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Record W2326222495 · doi:10.1158/1538-7445.am10-4538

Abstract 4538: Inhibition of mitochondrial protein synthesis with antimicrobial tigecycline preferentially induces cell death in leukemia cells

2010· article· en· W2326222495 on OpenAlexaff
Marko Škrtić, Paul A. Spagnuolo, Xiaoming Wang, Marcela Gronda, Rose Hurren, Craig D. Simpson, Sonali B. Fonseca, Alessandro Datti, Jean Wang, John E. Dick, Jeffrey L. Wrana, Shana O. Kelley, Aaron D. Schimmer

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer therapeutics and mechanisms
Canadian institutionsStem Cell NetworkLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsTigecyclineLeukemiaMyeloid leukemiaCytotoxic T cellDaunorubicinClonogenic assayMedicinePharmacologyApoptosisBiologyCancer researchImmunologyMicrobiologyAntibioticsIn vitroBiochemistry

Abstract

fetched live from OpenAlex

Abstract To identify known drugs with unrecognized anti-leukemia activity, we compiled a library of 500 on patent and off patent compounds, and screened it to identify compounds cytotoxic to leukemia cell lines. From this screen we identified Tigecycline, an antibiotic approved for the treatment of cutaneous and intra-abdominal infections. Tigecycline induced cell death in leukemia cell lines (LD50 3 to 8 μM, n = 6 cell lines) and primary Acute Myeloid Leukemia (AML) patient samples (LD50 5-10 μM, n = 7), preferentially over normal hematopoietic cells (10% cell death at 20 μM, n = 4) by MTS assays and Annexin V staining. Likewise, in colony formation assays, Tigecycline (5μM) reduced the clonogenic growth of primary AML patient samples (n = 4) by 95±1.5 %, demonstrating an effect on leukemia progenitor cells. In contrast, 5 μM of Tigecycline reduced the clonogenic growth of normal hematopoetic cells by 34± 5% (n = 5). Although Tigecycline is structurally related to tetracycline and minocycline, these drugs were not cytotoxic towards AML cell lines up to 25 μM. Thus, Tigecycline appears preferentially cytotoxic to leukemia cells at pharmacologically achievable concentrations. Given the anti-leukemic effects of Tigecycline in vitro, we evaluated the efficacy of Tigecycline as a potential anti-leukemic agent in vivo. Mice injected subcutaneously with OCI-AML2 leukemia cells were treated with Tigecycline 50 mg/kg i.p. daily. Compared to control, Tigecycline decreased tumour mass and volume without toxicity. We also assessed the effect of Tigecycline on primary AML stem cells defined by their ability to initiate leukemic engraftment in vivo. NOD-SCID mice were injected intra-femorally with primary AML cells. Two weeks after injection, mice were treated with Tigecycline 50 mg/kg i.p. daily for two weeks. After treatment, engraftment of human AML cells was measured by flow cytometry. Compared to control, Tigecycline decreased engraftment of AML cells without toxicity. Tigecycline binds and inhibits the bacterial 30S ribosome. Bacterial ribosomes are more homologous to mitochondrial ribosomes than cytosolic ribosomes, so we compared the effects of Tigecycline on mitochondrial and cytosolic protein synthesis. At times preceding the onset of cell death, Tigecycline decreased levels of the mitochondrial protein Cox-1. In contrast, it did not decrease the expression of cytosolic short half-life proteins Bcl-XL and XIAP, suggesting a preferential effect on mitochondrial protein synthesis. Thus, Tigecycline demonstrated preclinical activity through a mechanism related to mitochondrial protein synthesis inhibition. Moreover, Tigecycline appeared cytotoxic to leukemia stem cells over normal hematopoetic stem cells. Given its prior pharmacology and toxicology testing, Tigecycline could be rapidly repositioned for a new anti-leukemic indication. 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 4538.

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)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.033
GPT teacher head0.316
Teacher spread0.283 · 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".

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Citations0
Published2010
Admission routes1
Has abstractyes

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