Omics · study · 2026
A combinatorial EVs-miRNA signature mediates the anti-tumoral activity of NFAT3- regulated extracellular vesicles in aggressive cancers.
Listed in NCBI GEO
Aggressive cancers such as triple-negative breast cancer (TNBC) and pancreatic cancer remain difficult to treat because their malignant behavior is driven by complex gene networks rather than single oncogenic targets.
Description
Our study identifies a NFAT3 transcription factor-dependent miRNAs signature that suppresses tumor aggressiveness through extracellular vesicles (EVs). Functional analyses demonstrated that a specific combination of fifteen miRNAs (miR-Comb 15) is required to inhibit cancer cell proliferation and invasion across TNBC and pancreatic cancer models, whereas individual miRNA are insufficient to reproduce the full anti-tumoral effect.
To enable therapeutic translation, we engineered EVs derived from HEK 293T, a non- tumoral and scalable vesicle source. Using an optimized exogenous pH-gradient loading strategy, miR-Comb 15 was efficiently incorporated into EVs without altering their integrity or intrinsic bioactivity. Among multiple delivery platforms tested, miR-Comb 15 loaded HEK 293T EVs consistently exhibited superior anti-tumoral efficacy both in vitro and in vivo.
Read the rest (1 more)
Together, these findings establish a strong mechanistic link between transcriptional regulation and EVs-mediated RNA delivery and demonstrates that rationally designed RNA combinations delivered by EVs represent a promising therapeutic strategy for aggressive cancers.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE318nnn/GSE318086 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE318086 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA1416444 ncbi.nlm.nih.gov/bioproject/PRJNA1416444 ↗
project · from NCBI GEO
Topics
- Stated by source
- Homo sapiens · Non-coding RNA profiling by high throughput sequencing
- From keywords
- Life Sciences
- Inferred from text
- Cancer 75%
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE318086 | 14 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[disease].local:disease:cancer | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].local:field:life-sciences | mapping · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[method].geo_series_type:non-coding-rna-profiling-by-high-throughput-sequencing | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /gdstype |
| concepts[organism].NCBITaxon:9606 | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /taxon |
| description | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /summary |
| publication_date | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| title | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /title |