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A Novel Chromene-Based Pan-PI3 Kinase Inhibitor Displays Preclinical Activity in Leukemia and Myeloma.

2008· article· en· W2555789082 on OpenAlexaff
Xinliang Mao, Tabitha W. Wood, Xiaoming Wang, Johnathan St-Germain, Michael F. Moran, Alessandro Datti, Jeffrey L. Wrana, Robert A. Batey, Aaron D. Schimmer

Bibliographic record

VenueBlood · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer therapeutics and mechanisms
Canadian institutionsMount Sinai HospitalHospital for Sick ChildrenPrincess Margaret Cancer CentreUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsKinaseProtein kinase BCell cycleCancer researchCyclinLeukemiaCyclin-dependent kinasePI3K/AKT/mTOR pathwayBiologyChemistryPhosphorylationBiochemistryMolecular biologyCell biologyCellSignal transductionImmunology

Abstract

fetched live from OpenAlex

Abstract D-cyclins are universally dysregulated in multiple myeloma and frequently over-expressed in acute leukemia. Therefore, to better understand the regulation of the D-cyclins and identify leads for novel therapeutic agents for the treatment of hematologic malignancies, we conducted a high throughput screen of 50,000 novel chemical compounds to identify inhibitors of D-cyclin transactivation. From this screen, we identified a chromene-based compound 8-ethoxy-2-(4-fluorophenyl)-3-nitro-2H-chromene (pichromene). In secondary assays, pichromene reduced expression of cyclins D1, D2, and D3 in myeloma and leukemia cell lines at low micromolar concentrations. Furthermore, pichromene arrested the cells in the G0/G1 phase of the cell cycle. In myeloma and leukemia cell lines, pichromene decreased levels of phospho-AKT, but did not alter levels of total AKT. PI3 kinases regulate AKT phosphorylation that, in turn, regulate D-cyclin expression and cell cycle progression. Therefore, we evaluated the effects of pichromene on the enzymatic activity of PI3 kinases. In cell-free enzymatic assays, pichromene inhibited the enzymatic activity of all four isoforms of the PI3 kinase, PI3Kalpha, beta, delta and gamma, with similar efficacy. In contrast it did not markedly inhibit the enzymatic activities of unrelated kinases AKT 1, 2 or 3, PDK 1 or 2, or GSK3β or 3α at concentrations up to 300 μM in a similar cell-free assay. However, in intact cells, due to its inhibition of PI3 kinases, pichomene inhibited AKT activity as noted above. As inhibitors of PI3 kinases are pro-apoptotic and may have anti-cancer activity, we evaluated the effects of pichromene on the viability of leukemia and myeloma cells. Leukemia and myeloma cell lines were treated with increasing concentrations of pichromene and cell viability was measured after 72 hours by an MTS assay. Pichromene induced cell death in 9/10 leukemia and 9/10 myeloma cell lines with an ED50 < 10 μM. In contrast, it was less cytotoxic to primary normal hematopoietic cells obtained from volunteer donors of stem cells for allotransplant. Apoptosis was confirmed by Annexin V staining. Cell death was associated with caspase activation as demonstrated by the cleavage of caspase-3 and PARP through immunoblotting. Interestingly, U266 was the one myeloma cell line that was resistant to pichromene, and lacked detectable basal levels of phospho-AKT by immunoblotting. Given the effects of pichromene on malignant cells, we evaluated the efficacy of this compound in a leukemia xenograft mouse model. K562 cells were implanted subcutaneously into sublethally irradiated NOD/SCID mice. Mice were then treated with pichromene (50 mg/kg/day) or buffer control by oral gavage. Pichromene decreased tumor weight and volume by more than 35% as early as 8 days after treatment. No evidence of weight loss or gross organ toxicity was observed even when mice were treated with up to 500mg/kg/day of pichromene by oral gavage or intraperitoneally. Thus, in summary, we have identified a novel pan-inhibitor of PI3 kinases that displays preclinical efficacy in myeloma and leukemia.

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.023
GPT teacher head0.268
Teacher spread0.245 · 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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Citations1
Published2008
Admission routes1
Has abstractyes

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