Keystone Symposia "ncRNAs in Development and Cancer", Vancouver, Canada: Increased release of exosomes and export of invasion-modulating miRNAs miR921, -23b, -and -224 from metastatic urothelial carcinoma cells
Bibliographic record
Abstract
Cancer cells secrete soluble factors and various extracellular vesicles, including exosomes, into their tissue microenvironment. The secretion of exosomes is speculated to facilitate local invasion and increase the propensity of tumors to form distant metastases. Here we present a characterization of exosome vesicles from isogenic urothelial carcinoma cell lines, with different metastatic propensity by western blotting, electron microscopy, nanoparticle tracking analysis, dynamic light scattering, and profiling of 671 miRNAs by qRT-PCR. An increase in the number of multivesicular bodies and exosomes was observed for metastatic FL3 cells compared to isogenic non-metastatic T24 cells. The release was significantly inhibited by knockdown of Rab27b and pharmacological inhibition of nsmase2 by GW4869. miRNA profiling was conducted on parental cells and their secreted exosomes. Here, selective export of miR921, 23b, and 224 was observed from metastatic cell lines compared to their non- or low-metastatic isogenic parental cells and primary urothelial cells. Both inhibition of exosome release (Rab27b knockdown, GW4869 treatment) and ectopic overexpression of miR921, 23b, 224 inhibited cellular invasion through matrigel, whereas cellular viability was unaffected. Our results indicate that metastatic urothelial carcinoma cells display altered exosome secretion and -content, which may affect steps of the metastatic cascade such as local invasion.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.009 |
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 source (direct Gemma or distilled Codex), 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".