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Record W2075167686 · doi:10.1158/1538-7445.am10-2529

Abstract 2529: The anti-malarial agent Mefloquine preferentially demonstrates pre-clinical activity in leukemia and myeloma cells through STAT1-induced reactive oxygen species production

2010· article· en· W2075167686 on OpenAlexaff
Mahadeo A. Sukhai, Xiaoming Li, Xiaoming Wang, Rose Hurren, Marcela Gronda, Joyce Sun, Sue Chow, Rod Bremner, David W. Hedley, Aaron D. Schimmer

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer therapeutics and mechanisms
Canadian institutionsOntario Institute for Cancer Research
Fundersnot available
KeywordsMefloquineLeukemiaPharmacologyProgrammed cell deathReactive oxygen speciesImmunologyMedicineChemistryApoptosisChloroquineMalariaBiochemistry

Abstract

fetched live from OpenAlex

Abstract Off patent drugs with previously unrecognized anti-leukemia activity can be rapidly repurposed for this new indication, given their prior safety and toxicity testing. By screening a group of anti-malarial compounds for anti-cancer activity, we identified mefloquine, a quinoline licensed in oral formulation for the treatment of malaria. As an anti-cancer agent, we demonstrated that mefloquine decreased the viability of 9/9 leukemia cell lines with an LD50 <7.5 uM, and 9/9 myeloma cell lines with an LD50 <5.0 uM. Furthermore, mefloquine demonstrated induced cell death in primary AML samples (n = 3; LD50 <7.5 uM), but not normal peripheral blood stem cells. Given its in vitro activity, we evaluated the effects of oral mefloquine in mouse xenograft models of leukemia. Sublethally irradiated SCID mice were injected subcutaneously with OCI-AML2 or K562 human leukemia cells or MDAY-D2 murine leukemia cells, and treated with 50 mg/kg mefloquine, or vehicle alone by oral gavage. Oral mefloquine decreased tumor weight and volume in all 3 mouse models without toxicity. Mechanistically, mefloquine induced reactive oxygen species (ROS) in leukemia cells at times preceding and concentrations associated with cell death. Blockade of ROS by N-acetyl-L-cysteine (NAC) abrogated mefloquine sensitivity, suggesting that mefloquine-mediated cell death in AML was ROS-dependent. To further understand the mechanism of mefloquine-mediated cytoxicity, whole genome gene expression oligonucleotide array analysis of AML cells treated with mefloquine was conducted. The gene expression pattern of cells treated with mefloquine strongly resembled gene signatures associated with activated Toll-like receptor and interferon response pathways. STAT1 and NF-κB, both downstream transcription factor components of TLR-IFN signaling, were activated, as were downstream targets IRF1, IRF7 and IL-8, at times that preceded mefloquine-induced cell death. Gene expression changes were validated by Q-RT-PCR, and are potential biomarkers of mefloquine activity in cells. This pathway appears functionally important for mefloquine-mediated cell death, as cell lines defective for STAT1 signaling components showed decreased cell death after mefloquine treatment. These lines also showed decreased ability to generate ROS in response to mefloquine treatment, suggesting that mefloquine-induced ROS was produced through a STAT1-dependent mechanism. Taken together, our data demonstrate that the anti-malarial mefloquine displays significant pre-clinical activity in leukemia and myeloma cells, likely through a STAT1-dependent induction of ROS that is triggered by activation of the TLR-IFN cytokine axis in cells. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2529.

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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.103
GPT teacher head0.410
Teacher spread0.307 · 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
Published2010
Admission routes1
Has abstractyes

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