery was stained with double-immunofluorescence (P53-EGR1 and P53-EGR3) and quantified.EGR1 expression increased with WHO-grade, and declined by 18.9% in the tumour periphery vs. core (P = 0.01), while EGR3 expression increased by 13.8% in the periphery vs. core (P = 0.04). In patients with high EGR1 expression, 83% had methylated MGMT-promoters, while all patients with low EGR1 expression had un-methylated MGMT-promoters. High EGR3 expression in MGMT-methylated patients was associated with poor survival (HR = 1.98; 95%CI 1.22-3.22; P = 0.006), while EGR1 high/EGR3 high, was associated with poor survival vs. EGR1 high/EGR3 low (HR = 2.11; 95%CI 1.25-3.56; P = 0.005). EGR1 did not show prognostic value, but could be involved in MGMT-methylation. Importantly, EGR3 may be implicated in cell migration, while its expression levels seem to be prognostic in MGMT-methylated patients.

Topics & Concepts

EGR1Transcription factorValue (mathematics)Cancer researchTranscription (linguistics)GliomaMedicineOncologyInternal medicineBioinformaticsBiologyGeneticsComputer scienceGeneMachine learningLinguisticsPhilosophyGlioma Diagnosis and TreatmentCancer, Hypoxia, and MetabolismRadiomics and Machine Learning in Medical Imaging