Pharmacological interactions of jadomycin B with topoisomerase poisons in MDA-MB-231 human breast cancer cells
Bibliographic record
Abstract
Jadomycin B, a natural product isolated from Streptomyces venezuelae, exerts an anti-cancer effect on human triple negative breast cancer cells in vitro and has anti-tumoral effects in vivo in animal models of breast cancer. One proposed mechanism for this anti-cancer effect is through interaction with topoisomerase 2 (TOP2). Based on the previously described interactions between jadomycin B and TOP2 we hypothesized that jadomycin B will act additively with TOP2 poisons and produce a similar functional outcome in eliciting cell cycle arrest. Combined treatments of jadomycin B and the TOP2 poisons doxorubicin or mitoxantrone produced moderately synergistic to additive cytotoxicity (combination index values ranging from 0.72–0.94) in MDA-MB-231 cells. In comparison, combined mitoxantrone and doxorubicin produced additive cytotoxicity (combination index values 0.96–1.11). Jadomycin B combined with the proteosome inhibitor MG132 had additive cytotoxicity (combination index values 0.76–1.18). In contrast, mitoxantrone or doxorubicin cytotoxicity was antagonized by MG132 (combination index values 1.21–2.31). Jadomycin B treatment arrested cells in S-phase ( P = 0.0024) as opposed to mitoxantrone which caused G2/M-phase arrest ( P < 0.0001). In conclusion, jadomycin B interacts differently than known TOP2 poisons in combination, supporting a novel pharmacological mechanism(s) of action for jadomycin B cytotoxicity.
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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 | 0.001 |
| 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".