Breathing New Life into TRAIL for Breast Cancer Therapy: Co-Delivery of pTRAIL and Complementary siRNAs Using Lipopolymers
Bibliographic record
Abstract
Preclinical studies showed that tumor necrosis factor - related apoptosis-inducing ligand (TRAIL) therapy is safe and effective to combat cancers, but clinical outcomes have been less than optimal due to short half-life of TRAIL protein, insufficient induction of apoptosis, and TRAIL resistance displayed in many tumors. In this study, we explored co-delivery of a TRAIL expressing plasmid (pTRAIL) and complementary small interfering RNAs (siRNAs) (silencing Bcl2-like 12 [BCL2L12] and superoxide dismutase 1 [SOD1]) to improve the response of breast cancer cells against TRAIL therapy. It is desirable to co-deliver the pDNA along with siRNA using a single delivery agent, but this is challenging given different structures of long/flexible pDNA and short/rigid siRNA. Toward this goal, we identified an aliphatic lipid-grafted low–molecular weight polyethylenimine (PEI) that accommodated both pDNA and siRNA in a single complex. The co-delivery of pTRAIL with BCL2L12- or SOD1-specific siRNAs resulted more significant cell death in different breast cancer cells compared with separate delivery without affecting nonmalignant cells viability. Ternary complexes of lipopolymer with pTRAIL and BCL2L12 siRNA significantly retarded the growth of breast cancer xenografts in mice. The enhanced anticancer activity was attributed to increased in situ secretion of TRAIL and sensitization of breast cancer cells against TRAIL by the co-delivered siRNAs. The lipid-grafted PEIs capable of co-delivering multiple types of nucleic acids can serve as powerful carriers for more effective complementary therapeutics. Graphical Abstract
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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".