Characterization of the anticancer pharmacology of novel jadomycin molecules
Bibliographic record
Abstract
Introduction Jadomycins are natural anticancer products produced by the soil bacteria S. Venezuelae . The object was to examine the cytotoxicity and mechanisms of action of jadomycins in control and taxol, etoposide, and mitoxantrone‐resistant MCF7 breast cancer cells that respectively overexpress the ATP binding cassette (ABC) transporters ABCB1, ABCC1, or ABCG2. Methods and Results Lactate dehydrogenase (LDH) assays were used to determine the cytotoxicity of jadomycins DNV, L, B, SPhG, F, W, S, and T. All jadomycins were 100% efficacious at killing control MCF7 cells with EC 50 values of 4.3 to 42.3 μM. The jadomycins effectively killed the ABCB1, ABCC1, and ABCG2 overexpressing MCF7 cells with a slight 1.5–3.5‐fold reduction in potency relative to the control MCF7 cells. Using PCR cancer gene arrays and quantitative PCR assays, the expression of 15 cancer‐related genes was found to be altered by jadomycin B or S treatment. This included up to a 23.7‐fold increase in the expression of the antioxidant encoding thioredoxin reductase 1 ( TXNRD1 ). Reactive oxygen species (ROS) assays indicated ROS levels are elevated after jadomycin B, S, or SPhG treatment. Conclusions Jadomycin cytotoxicity in MCF7 breast cancer cells is not dependent of ABCB1, ABCC1, or ABCG2 function. The mechanisms of jadomycin action may include the production of ROS and subsequent cellular oxidative damage. This project is funded by NSERC, CIHR, NSHRF, and BHCRI.
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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".