Evidence map›Paper›PMID 41097037›Full record

ArticleInternational journal of molecular sciences2025

Transcriptomic-Driven Drug Repurposing Reveals SP600125 as a Promising Drug Candidate for the Treatment of Glial-Mesenchymal Transition in Glioblastoma.

Kirill V Odarenko, Marina A Zenkova, Andrey V Markov

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Kirill V OdarenkoInstitute of Chemical Biology and Fundamental Medicine, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia.ORCID 0000-0003-1092-0014
Marina A ZenkovaInstitute of Chemical Biology and Fundamental Medicine, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia.ORCID 0000-0003-4044-1049
Andrey V MarkovInstitute of Chemical Biology and Fundamental Medicine, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia.ORCID 0000-0001-7569-9555

Funding

Russian Science Foundation 23-14-00374Russian state-funded project for ICBFM SB RAS 125012300659-6
6 · The paper itself

Abstract

Glioblastoma multiforme (GBM) is an aggressive brain cancer characterized by highly invasive growth driven by glial-mesenchymal transition (GMT). Given the urgent need for effective therapies targeting this process, we aimed to discover potential GMT inhibitors using transcriptomic-based repurposing applied to both approved and experimental drugs. Deep bioinformatic analysis of transcriptomic data from GBM patient tumors and GBM cell lines with mesenchymal phenotype using gene set variation analysis (GSVA), weighted gene co-expression network analysis (WGCNA), reconstruction of GMT-related gene association networks, gene set enrichment analysis (GSEA), and the search for correlation with transcriptomic profiles of known GMT markers, revealed a novel 31-gene GMT signature applicable as relevant input data for the connectivity map-based drug repurposing study. Using this gene signature, a number of small-molecule compounds were predicted as potent anti-GMT agents. Further ranking according to their blood-brain barrier permeability, as well as structural and transcriptomic similarities to known anti-GBM drugs, revealed SP600125, vemurafenib, FG-7142, dibenzoylmethane, and phensuximide as the most promising for GMT inhibition. In vitro validation showed that SP600125, which is most closely associated with GMT-related hub genes, effectively inhibited TGF-β1- and chemical hypoxia-induced GMT in U87 GBM cells by reducing morphological changes, migration, vasculogenic mimicry, and mesenchymal marker expression. These results clearly demonstrate the applicability of connectivity mapping as a powerful tool to accelerate the discovery of effective GMT-targeting therapies for GBM and significantly expand our understanding of the antitumor potential of SP600125.

Indexed as

AnthracenesAntineoplastic AgentsBrain NeoplasmsDrug RepositioningEpithelial-Mesenchymal TransitionGlioblastomaTranscriptomeCell Line, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansAnthracenesAntineoplastic Agentsdrug repositioningdrug repurposingglial-mesenchymal transitionglioblastomaproneural-mesenchymal transitionSP600125

Identifiers

PMID41097037
PMCPMC12524707

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.