Authors
Harry Porter, Kayley Mulhall, Maria Shah, Jeffy Joseph Vinohar, Konstantinos-Panagiotis Karadimas, Shaylen Mistry, Simon Deacon, Farhana Haque, Emyr Bakker, David J Boocock, Clare Coveney, Robert Layfield, Ruman Rahman, Phoebe McCrorie
Published in
Neuro-oncology advances. Volume 8. Issue 1. Pages vdag181. Epub Jul 10, 2026.
Abstract
Glioblastoma (GBM) is an aggressive brain tumor characterized by rapid growth and infiltration. New therapies are desperately needed to improve GBM patient outcomes. Intra-tumoral heterogeneity is a common driver of failure for novel GBM treatments, and many preclinical studies rely on cell lines established from the tumor core. As a result, they fail to characterize the infiltrative tumor cells, which remain post-surgery and ultimately drive tumor recurrence.
This study characterizes the membrane proteome of 3 patient-derived GBM cell lines isolated from the tumor invasive margin (GIN8, GIN28, and GIN31), which is a proxy for residual disease post-surgery. We combined plasma membrane protein analysis with total protein analysis using liquid chromatography-mass spectrometry to uncover therapeutic targets most amenable for drug repurposing. Molecular docking analysis predicted specific binding pockets on the surface of key membrane proteins against which the top 10 approved drug candidates were screened based on their binding energy scores.
Membrane proteins such as EDIL3, DYSF, ROBO1, SERPINE2, LOXL1, and CD70 were consistently significantly upregulated across GBM cell lines relative to healthy astrocyte controls, indicating potential functional roles in GBM progression. Molecular docking identified nilotinib (targeting LOXL1) and darifenacin (targeting SH3KBP1) as candidate drugs that can bind to identified membrane proteins. Nilotinib and darifenacin produced average IC50 values of 8.45 µM and 46.77 µM, respectively, in cell viability assays against GIN cell lines.
These findings suggest that targeting membrane proteins offers promise for developing effective GBM therapies predicated on the most prognostically relevant intra-tumor region.
PMID:
42534387
Bibliographic data and abstract were imported from PubMed on 31 Jul 2026.
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