Increased intracellular drug accumulation and complete chemosensitization achieved in multidrug-resistant solid tumors by co-administering valspodar(PSC 833) with sterically stabilized liposomal doxorubicin
Bibliographic record
Abstract
We have previously demonstrated that liposome encapsulation of doxorubicin (DOX) can alleviate adverse interactions with non-encapsulated DOX and the cyclosporine multidrug-resistant (MDR) modulator Valspodar. We have now investigated the behavior of different liposomal DOX formulations in MDA435LCC6/MDR-1 human breast cancer solid tumor xenograft models to identify liposome characteristics associated with enhanced therapeutic activity and the mechanism whereby increased chemosensitization is achieved. Toxicity studies incorporating conventional phosphatidylcholine (PC)/cholesterol (chol) and sterically stabilized (polyethylene glycol 2000 [PEG]-containing) formulations of DOX indicated that whereas PC/Chol DOX was approximately 3-fold more toxic in the presence of Valspodar, PEG containing distearoylglycerophosphocholine (DSPC)/Chol DOX was minimally affected. In mice bearing MDR tumors, co-administration of Valspodar and egg phosphocholine (EPC)/Chol DOX resulted in modest MDR modulation and efficacy, whereas the sterically stabilized formulation induced reductions in tumor growth equivalent to that achieved for drug-sensitive tumors treated with non-encapsulated DOX. Pharmacokinetic studies revealed a 2.5-fold increase in plasma DOX area under the curve (AUC) upon co-administration of Valspodar with EPC/Chol DOX whereas no such alterations were observed with the sterically stabilized liposomes. Compared to non-encapsulated DOX combined with Valspodar, improvements in efficacy and toxicity correlated with the extent to which liposomal DOX formulations were able to circumvent pharmacokinetic interactions. Confocal microscopy demonstrated that Valspodar increased cell-associated DOX which correlated with the level of anti-tumor efficacy.
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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 | 0.001 | 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 | 0.001 |
| 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 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".