Anthracyclines Suppress Both NADPH Oxidase- Dependent and -Independent NETosis in Human Neutrophils
Bibliographic record
Abstract
Neutrophil extracellular traps (NETs) are cytotoxic DNA-protein complexes that play positive and negative roles in combating infection, inflammation, organ damage, autoimmunity, sepsis and cancer. However, NETosis regulatory effects of most of the clinically used drugs are not clearly established. Several recent studies highlight the relevance of NETs in promoting both cancer cell death and metastasis. Here, we screened the NETosis regulatory ability of 126 compounds belonging to 39 classes of drugs commonly used for treating cancer, blood cell disorders and other diseases. Our studies show that anthracyclines (e.g., epirubicin, daunorubicin, doxorubicin, and idarubicin) consistently suppress both NADPH oxidase-dependent and -independent types of NETosis in human neutrophils, ex vivo. The intercalating property of anthracycline may be enough to alter the transcription initiation and lead NETosis inhibition. Notably, the inhibitory doses of anthracyclines neither suppress the production of reactive oxygen species that are necessary for antimicrobial functions nor induce apoptotic cell death in neutrophils. Therefore, anthracyclines are a major class of drug that suppresses NETosis. The dexrazoxane, a cardioprotective agent, used for limiting the side effects of anthracyclines, neither affect NETosis nor alter the ability of anthracyclines to suppress NETosis. Hence, at correct doses, anthracyclines together with dexrazoxane could be considered as a therapeutic candidate drug for suppressing unwanted NETosis in NET-related diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".