Effective down‐regulation of signal transducer and activator of transcription 3 (STAT3) by polyplexes of siRNA and lipid‐substituted polyethyleneimine for sensitization of breast tumor cells to conventional chemotherapy
Bibliographic record
Abstract
Abstract Signal transducer and activator of transcription 3 (STAT3) is a transcription factor that plays a major role in the development of resistance to conventional anti‐cancer drugs in many types of cancer, when constitutively activated. Inhibition of STAT3 is considered as a promising strategy for inhibition of tumor growth and overcoming the drug resistance manifested. In this study, the capability of STAT3 knockdown by lipid substituted low molecular weight (2 kDa) polyethyleneimine (PEI2) complexes of STAT3–siRNA was assessed. The efficiency of PEI/STAT3‐siRNA polyplexes in the induction of STAT3 associated cell death in wild type and drug‐resistant MDA‐MB‐435 breast cancer cells as monotherapy and upon combination with chemotherapeutic agents, doxorubicin and paclitaxel, was also investigated. Our results identified linoleic acid‐substituted (PEI‐LA) polymer as the most efficient carrier among different lipid substituted PEI2 for siRNA delivery, leading to most STAT3 associated loss of cell viability in MDA‐MB‐435 cells. STAT3‐siRNA delivery by the PEI‐LA polymer resulted in efficient down‐regulation of STAT3 at both mRNA and protein levels. Furthermore, pre‐treatment of cancer cells with STAT3–siRNA formulation increased the cytotoxic effect of doxorubicin and paclitaxel in both wild type and drug resistant MDA‐MB‐435 cells. The results of this study point to the potential of PEI‐LA polyplexes of STAT3–siRNA as inhibitors of STAT3 expression in breast tumor cells. The results also demonstrate an improved efficacy for chemotherapeutic drugs in combination with lipid‐substituted low molecular weight PEI‐LA/STAT3‐siRNA complexes in comparison to drug therapy alone. © 2013 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 102A: 3216–3228, 2014.
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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) | 0.001 | 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) | 0.001 | 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".