ArticleACS biomaterials science & engineering2025
Enhancing Gene Delivery to Breast Cancer with Highly Efficient siRNA Loading and pH-Responsive Small Extracellular Vesicles.
Article in ACS biomaterials science & engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Engineering stimuli-responsive extracellular vesicles for enhanced anticancer therapeutics.Current opinion in biomedical engineering · 2026Article
- M1 Macrophage-Derived Small Extracellular Vesicles as Synergistic Nanotherapeutics: Harnessing Intrinsic Anticancer Activity and Drug Delivery Capacity.Journal of extracellular vesicles · 2026Article
- Small extracellular vesicles as system-level regulators and predictive biomarkers in breast cancer progression and chemoresistance.Frontiers in pharmacology · 2026Review
- Regulatory mechanisms of deer antler extracellular vesicles in multilevel tissue repair: a state-of-the-art review.Frontiers in pharmacology · 2026Review
- Extracellular vesicle-mediated immunomodulation and targeted delivery: breakthroughs and challenges in rheumatoid arthritis therapy.Frontiers in immunology · 2026Review
- N-Amino Peptide-Graphene Quantum Dot Loaded Small Extracellular Vesicles for Targeted Therapy of Tauopathies.Advanced nanobiomed research · 2025Article
- Extracellular Vesicle-Based Drug Delivery Systems in Cancer Therapy.International journal of molecular sciences · 2025Review
- Bottom-up Biomaterial strategies for creating tailored stem cells in regenerative medicine.Frontiers in bioengineering and biotechnology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Small extracellular vesicles (sEVs) are promising nanocarriers for drug delivery to treat a wide range of diseases due to their natural origin and innate homing properties. However, suboptimal therapeutic effects, attributed to ineffective targeting, limited lysosomal escape, and insufficient delivery, remain challenges in effectively delivering therapeutic cargo. Despite advances in sEV-based drug delivery systems, conventional approaches need improvement to address low drug-loading efficiency and to develop surface functionalization techniques for precise targeting of cells of interest, all while preserving the membrane integrity of sEVs. We report an enhanced gene delivery system using multifunctional sEVs for highly efficient siRNA loading and delivery. The integration of chiral graphene quantum dots enhanced the loading capacity while preserving the structural integrity of the sEVs. Additionally, lysosomal escape is facilitated by functionalizing sEVs with pH-responsive peptides, fully harnessing the inherent homing effect of sEVs for targeted and precise delivery. These sEVs achieved a 1.74-fold increase in cytosolic cargo delivery compared to unmodified sEVs, resulting in substantial gene silencing of around 73%. Our approach has significant potential to advance sEV-based gene delivery in order to accelerate clinical progress.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.