In vivo functional characterization of EGFR variants identifies novel drivers of glioblastoma.

ABSTRACT:

Background

Glioblastoma is the most common and aggressive primary brain tumor. Large-scale sequencing initiatives have cataloged its mutational landscape in hopes of elucidating mechanisms driving this deadly disease. However, a major bottleneck in harnessing this data for new therapies is deciphering "driver" and "passenger" events amongst the vast volume of information.

Methods

We utilized an autochthonous, in vivo screening approach to identify driver, EGFR variants. RNA-Seq identified unique molecular signatures of mouse gliomas across these variants, which only differ by a single amino acid change. In particular, we identified alterations to lipid metabolism, which we further validated through an unbiased lipidomics screen.

Results

Our screen identified A289I as

SUBMITTER: Yu K 

PROVIDER: S-EPMC10013639 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature