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Abstract A038: Lomitapide enhances cytotoxic effects of temozolomide in chemo-resistant glioblastoma

2025· article· en· W4415444344 on OpenAlexaff
Alyona Ivanova, Taylor M. Wilson, Kimia Ghannad‐Zadeh, Robert Flick, Megan Wu, Sunit Das

Bibliographic record

VenueMolecular Cancer Therapeutics · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsTemozolomideGliomaCytotoxic T cellDrugCytotoxicityMevalonate pathwayCancerGlioblastomaProdrug

Abstract

fetched live from OpenAlex

Abstract Glioblastoma is the most prevalent and aggressive malignant primary brain tumour in adults, with a median survival following multi-modality therapy of 14.6 months. The current standard of care for patients with glioblastoma includes maximal safe surgical resection followed by radiation and chemotherapy with the alkylating agent, temozolomide. However, more than one-third of patients experience tumour progression during conventional therapy, suggesting that many of these patients harbor tumour cells that are intrinsically resistant to temozolomide-associated cytotoxicity. There is significant need for novel therapies to complement or improve our current treatments. Drug repurposing has gained attention in cancer research for its time- and monetary-efficiency in advancing chemical leads for clinical studies. The use of FDA-approved agents significantly decreases the time required for agents to go from bench to bedside, as toxicological data for these drugs is publicly available. In this study, we performed a high-throughput drug screen using a library of approximately 900 FDA-approved candidates. We identified eight agents that were predicted to have good brain penetration and exhibited cytotoxicity against glioma cells when combined with TMZ. As multiple recent reports have identified cholesterol biosynthesis as a vulnerability in glioblastoma, we chose to investigate the lipid-lowering drug (statin), lomitapide (Juxtapid). We find that lomitapide inhibits the mevalonate pathway of de novo cholesterol biosynthesis in TMZ-resistant glioma cells, resulting in cholesterol and ubiquinone (CoQ10) deficiency. Depletion of antioxidant CoQ10 in turn causes excessive accumulation of cellular reactive oxygen species that prime TMZ-resistant glioma cells for ferroptosis. In a mouse xenograft model, concurrent treatment with lomitapide and TMZ significantly delays tumour recurrence and prolongs survival, compared to TMZ alone. Our findings identify lomitapide as a potential therapeutic agent capable of targeting treatment resistance and delaying tumour progression in glioblastoma. Citation Format: Alyona Ivanova, Taylor M. Wilson, Kimia Ghannad-Zadeh, Esmond Tse, Robert Flick, Megan Wu, Sunit Das. Lomitapide enhances cytotoxic effects of temozolomide in chemo-resistant glioblastoma [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2025 Oct 22-26; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2025;24(10 Suppl):Abstract nr A038.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.267
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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