Troglitazone reverses the multiple drug resistance phenotype in cancer cells
Why this work is in the frame
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Bibliographic record
Abstract
A major problem in treating cancer is the development of drug resistance. We previously demonstrated doxorubicin (DOX) resistance in K562 human leukemia cells that was associated with upregulation of glyoxalase 1 (GLO-1) and histone H3 expression. The thiazolidinedione troglitazone (TRG) downregulated GLO-1 expression and further upregulated histone H3 expression and post-translational modifications in these cells, leading to a regained sensitivity to DOX. Given the pleiotropic effects of epigenetic changes in cancer development, we hypothesized that TRG may downregulate the multiple drug resistance (MDR) phenotype in a variety of cancer cells. To test this, MCF7 human breast cancer cells and K562 cells were cultured in the presence of low-dose DOX to establish DOX-resistant cell lines (K562/DOX and MCF7/DOX). The MDR phenotype was confirmed by Western blot analysis of the 170 kDa P-glycoprotein (Pgp) drug efflux pump multiple drug resistance protein 1 (MDR-1), and the breast cancer resistance protein (BCRP). TRG markedly decreased expression of both MDR-1 and BCRP in these cells, resulting in sensitivity to DOX. Silencing of MDR-1 expression also sensitized MCF7/DOX cells to DOX. Use of the specific and irreversible peroxisome proliferator-activated receptor gamma (PPARgamma) inhibitor GW9662 in the nanomolar range not only demonstrated that the action of TRG on MCF/DOX was PPARgamma-independent, but indicated that PPARgamma may play a role in the MDR phenotype, which is antagonized by TRG. We conclude that TRG is potentially a useful adjunct therapy in chemoresistant cancers.
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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 | 0.001 | 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) | 0.000 | 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 it