A novel polyethyleneimine-coated adeno-associated virus-like particle formulation for efficient siRNA delivery in breast cancer therapy: preparation and in vitro analysis
Bibliographic record
Abstract
BACKGROUND: Systemic delivery of small interfering RNA (siRNA) is limited by its poor stability and limited cell-penetrating properties. To overcome these limitations, we designed an efficient siRNA delivery system using polyethyleneimine-coated virus-like particles derived from adeno-associated virus type 2 (PEI-AAV2-VLPs). METHODS: AAV2-VLPs were produced in insect cells by infection with a baculovirus vector containing three AAV2 capsid genes. Using this method, we generated well dispersed AAV2-VLPs with an average diameter of 20 nm, similar to that of the wild-type AAV2 capsid. The nanoparticles were subsequently purified by chromatography and three viral capsid proteins were confirmed by Western blot. The negatively charged AAV2-VLPs were surface-coated with PEI to develop cationic nanoparticles, and the formulation was used for efficient siRNA delivery under optimized transfection conditions. RESULTS: PEI-AAV2-VLPs were able to condense siRNA and to protect it from degradation by nucleases, as confirmed by gel electrophoresis. siRNA delivery mediated by PEI-AAV2-VLPs resulted in a high transfection rate in MCF-7 breast cancer cells with no significant cytotoxicity. A cell death assay also confirmed the efficacy and functionality of this novel siRNA formulation towards MCF-7 cancer cells, in which more than 60% of cell death was induced within 72 hours of transfection. CONCLUSION: The present study explores the potential of virus-like particles as a new approach for gene delivery and confirms its potential for breast cancer therapy.
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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".