Reversal of P-glycoprotein-mediated multidrug resistance by novel curcumin analogues in paclitaxel-resistant human breast cancer cells
Bibliographic record
Abstract
Multidrug resistance (MDR) is a major obstacle for successful cancer chemotherapy, and the main cause of MDR has been attributed to overexpression of P-glycoprotein (P-gp). In this present study, four P-gp modulators (E,E)-4,6-bis(styryl)-2-(substituted amino)-pyrimidines were evaluated for their activity in a breast cancer cell line overexpressing P-gp (LCC6MDR). The four modulators displayed significantly better P-gp modulating activity compared with the positive control verapamil (RF = 5.4), with a relative fold (RF) increase in activity ranging from 33.3 to 86.0. In contrast to compounds a and c that exhibited lower cytotoxicity, compounds b and d were nontoxic towards both cancer cells and normal cells, with IC 50 values greater than 100 μmol/L. The qRT-PCR results demonstrated that after exposure to 2 μmol/L of compounds a, b, c, and d, the mRNA expression level of MDR1 in LCC6MDR cells decreased to 45%, 50%, 38%, and 51%, respectively. However, the Western-blot results indicated that compound c could reverse P-gp mediated MDR, but not via decreases in protein expression. DOX and Rh123 accumulation and efflux results further confirmed that the reversal of MDR activity happens via inhibition of P-gp efflux and increases in intracellular drug accumulation. These results demonstrated that compound c has low toxicity and is an efficient P-gp modulator, highlighting its potential as a promising candidate for P-gp-mediated reversal of MDR.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".