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The EGFRvIII transcriptome in glioblastoma, a meta-omics analysis.

BACKGROUND EGFR is among the genes most frequently altered in glioblastoma, with exons 2-7 deletions (EGFRvIII) being amongst its most common genomic mutations. There are conflicting reports about its prognostic… Click to show full abstract

BACKGROUND EGFR is among the genes most frequently altered in glioblastoma, with exons 2-7 deletions (EGFRvIII) being amongst its most common genomic mutations. There are conflicting reports about its prognostic role and it remains unclear whether and how it differs in signalling compared with wildtype EGFR. METHODS To better understand the oncogenic role of EGFRvIII, we leveraged four large datasets into one large glioblastoma transcriptome dataset (n=741) alongside 81 whole-genome samples from two datasets. RESULTS The EGFRvIII/EGFR expression ratios differ strongly between tumours and ranges from 1% to 95%. Interestingly, the slope of relative EGFRvIII expression is near-linear, which argues against a more positive selection pressure than EGFR wildtype. An absence of selection pressure is also suggested by the similar survival between EGFRvIII positive and negative glioblastoma patients. EGFRvIII levels are inversely correlated with pan-EGFR (all wildtype and mutant variants) expression, which indicates that EGFRvIII has a higher potency in downstream pathway activation. EGFRvIII-positive glioblastomas have a lower CDK4 or MDM2 amplification incidence than EGFRvIII-negative (p=0.007), which may point towards crosstalk between these pathways. EGFRvIII-expressing tumours have an upregulation of 'classical' subtype genes compared to those with EGFR-amplification only (p=3.873e-6). Genomic breakpoints of the EGFRvIII deletions have a preference towards the 3' end of the large intron-1. These preferred breakpoints preserve a cryptic exon resulting in a novel EGFRvIII variant and preserve an intronic enhancer. CONCLUSIONS These data provide deeper insights into the complex EGFRvIII biology and provide new insights for targeting EGFRvIII mutated tumours.

Keywords: glioblastoma; transcriptome glioblastoma; egfrviii transcriptome; meta omics; glioblastoma meta; omics analysis

Journal Title: Neuro-oncology
Year Published: 2021

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