Combined treatment of Bcl‐2 antisense oligodeoxynucleotides (G3139), p‐glycoprotein inhibitor (PSC833), and sterically stabilized liposomal doxorubicin suppresses growth of drug‐resistant growth of drug‐resistant breast cancer in severely combined immunodeficient mice
Bibliographic record
Abstract
We studied the possibility of increasing sensitization of drug-resistant MDA435/LCC6 multidrug-resistant (MDR) human breast cancer cells to doxorubicin (DOX) by increasing cellular drug retention with P-glycoprotein (P-gp) inhibitor PSC833 in combination with induction of cell death through down-regulation of Bcl-2 protein using Bcl-2 antisense (G3139). In in vitro cytotoxicity assays, the combination of G3139 with DOX exhibited 40% increased cytotoxicity in both wild-type (WT) and MDR cells. PSC833 increased the cytotoxicity of DOX and Taxol with complete and partial reversal of the resistance of MDR cells to DOX and Taxol, respectively. The presence of G3139 did not increase the cytotoxicity of PSC833 combined with DOX or Taxol in both cell lines. In vivo studies with WT and MDR cell lines transplanted into severely combined immunodeficient mice demonstrated that G3139 (5 mg/kg) was able to suppress the growth of both WT and MDR tumors to an equivalent extent. PSC833 (100 mg/kg) partially restored the sensitivity of resistant tumors to DOX, and the combination of G3139 and PSC833 with liposomal DOX showed maximum growth suppression of MDR tumors compared with individual treatments. The improved efficacy of this treatment was attributed to Bcl-2 antisense-induced apoptosis, combined with cellular retention of DOX in tumor cells via P-gp blockade.
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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 | 0.001 |
| 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".