Chelation of intracellular iron with the antifungal agent ciclopirox olamine induces cell death in leukemia and myeloma cells
Bibliographic record
Abstract
Off-patent drugs with previously unrecognized anticancer activity could be rapidly repurposed for this new indication. To identify such compounds, we conducted 2 independent cell-based chemical screens and identified the antimicrobial ciclopirox olamine (CPX) in both screens. CPX decreased cell growth and viability of malignant leukemia, myeloma, and solid tumor cell lines as well as primary AML patient samples at low-micromolar concentrations that appear pharmacologically achievable. Furthermore, oral CPX decreased tumor weight and volume in 3 mouse models of leukemia by up to 65% compared with control without evidence of weight loss or gross organ toxicity. In addition, oral CPX prevented the engraftment of primary AML cells in nonobese diabetic/severe combined immunodeficiency mouse models, thereby establishing its ability to target leukemia stem cells. Mechanistically, CPX bound intracellular iron, and this intracellular iron chelation was functionally important for its cytotoxicity. By electron paramagnetic resonance, CPX inhibited the iron-dependent enzyme ribonucleotide reductase at concentrations associated with cell death. Thus, in summary, CPX has previously unrecognized anticancer activity at concentrations that are pharmacologically achievable. Therefore, CPX could be rapidly repurposed for the treatment of malignancies, including leukemia and myeloma.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".