Jadomycin breast cancer cytotoxicity is mediated by a copper‐dependent, reactive oxygen species–inducing mechanism
Bibliographic record
Abstract
Jadomycins are natural products biosynthesized by the bacteria Streptomyces venezuelae which kill drug-sensitive and multidrug-resistant breast cancer cells in culture. Currently, the mechanisms of jadomycin cytotoxicity are poorly understood; however, reactive oxygen species (ROS)-induced DNA cleavage is suggested based on bacterial plasmid DNA cleavage studies. The objective of this study was to determine if and how ROS contribute to jadomycin cytotoxicity in drug-sensitive MCF7 (MCF7-CON) and taxol-resistant MCF7 (MCF7-TXL) breast cancer cells. As determined using an intracellular, fluorescent, ROS-detecting probe, jadomycins B, S, SPhG, and F dose dependently increased intracellular ROS activity 2.5- to 5.9-fold. Cotreatment with the antioxidant N-acetyl cysteine lowered ROS concentrations to below baseline levels and decreased the corresponding cytotoxic potency of the four jadomycins 1.9- to 3.3-fold, confirming a ROS-mediated mechanism. Addition of CuSO4 enhanced, whereas addition of the Cu(II)-chelator d-penicillamine reduced, the ROS generation and cytotoxicity of each jadomycin. Specific inhibitors of the antioxidant enzymes, superoxide dismutase 1, glutathione S-transferase, and thioredoxin reductase, but not catalase, enhanced jadomycin-mediated ROS generation and anticancer activity. In conclusion, the results indicate that jadomycin cytotoxicity involves the generation of cytosolic superoxide via a Cu(II)-jadomycin reaction, a mechanism common to all jadomycins tested and observed in MCF7-CON and drug-resistant MCF7-TXL cells. The superoxide dismutase 1, glutathione, and peroxiredoxin/thioredoxin cellular antioxidant enzyme pathways scavenged intracellular ROS generated by jadomycin treatment. Blocking these antioxidant pathways could serve as a strategy to enhance jadomycin cytotoxic potency in drug-sensitive and multidrug-resistant breast cancers.
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 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) | 0.000 | 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".