Anti-tumour and associated metabolic effects of repurposed Afuresertib and Taxifolin for glioblastoma treatment

Abstract

Isocitrate dehydrogenase wild-type glioblastoma (GBM) is a particularly devastating central nervous system tumour with limited treatments. Taking advantage of computational strategies, drug repurposing has been regarded as an alternative and effective tool in GBM drug development, especially models targeting altered metabolic pathways and genomic alterations. In previous work, Afuresertib and Taxifolin were selected as repurposed candidates after the application of Transcriptomics-informed Stoichiometric Modelling and Network analysis. Whilst these two candidates have been studied in the other types of cancers, they have not been tested against GBM. This study explored the in vitro anti-tumour effect of Afuresertib and Taxifolin using PrestoBlue metabolic viability assay and Transwell collagen barrier assay on patient-derived glioblastoma cell lines. Their associated metabolic impact was revealed by the application of untargeted metabolomics method. The results showed that Afuresertib had stronger inhibition on GBM cell proliferation and invasion than Taxifolin. Glycerophospholipids metabolism was more active in cells derived from invasion margin relative to cells from tumour core, indicating the possibility of varying underlining genetic mutations between GIN and GCE cell lines. Afuresertib could affect amino acid metabolism and glycerophospholipid metabolism, exerting the function of anti-proliferation and anti-invasion. Taxifolin could damage nicotinate and nicotinamide metabolism, leading to the death of tumour cells.

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Article information

Article type
Paper
Submitted
25 Apr 2025
Accepted
01 Dec 2025
First published
02 Dec 2025
This article is Open Access
Creative Commons BY license

Analyst, 2026, Accepted Manuscript

Anti-tumour and associated metabolic effects of repurposed Afuresertib and Taxifolin for glioblastoma treatment

R. Chen, N. Gumus, S. Jearranaiprepame, A. Woodward, R. Rahman and D. Kim, Analyst, 2026, Accepted Manuscript , DOI: 10.1039/D5AN00461F

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