Mesenchymal stem cell-derived small extracellular vesicles as a delivery vehicle of oncolytic reovirus
Bibliographic record
Abstract
AIM: The oncolytic reovirus has demonstrated efficacy against various cancer types in preclinical and clinical studies. However, its anti-tumor activity is limited. This study aimed to develop a novel drug delivery system (DDS) using small extracellular vesicles (sEVs) derived from human adipose-derived mesenchymal stem cells to enhance the therapeutic potential of reovirus. MATERIALS AND METHODS: sEVs, which offer distinct advantages over traditional systems such as nanoparticles due to their natural biocompatibility, low immunogenicity, ability to cross biological barriers, and cell-derived targeting properties, were engineered to encapsulate reovirus particles (sEVs-reo). The anti-tumor activity of sEVs-reo was evaluated using colorectal cancer cell lines HCT116 and SW480. Additionally, resistance to neutralizing antibodies, internalization by cancer cells, and efficacy against junctional adhesion molecule-A(JAM-A)-knockout colon cancer cells resistant to reovirus, generated via CRISPR/Cas9, were assessed. KEY FINDINGS: sEVs-reo encapsulated reovirus particles effectively, and at a concentration of 0.5 μg/ml, reduced viable tumor cells by 60.3 % in HCT116 and 42.5 % in SW480. Remarkably, sEVs-reo exhibited significant efficacy even in the presence of neutralizing antibodies, including anti-σ1 antibodies and serum from reovirus-infected mice. sEVs-reo were rapidly internalized by cancer cells within 4 h while exhibiting reduced immunogenicity relative to reovirus, and demonstrated significant anti-tumor activity against JAM-A-deficient colon cancer cells. SIGNIFICANCE: This study demonstrates that sEVs-reo can address key challenges associated with oncolytic virotherapy. These findings support potential of sEVs as a novel and effective DDS for reovirus in colon cancer treatment, while offering a versatile platform to enhance the efficacy of other oncolytic viruses.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".