Jadomycins are cytotoxic to ABCB1-, ABCC1-, and ABCG2-overexpressing MCF7 breast cancer cells
Bibliographic record
Abstract
Multidrug resistance remains a major obstacle in the effective treatment of metastatic breast cancer. One mechanism by which multidrug resistance is conferred is the decreased intracellular drug accumulation due to the upregulation of the ATP-binding cassette (ABC) transporters. We have previously demonstrated that jadomycins, polyketide-derived natural products produced by Streptomyces venezuelae ISP5230, inhibit the growth of the human breast ductal carcinoma cell lines T47D and MDA-MB-435. To expand our understanding of jadomycin pharmacology, the goal of the present study was to determine whether the function of ABC efflux transporters affects the anticancer activity of jadomycins to MCF7 breast cancer cells. Seven jadomycin analogs (DNV, B, L, SPhG, F, S, and T) effectively reduced the viability of MCF7 control and ABCB1-, ABCC1-, or ABCG2-overexpressing drug-resistant MCF7 breast cancer cells as measured by methyltetrazolium cell viability assays and lactate dehydrogenase cytotoxicity assays. The inhibition of ABCB1, ABCC1, or ABCG2 with verapamil, MK-571, or Ko-143, respectively, did not augment the cytotoxicity of jadomycins DNV, B, L, SPhG, F, S, or T in drug-resistant MCF7 cells. Furthermore, jadomycins B, L, SPhG, F, S, and T did not increase the intracellular accumulation of ABCB1, ABCC1, or ABCG2 fluorescent substrates in HEK-293 cells stably transfected with ABCB1, ABCC1, or ABCG2. We conclude that jadomycins B, L, SPhG, F, S, and T are effective agents in the eradication of MCF7 breast cancer cells grown in culture, and that their cytotoxicities are minimally affected by ABCB1, ABCC1, and ABCG2 efflux transporter function.
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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".