Transcriptomic analysis identifies a potential target for bevacizumab resistant glioblastoma.

Area of Science:

• Neuro-oncology
• Molecular Biology
• Bioinformatics

Background:

• Glioblastoma (GBM), a WHO grade 4 IDH wild-type brain tumor, has a poor prognosis despite standard treatments.
• Bevacizumab, an anti-VEGF-A therapy, is used for recurrent GBM, but response predictors are needed.

Purpose of the Study:

• To identify biomarkers predicting response to bevacizumab in GBM.
• To investigate the role of Early Growth Response-1 (EGR1) in bevacizumab treatment outcomes.

Main Methods:

• Patient-derived xenograft (PDX) models of GBM were treated with bevacizumab or vehicle.
• RNA sequencing (RNAseq) compared gene expression between good and poor responders.
• Bioinformatic analysis identified differentially expressed genes and pathways.
• Protein and functional studies assessed EGR1, Ki67, and angiogenesis.
• Database mining (GLASS) analyzed clinical data.

Main Results:

• Poor responders exhibited upregulated angiogenesis and collagen gene sets.
• Early Growth Response-1 (EGR1) and CHRNA7 (α7-nicotinic-acetylcholine receptor) were upregulated in poor responders.
• Elevated nuclear EGR1, increased Ki67 labeling, and enhanced angiogenesis were observed in bevacizumab-treated poor responders.
• EGR1 and CHRNA7 expression were directly correlated, suggesting CHRNA7 is an EGR1 target.
• Elevated EGR1 and methylated MGMT promoter correlated with shorter survival in female recurrent GBM patients.

Conclusions:

• Increased EGR1 expression, associated with elevated Ki67 and angiogenesis, indicates a poor response to bevacizumab in GBM.
• EGR1 may serve as a predictive biomarker for bevacizumab treatment in GBM.
• Further investigation into EGR1's role in GBM pathogenesis and treatment response is warranted.