Modulation of Hypoxia-Induced Chemoresistance to Polymeric Micellar Cisplatin: The Effect of Ligand Modification of Micellar Carrier Versus Inhibition of the Mediators of Drug Resistance
Bibliographic record
Abstract
Hypoxia can induce chemoresistance, which is a significant clinical obstacle in cancer therapy. Here, we assessed development of hypoxia-induced chemoresistance (HICR) against free versus polymeric cisplatin micelles in a triple negative breast cancer cell line, MDA-MB-231. We then explored two strategies for the modulation of HICR against cisplatin micelles: a) the development of actively targeted micelles; and b) combination therapy with modulators of HICR in MDA-MB-231 cells. Actively targeted cisplatin micelles were prepared through surface modification of acetal-poly(ethylene oxide)-poly(α-carboxyl-ε-caprolactone) (acetal-PEO-PCCL) micelles with epidermal growth factor receptor (EGFR)-targeting peptide, GE11 (YHWYGYTPQNVI). Our results showed that hypoxia induced resistance against free and cisplatin micelles in MDA-MB-231 cells. A significant increase in micellar cisplatin uptake was observed in MDA-MB-231 cells that overexpress EGFR, following surface modification of micelles with GE11. This did not lead to increased cytotoxicity of micellar cisplatin, however. On the other hand, the addition of pharmacological inhibitors of key molecules involved in HICR in MDA-MB-231 cells, i.e., inhibitors of hypoxia inducing factor-1 (HIF-1) and signal transducer and activator of transcription 3 (STAT3), substantially enhanced the cytotoxicity of free and cisplatin micelles. The results indicated the potential benefit of combination therapy with HIF-1 and STAT3 inhibitors in overcoming HICR to free or micellar cisplatin.
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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) | 0.000 | 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 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".