Characterization of a Potent, Selective, and Safe Inhibitor, Ac15(Az8)2, in Reversing Multidrug Resistance Mediated by Breast Cancer Resistance Protein (BCRP/ABCG2)
Bibliographic record
Abstract
Overexpression of breast cancer resistance transporter (BCRP/ABCG2) in cancers has been explained for the failure of chemotherapy in clinic. Inhibition of the transport activity of BCRP during chemotherapy should reverse multidrug resistance. In this study, a triazole-bridged flavonoid dimer Ac15(Az8)2 was identified as a potent, nontoxic, and selective BCRP inhibitor. Using BCRP-overexpressing cell lines, its EC50 for reversing BCRP-mediated topotecan resistance was 3 nM in MCF7/MX100 and 72 nM in S1M180 in vitro. Mechanistic studies revealed that Ac15(Az8)2 restored intracellular drug accumulation by inhibiting BCRP-ATPase activity and drug efflux. It did not down-regulate the cell surface BCRP level to enhance drug retention. It was not a transport substrate of BCRP and showed a non-competitive relationship with DOX in binding to BCRP. A pharmacokinetic study revealed that I.P. administration of 45 mg/kg of Ac15(Az8)2 resulted in plasma concentration above its EC50 (72 nM) for longer than 24 h. It increased the AUC of topotecan by 2-fold. In an in vivo model of BCRP-overexpressing S1M180 xenograft in Balb/c nude mice, it significantly reversed BCRP-mediated topotecan resistance and inhibited tumor growth by 40% with no serious body weight loss or death incidence. Moreover, it also increased the topotecan level in the S1M180 xenograft by 2-fold. Our results suggest that Ac15(Az8)2 is a promising candidate for further investigation into combination therapy for treating BCRP-overexpressing cancers.
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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".